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LitCovid100 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: First expert elicitation of knowledge on drivers of emergence of the COVID-19 in pets. Infection with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) induces the coronavirus infectious disease 19 (COVID-19). Its pandemic form in human population and its probable animal origin, along with recent case reports in pets, make drivers of emergence crucial in domestic carnivore pets, especially cats, dogs and ferrets. Few data are available in these species; we first listed forty-six possible drivers of emergence of COVID-19 in pets, regrouped in eight domains (i.e. pathogen/disease characteristics, spatial-temporal distance of outbreaks, ability to monitor, disease treatment and control, characteristics of pets, changes in climate conditions, wildlife interface, human activity, and economic and trade activities). Secondly, we developed a scoring system per driver, then elicited scientific experts (N = 33) to: (a) allocate a score to each driver, (b) weight the drivers scores within each domain and (c) weight the different domains between them. Thirdly, an overall weighted score per driver was calculated; drivers were ranked in decreasing order. Fourthly, a regression tree analysis was used to group drivers with comparable likelihood to play a role in the emergence of COVID-19 in pets. Finally, the robustness of the expert elicitation was verified. Five drivers were ranked with the highest probability to play a key role in the emergence of COVID-19 in pets: availability and quality of diagnostic tools, human density close to pets, ability of preventive/control measures to avoid the disease introduction or spread in a country (except treatment, vaccination and reservoir(s) control), current species specificity of the disease-causing agent and current knowledge on the pathogen. As scientific knowledge on the topic is scarce and still uncertain, expert elicitation of knowledge, in addition with clustering and sensitivity analyses, is of prime importance to prioritize future studies, starting from the top five drivers. The present methodology is applicable to other emerging pet diseases.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid101 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: COVID-19 Infection Among Healthcare Workers: Serological Findings Supporting Routine Testing. A growing body of evidence demonstrates that asymptomatic and pre-symptomatic transmission of SARS-CoV-2 is a major contributor to the COVID-19 pandemic. Frontline healthcare workers in COVID-19 hotspots have faced numerous challenges, including shortages of personal protective equipment (PPE) and difficulties acquiring clinical testing. The magnitude of the exposure of healthcare workers and the potential for asymptomatic transmission makes it critical to understand the incidence of infection in this population. To determine the prevalence of asymptomatic SARS-CoV-2 infection amongst healthcare workers, we studied frontline staff working in the Montefiore Health System in New York City. All participants were asymptomatic at the time of testing and were tested by RT-qPCR and for anti-SARS-CoV-2 antibodies. The medical, occupational, and COVID-19 exposure histories of participants were recorded via questionnaires. Of the 98 asymptomatic healthcare workers tested, 19 (19.4%) tested positive by RT-qPCR and/or ELISA. Within this group, four (4.1%) were RT-qPCR positive, and four (4.1%) were PCR and IgG positive. Notably, an additional 11 (11.2%) individuals were IgG positive without a positive PCR. Two PCR positive individuals subsequently developed COVID-19 symptoms, while all others remained asymptomatic at 2-week follow-up. These results indicate that there is considerable asymptomatic infection with SARS-CoV-2 within the healthcare workforce, despite current mitigation policies. Furthermore, presuming that asymptomatic staff are not carrying SARS-CoV-2 is inconsistent with our results, and this could result in amplified transmission within healthcare settings. Consequently, aggressive testing regiments, such as testing frontline healthcare workers on a regular, multi-modal basis, may be required to prevent further spread within the workforce and to patients.
OUTPUT:
| Prevention;Diagnosis;Transmission | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
1,
0,
1,
0,
0
] |
LitCovid102 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Practical Tips for Ambulatory Care in COVID-19: Lessons Learned in a New York Health System. Although significant attention has been allocated to hospital management of COVID-19 patients during this pandemic, less discussed is the management of ambulatory patients. This has resulted in a challenge for ambulatory care providers in the management of COVID-19, particularly in areas with high disease prevalence. In this article, the authors share a pragmatic approach to ambulatory management of COVID-19 at Northwell Health, a large health system that employs approximately 300 primary care providers in the New York metro area. This includes guidance on various COVID-19 management topics: clinical assessment algorithms, guidance on patient tracking, and the importance of engaging in partnerships with other provider types. Sharing these experiences in the clinical management of COVID-19 may benefit other ambulatory providers in earlier stages of the COVID-19 pandemic.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid103 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Prevention program for the COVID-19 in a children's digestive endoscopy center. The pneumonia caused by the coronavirus disease-2019 (COVID-19) outbreak in Wuhan, China constitutes a public health emergency of international concern. The gastrointestinal symptoms of vomiting, diarrhea and abdominal pain and the detection of COVID-19 nucleic acid from fecal specimens in a small number of patients suggest the possibility of transmission via the gastrointestinal tract. People of all ages are vulnerable to this virus, including children. Digestive endoscopy is an invasive procedure during which children cannot wear masks; therefore, they have higher risks of exposure to COVID-19, and the digestive endoscopy center is a relatively high-risk area for COVID-19 infection. Based on these factors and in combination with related policies and regulations, a prevention and control program for the COVID-19 pneumonia in a children's digestive endoscopy center was established to prevent the COVID-19 nosocomial infection.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid104 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Challenges of intensive care and anesthesiology related to COVID-19 pandemic. Practical considerations Due to the coronavirus epidemic, healthcare systems face growing challenges all around the world nowadays. These challenges are the most critical in the field of intensive treatment and anesthesiology. One of the most important prerequisites of effective critical care treatment is preserving the involved healthcare workers from the infection, by providing them with detailed practical advices on the preventive measures and treatment strategies. The aim of the present review is to summarize the most important related knowledge available from previous experiences. Orv Hetil. 2020; 161(17): 652-659.
OUTPUT:
| Prevention;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
1,
0,
0
] |
LitCovid105 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Validation and performance comparison of three SARS-CoV-2 antibody assays. Serology testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly being used during the current pandemic of coronavirus disease 2019 (COVID-19), although its clinical and epidemiologic utilities are still debatable. Characterizing these assays provides scientific basis to best use them. The current study assessed one chemiluminescent assay (Abbott COVID-2 IgG) and two lateral flow assays (STANDARD Q [SQ] IgM/IgG Duo and Wondfo total antibody test) using 113 blood samples from 71 PCR-confirmed COVID-19 hospitalized patients, 119 samples with potential cross-reactions, and 1068 negative controls including 942 pre-pandemic samples. SARS-CoV-2 IgM antibodies became detectable 3-4 days post-symptom onset using SQ IgM test and IgG antibodies were first detected 5-6 days post-onset using SQ IgG. Abbott IgG and Wondfo Total were able to detect antibodies 7 to 8 days post-onset. After 14 days post-symptom onset, the SQ IgG, Abbott IgG and Wondfo Total tests were able to detect antibodies from 100% of the PCR-confirmed patients in this series; 87.5% sensitivity for SQ IgM. Overall agreement was 88.5% between SQ IgM/IgG and Wondfo Total and 94.6% between SQ IgG and Abbott IgG. No cross-reaction due to recent sera with three of the endemic coronaviruses was observed. Viral hepatitis and autoimmune samples were the main source of limited cross-reactions. The specificities were 100% for SQ IgG and Wondfo Total, 99.62% for Abbott IgG, and 98.87% for SQ IgM. These findings demonstrated high sensitivity and specificity of appropriately validated SARS-CoV-2 serologic assays with implications for clinical use and epidemiological seroprevalence studies.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid106 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Novel beta-Coronavirus (SARS-CoV-2): Current and future aspects of pharmacological treatments. The novel coronavirus outbreak has reported to be rapidly spreading across the countries and becomes a foremost community health alarm. At present, no vaccine or specific drug is on hand for the treatment of this infectious disease. This review investigates the drugs, which are being evaluated and found to be effective against nCOVID-19 infection. A thorough literature search was performedon the recently published research papers in between January 2020 to May 2020, through various databases like "Science Direct", "Google Scholar", "PubMed","Medline", "Web of Science", and "World Health Organization (WHO)". We reviewed and documented the information related with the current and future aspects for the management and cure of COVID-19. As of 21st July 2020 a total of 14,562,550 confirmed cases of coronavirus and 607,781 deaths have been reported world-wide. The main clinical feature of COVID-19 ranges from asymptomatic disease to mild lower respiratory tract illness to severe pneumonia, acute lung injury, acute respiratory distress syndrome (ARDS), multiple organ dysfunction, and death. The drugs at present used in COVID-19 patients and ongoing clinical trials focusing on drug repurposing of various therapeutic classes of drug e.g. antiviral, anti-inflammatory and/or immunomodulatory drugs along with adjuvant/supportive care. Many drugs on clinical trials shows effective results on preliminary scale and now used currently in patients. Adjuvant/supportive care therapy are used in patients to get the best results in order to minimize the short and long-term complications. However, further studies and clinical trials are needed on large scale of population to reach any firm conclusion in terms of its efficacy and safety.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid107 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Profiling of Initial Available SARS-CoV-2 Sequences from Iranian Related COVID-19 Patients. The etiologic agent SARS-CoV-2 has caused the outbreak of COVID-19 which is spread widely around the world. It is vital to uncover and investigate the full genome sequence of SARS-CoV-2 throughout the world to track changes in this virus. To this purpose, SARS-CoV-2 full genome sequence profiling of 20 patients in Iran and different countries that already had a travel history to Iran or contacts with Iranian cases were provided from the GISAID database. The bioinformatics analysis showed 44 different nucleotide mutations that caused 26 nonsynonymous mutations in protein sequences with regard to the reference full genome of the SARS-CoV-2 sequence (NC_045512.2). R207C, V378I, M2796I, L3606F, and A6407V in ORF1ab were common mutations in these sequences. Also, some of the detected mutations only were found in Iranian data in comparison with all the available sequences of SARS-CoV-2. The position of S protein mutations showed they were far from the binding site of this protein with angiotensin-converting enzyme-2 (ACE2) as the host cell receptor. These results can be helpful to design specific diagnostic tests, trace the SARS-CoV-2 sequence changes in Iran, and explore therapeutic drugs and vaccines.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid108 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Hydroxychloroquine and maintenance immunosuppression use in kidney transplant recipients: Analysis of linked US registry and claims data. Hydroxychloroquine (HCQ) is an antimalarial drug with immunomodulatory effects used to treat systemic lupus erythematosus (SLE) and scleroderma. The antiviral effects of HCQ have raised attention in the context of the COVID-19 pandemic, although safety is controversial. We examined linkages of national transplant registry data with pharmaceutical claims and Medicare billing claims to study HCQ use among Medicare-insured kidney transplant recipients with SLE or scleroderma (2008-2017; N = 1820). We compared three groups based on immunosuppression regimen 7 months-to-1 year post transplant: (a) tacrolimus (Tac) + mycophenolic acid (MPA) + prednisone (Pred) (referent group, 77.7%); (b) Tac + MPA + Pred + HCQ (16.5%); or (c) other immunosuppression + HCQ (5.7%). Compared to the referent group, recipients treated with other immunosuppression + HCQ had a 2-fold increased risk of abnormal ECG or QT prolongation (18.9% vs. 10.7%; aHR,1.12 1.963.42 , p = .02) and ventricular arrhythmias (15.2% vs. 11.4%; aHR,1.00 1.813.29 , p = .05) in the >1-to-3 years post-transplant. Tac + MPA + Pred + HCQ was associated with increased risk of ventricular arrhythmias (13.5% vs. 11.4%; aHR,1.02 1.542.31 , p = .04) and pancytopenia (35.9% vs. 31.4%; aHR,1.03 1.311.68 , p = .03) compared to triple immunosuppression without HCQ. However, HCQ-containing regimens were not associated with an increased risk of death or graft failure. HCQ may be used safely in selected kidney transplant recipients in addition to their maintenance immunosuppression, although attention to arrhythmias is warranted.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid109 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Progression of confirmed COVID-19 cases after the implementation of control measures. OBJECTIVE: To analyse the measures adopted by countries that have shown control over the transmission of coronavirus disease 2019 (COVID-19) and how each curve of accumulated cases behaved after the implementation of those measures. METHODS: The methodology adopted for this study comprises three phases: systemizing control measures adopted by different countries, identifying structural breaks in the growth of the number of cases for those countries, and analyzing Brazilian data in particular. RESULTS: We noted that China (excluding Hubei Province), Hubei Province, and South Korea have been effective in their deceleration of the growth rates of COVID-19 cases. The effectiveness of the measures taken by these countries could be seen after 1 to 2 weeks of their application. In Italy and Spain, control measures at the national level were taken at a late stage of the epidemic, which could have contributed to the high propagation of COVID-19. In Brazil, Rio de Janeiro and Sao Paulo adopted measures that could be effective in slowing the propagation of the virus. However, we only expect to see their effects on the growth of the curve in the coming days. CONCLUSION: Our results may help decisionmakers in countries in relatively early stages of the epidemic, especially Brazil, understand the importance of control measures in decelerating the growth curve of confirmed cases.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid110 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Occupational COVID-19 risk to dental staff working in a public dental unit in the outbreak epicenter. OBJECTIVE: The management of the COVID-19 outbreak occurred in Lombardy (Italy) implied that non-COVID-19 health care was remodeled, limiting adequate resources in non-hospital public dental healthcare settings. This situation offered the opportunity to investigate the occupational COVID-19 risk to dental staff in public non-hospital dental units. METHODS: An infection control protocol was designed for dental health care in the Territorial Health and Social Services Authority (ASST) "Melegnano and Martesana" (Milan). Since specific guidance from central authorities was lacking, information was gathered from international public health organizations. The probability to visit asymptomatic COVID-19-infected patients was estimated, and the occupational risk to dental staff was calculated. RESULTS: The probability to visit asymptomatic patients passed from 1.2% (95% confidence interval -95 CI, 0.6%-2.5%) in the first period (20 February-15 March 2020) to 11.1% (95 CI, 5.8%-23.6%) in the second period (16 March-30 April). Dentists and dental assistants did not develop COVID-19, while one nurse did, the nature of her occupational risk was unclear, as nurses provided prevalently non-dental health care. The probabilities of developing COVID-19 per worked hour per person excluding and including this uncertain situation were 0.0% (95 CI, 0.0%-3.2%) and 0.9% (95 CI, 0.1%-4.7%). CONCLUSION: Relatively simple infection control procedures were enough to control occupational COVID-19 risk during the outbreak.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid111 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: COVID-19: Current Developments and Further Opportunities in Drug Delivery and Therapeutics. SARS-CoV-2 has affected people from all age groups, races and ethnicities. Given that many infected individuals are asymptomatic, they transmit the disease to others unknowingly, which has resulted in the spread of infection at an alarming rate. This review aims to provide an overview of the pathophysiology, preventive measures to reduce the disease spread, therapies currently in use, an update on vaccine development and opportunities for vaccine delivery. The World Health Organization has advised several precautions including social distancing, hand washing and the use of PPE including gloves and face masks for minimizing the spread of SARS-CoV-2 infection. At present, several antiviral therapies previously approved for other infections are being repositioned to study their efficacy against SARS-CoV-2. In addition, some medicines (i.e., remdesivir, chloroquine, hydroxychloroquine) have received emergency use authorisation from the FDA. Plasma therapy has also been authorised for emergency use for the treatment of COVID-19 on a smaller scale. However, no vaccine has been approved so far against this virus. Nevertheless, several potential vaccine targets have been reported, and development of different types of vaccines including DNA, mRNA, viral vector, inactivated, subunit and vaccine-like particles is in process. It is concluded that a suitable candidate delivered through an advanced drug delivery approach would effectively boost the immune system against this coronavirus.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid112 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: [Period Prevalence of SARS-CoV-2 in an Unselected Sample of Pregnant Women in Jena, Thuringia]. INTRODUCTION: Following an exponential increase in SARS-CoV-2 infections, the city of Jena, Thuringia, was the first in Germany to introduce mandatory mouth and nose coverings. An estimation of the SARS-CoV-2 period prevalence was achieved by screening an unselected cohort of pregnant women. Of interest was the number of unreported cases. METHODS: Upon admission to hospital, patients were screened for SARS-CoV-2 by a specific real-time PCR and antibodies determined by a specific SARS-CoV-2 IgG in serum by ELISA. The SARS-CoV-2 period prevalence was estimated using the Clopper-Pearson exact method, the group comparison with Fischer's exact test. RESULTS: From 6 April to 13 May 2020, 234 pregnant women were admitted to the Department of Obstetrics. A total of 225 (96.2%) SARS-CoV-2 PCRs were carried out and all remained negative. Specific IgG antibodies were detected in one (0.6%) of 180 (76.9%) antibody tests performed. The interval estimate of the period prevalence thus results in a 95% confidence interval between 0-1.7%. For 96 households with children, the period prevalence is 0-3.8%, which does not differ from the 0-4.8% for 76 households without children (p=1.00). DISCUSSION: This is the first report on the SARS-CoV-2 period prevalence of an unselected sample of pregnant women in Germany. Antibody testing showed no evidence of the feared high number of unreported asymptomatic SARS-CoV-2 infections. The seroconversion rate was below 1% (0.6%).
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid113 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: From SARS-CoV to SARS-CoV-2: safety and broad-spectrum are important for coronavirus vaccine development. The global pandemic of COVID-19 caused by SARS-CoV-2 (also known as 2019-nCoV and HCoV-19) has posed serious threats to public health and economic stability worldwide, thus calling for development of vaccines against SARS-CoV-2 and other emerging and reemerging coronaviruses. Since SARS-CoV-2 and SARS-CoV have high similarity of their genomic sequences and share the same cellular receptor (ACE2), it is essential to learn the lessons and experiences from the development of SARS-CoV vaccines for the development of SARS-CoV-2 vaccines. In this review, we summarized the current knowledge on the advantages and disadvantages of the SARS-CoV vaccine candidates and prospected the strategies for the development of safe, effective and broad-spectrum coronavirus vaccines for prevention of infection by currently circulating SARS-CoV-2 and other emerging and reemerging coronaviruses that may cause future epidemics or pandemics.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid114 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Telehealth in response to the COVID-19 pandemic: Implications for rural health disparities. Telehealth programs have long held promise for addressing rural health disparities perpetuated by inadequate healthcare access. The COVID-19 (coronavirus disease 2019) pandemic and accompanying social distancing measures have hastened the implementation of telehealth programs in hospital systems around the globe. Here, we provide specific examples of telehealth efforts that have been implemented in a large rural healthcare system in response to the pandemic, and further describe how the massive shift to telehealth and reliance on virtual connections in these times of social isolation may impact rural health disparities for those without access to necessary broadband to deploy digital technologies. Finally, we provide recommendations for researchers and policymakers to ensure that telehealth initiatives do not amplify existing health disparities experienced by those living in rural communities.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid115 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Early impact of COVID-19 social distancing measures on reported sexual behaviour of HIV pre-exposure prophylaxis users in Wales. OBJECTIVES: To describe the early impact of COVID-19 and associated control measures on the sexual behaviour of pre-exposure prophylaxis (PrEP) users in Wales. METHODS: Data were obtained from an ecological momentary assessment study of PrEP use and sexual behaviour. Participants were individuals accessing PrEP through the National Health Service (NHS) sexual health clinics across four health boards in Wales. Weekly data documenting condomless sex in the preceding week were analysed between 03/02/2020 and 10/05/2020. The introduction of social distancing measures and changes to sexual health clinics in Wales occurred on the week starting 16/03/2020. Two-level logistic regression models were fitted to condomless sex (yes/no) over time, included an indicator for the week starting 16/03/2020, and were extended to explore differential associations by relationship status and sexual health clinic. RESULTS: Data were available from 56 participants and included 697 person-weeks (89% of the maximum number that could have been obtained). On average, 42% of participants reported condomless sex in the period prior to the introduction of social distancing measures and 20% reported condomless sex after (OR=0.16, 95% CI 0.07 to 0.37, p<0.001). There was some evidence to suggest that this association was moderated by relationship status (OR for single participants=0.09, 95% CI 0.06 to 0.23; OR for not single participants=0.46, 95% CI 0.16 to 1.25). CONCLUSIONS: The introduction of social distancing measures and changes to PrEP services across Wales was associated with a marked reduction in reported instances of condomless sexual intercourse among respondents, with a larger reduction in those who were single compared with those who were not. The long-term impact of COVID-19 and associated control measures on this population's physical and mental health and well-being requires close examination.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid116 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Change of dermatological practice after the COVID-19 outbreak resolves. AIM: Dermatological care has already been deeply impacted by the coronavirus disease-2019 (COVID-19) epidemic. The consequences may continue long after the epidemic resolves. In this study, we aimed to evaluate the change of dermatological practice since the COVID-19 outbreak is almost controlled in mainland China. MATERIAL AND METHODS: Patients requesting a dermatology outpatient visit from January to May in 2019 and 2020 were retrospectively investigated. RESULTS: The number of patients decreased significantly shortly after the COVID-19 outbreak, and it started to increase after the spread of coronavirus was gradually controlled at the end of February in China. The three most common diseases were atopic dermatitis (11.0%), acne (10.2%), and warts (7.2%) in 2019, while acne (8.9%), warts (5.8%), and acute urticaria (5.6%) in 2020. The most statistically significant increased reasons for requesting an outpatient visit from March to May in 2020 was pet-related dermatophytoses, followed by cosmetic consultation and irritated contact dermatitis, an increase of 88.2%, 84.7%, and 58.8%, respectively, over the same period of 2019. CONCLUSION: Understanding the trends and impacts of dermatologic diseases on patients and health systems during this epidemic will allow for better preparation of dermatologists in the future.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid117 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Coagulation disorders in coronavirus infected patients: COVID-19, SARS-CoV-1, MERS-CoV and lessons from the past. Coronavirus disease 2019 (COVID-19) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus strain disease, has recently emerged in China and rapidly spread worldwide. This novel strain is highly transmittable and severe disease has been reported in up to 16% of hospitalized cases. More than 600,000 cases have been confirmed and the number of deaths is constantly increasing. COVID-19 hospitalized patients, especially those suffering from severe respiratory or systemic manifestations, fall under the spectrum of the acutely ill medical population, which is at increased venous thromboembolism risk. Thrombotic complications seem to emerge as an important issue in patients infected with COVID-19. Preliminary reports on COVID-19 patients' clinical and laboratory findings include thrombocytopenia, elevated D-dimer, prolonged prothrombin time, and disseminated intravascular coagulation. As the pandemic is spreading and the whole picture is yet unknown, we highlight the importance of coagulation disorders in COVID-19 infected patients and review relevant data of previous coronavirus epidemics caused by the severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and the Middle East Respiratory Syndrome coronavirus (MERS-CoV).
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid118 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Increased expression of CD8 marker on T-cells in COVID-19 patients. BACKGROUND: Cell-mediated immunity including T-cells (T helper and cytotoxic) plays an essential role in efficient antiviral responses against coronavirus disease-2019 (COVID-19). Therefore, in this study, we evaluated the ratio and expression of CD4 and CD8 markers in COVID-19 patients to clarify the immune characterizations of CD4 and CD8 T-cells in COVID-19 patients. METHODS: Peripheral blood samples of 25 COVID-19 patients and 25 normal individuals with similar age and sex as the control group were collected. White blood cells, platelets, and lymphocytes were counted and CD4 and CD8 T lymphocytes were evaluated by flow cytometry. RESULTS: The number of white blood cells, lymphocytes, and platelets were reduced significantly in COVID-19 patients (P < 0.05). The difference in CD4:CD8 ratio, CD4 T-cell frequency, CD8 T-cell frequency, and CD4 mean fluorescence intensity (MFI) was not significant between COVID-19 patients and healthy individuals (P > 0.05); however, the CD8 MFI increased significantly in COVID-19 infected patients (P < 0.05). CONCLUSION: Although, there is no significant difference in the ratio of CD4 to CD8 between two groups, the expression level of CD8 in COVID-19 patients was significantly higher than the normal individuals. This result suggested that the cellular immune responses triggered by COVID-19 infection were developed through overexpression of CD8 and hyperactivation of cytotoxic T lymphocytes.
OUTPUT:
| Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
0,
0,
0,
0
] |
LitCovid119 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Physical Activity, Screen Time, and Emotional Well-Being during the 2019 Novel Coronavirus Outbreak in China. We aimed to evaluate the effects of the COVID-19 lock down on lifestyle in China during the initial stage of the pandemic. A questionnaire was distributed to Chinese adults living in 31 provinces of China via the internet using a snowball sampling strategy. Information on 7-day physical activity recall, screen time, and emotional state were collected between January 24 and February 2, 2020. ANOVA, chi(2) test, and Spearman's correlation coefficients were used for statistical analysis. 12,107 participants aged 18-80 years were included. During the initial phase of the COVID-19 outbreak, nearly 60% of Chinese adults had inadequate physical activity (95% CI 56.6%-58.3%), which was more than twice the global prevalence (27.5%, 25.0%-32.2%). Their mean screen time was more than 4 hours per day while staying at home (261.3 +/- 189.8 min per day), and the longest screen time was found in young adults (305.6 +/- 217.5 min per day). We found a positive and significant correlation between provincial proportions of confirmed COVID-19 cases and negative affect scores (r = 0.501, p = 0.004). Individuals with vigorous physical activity appeared to have a better emotional state and less screen time than those with light physical activity. During this nationwide lockdown, more than half of Chinese adults temporarily adopted a sedentary lifestyle with insufficient physical activity, more screen time, and poor emotional state, which may carry considerable health risks. Promotion of home-based self-exercise can potentially help improve health and wellness.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid120 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: On the Alert for Cytokine Storm: Immunopathology in COVID-19. Poor outcomes in COVID-19 correlate with clinical and laboratory features of cytokine storm syndrome. Broad screening for cytokine storm and early, targeted antiinflammatory therapy may prevent immunopathology and could help conserve limited health care resources. While studies are ongoing, extrapolating from clinical experience in cytokine storm syndromes may benefit the multidisciplinary teams caring for patients with severe COVID-19.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid121 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: The impact of COVID-19 pandemic on orthopaedic resident education: a nationwide survey study in South Korea. PURPOSE: There have not been well-designed survey studies investigating the impact of the coronavirus disease 2019 (COVID-19) pandemic on orthopaedic resident education. METHODS: A 58-question, web-based survey was administered to orthopaedic residents in South Korea. A total of 229 orthopaedic residents from 43 hospitals completed the survey questionnaire. RESULTS: The average working time of 72.7 hours/week before the pandemic was decreased to 65.6 hours/week during the pandemic (p < 0.001). The time working in the operating room was significantly decreased during the pandemic, but not in the emergency centre and outpatient clinic. The education times for lecture and clinical case discussion were decreased during the pandemic (both, p < 0.001), respectively. While the use of traditional teaching methods was decreased, the use of online-based teaching methods was increased (p < 0.001). However, satisfaction level with online-based teaching methods was significantly lower compared with that of traditional teaching methods. The average working time exposed to the patients with COVID-19 was 9.7 hours/week. About 47.6% of orthopaedic residents experienced isolation or quarantine. The average score for quality of life, which was 68.9 out of 100 scores before the pandemic, decreased to 61.7 during the pandemic (p < 0.001). The most stressful factor for orthopaedic residents during the pandemic was family/relative health, followed by their own health and residency program. CONCLUSION: The COVID-19 pandemic had a significant impact on orthopaedic resident education in South Korea. Therefore, flexible and sustainable strategies are necessary to prepare for the future as well as the current pandemic situation.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid122 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: COVID-19 and Substance Use Disorders: Recommendations to a Comprehensive Healthcare Response. An International Society of Addiction Medicine Practice and Policy Interest Group Position Paper. Coronavirus Disease 2019 (COVID-19) is escalating all over the world and has higher morbidities and mortalities in certain vulnerable populations. People Who Use Drugs (PWUD) are a marginalized and stigmatized group with weaker immunity responses, vulnerability to stress, poor health conditions, high-risk behaviors, and lower access to health care services. These conditions put them at a higher risk of COVID-19 infection and its complications. In this paper, an international group of experts on addiction medicine, infectious diseases, and disaster psychiatry explore the possible raised concerns in this issue and provide recommendations to manage the comorbidity of COVID-19 and Substance Use Disorder (SUD).
OUTPUT:
| Prevention;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
1,
0,
0
] |
LitCovid123 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Metabolic Syndrome and Viral Pathogenesis: Lessons from Influenza and Coronaviruses. Metabolic syndrome increases the risk of severe disease due to viral infection. Yet few studies have assessed the pathogenesis of respiratory viruses in high-risk populations. Here, we summarize how metabolic dysregulation impairs immune responses, and we define the role of metabolism during influenza virus and coronavirus infections. We also discuss the use of various in vitro, in vivo, and ex vivo models to elucidate the contributions of host factors to viral susceptibility, immunity, and disease severity.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid124 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Commercial airline protocol during COVID-19 pandemic: An experience of Thai Airways International. INTRODUCTION: Coronavirus disease 2019 (COVID-19) pandemic has affected the aviation industry. Existing protocols have relied on scientifically questionable evidence and might not lead to the optimal balance between public health safety and airlines' financial viability. OBJECTIVE: To explore the implementation feasibility of Thai Airways International protocol from the perspectives of passengers and aircrews. DESIGN: An online questionnaire survey of passengers and an in-depth interview with aircrews. SETTING: Two randomly selected repatriation flights operated by Thai Airways International using Boeing 777 aircraft (TG476 from Sydney and TG492 from Auckland to Bangkok). PARTICIPANTS: 377 Thai passengers and 35 aircrews. RESULTS: The mean age of passengers was 28.14 (95%CI 26.72 to 29.55) years old; 57.03% were female. TG492 passengers were mostly students and significantly younger than that of TG476 (p<0.0001) with comparable flying experience (p = 0.1192). The average body temperature was 36.52 (95%CI 36.48 to 36.55) degrees Celsius. Passengers estimated average physical distances of 1.59 (95%CI 1.48 to 1.70), 1.41 (95%CI 1.29 to 1.53), and 1.26 (95%CI 1.12 to 1.41) meters at check-in, boarding, and in-flight, respectively. Passengers were checked for body temperature during the flight 1.97 (95%CI 1.77 to 2.18) times on average which is significantly more frequent in longer than shorter flight (p<0.0001). Passengers moved around or went to the toilet during the flight 2.00 (95%CI 1.63 to 2.37) and 2.08 (95%CI 1.73 to 2.43) times which are significantly more frequent in longer than shorter flight (p = 0.0186 and 0.0049, respectively). The aircrews were satisfied with the protocol and provided several practical suggestions. CONCLUSION: The protocol was well received by the passengers and aircrews of the repatriation flights with some suggestions for improvement.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid125 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: COVID-19 - 6 million cases worldwide and an overview of the diagnosis in Brazil: a tragedy to be announced. On 1 June 2020, 6 million cases of COVID-19 were recorded with a total of 374,927 deaths worldwide. Brazil, at that point, presented a total of 514,992 cases and 29,341 deaths caused by the COVID-19 disease. At that moment, Brazil appeared in the second position regarding number of cases, fourth in number of deaths, second in number of recovered patients (N=206,555), second in number of follow-up cases (N=279,096), third in number of active and serious cases (N=8,318), 39(th) in number of cases per million inhabitants (N=2,424), and 125(th) in number of SARS-CoV-2 real-time polymerase chain reaction (RT-PCR) exams per million inhabitants (N=4,378). To beat the pandemic, Brazil needs to optimize the COVID-19 diagnosis through the SARS-CoV-2 identification using RT-PCR tests and adjust its policies to save lives. Brazil is in a crucial moment to minimize the impact of the illness on society by reducing the number of new cases and thus, preventing deaths, mainly of the risk group populations. However, as widely announced, in Brazil the diagnosis using RT-PCR is still scarce and part of the material collected from COVID-19 patients was disposed of and many patients were not tested, regardless of the seriousness of the symptoms, due to errors of medical data records, improper conservation of the samples after collection and/or during transport, which compromised the quality of the material to be tested. Moreover, the federal government has supported the end of the quarantine, while the number of deaths has grown in thousands every day and the cases have been expanding to the interior of the country.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid126 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Medical mask versus cotton mask for preventing respiratory droplet transmission in micro environments. The objective of this study was to investigate whether cotton mask worn by respiratory infection person could suppress respiratory droplet levels compared to medical mask. We recruited adult volunteers with confirmed influenza and suspected cases of coronavirus disease 2019 (COVID-19) to wear medical masks and self-designed triple-layer cotton masks in a regular bedroom and a car with air conditioning. Four 1-hour repeated measurements (two measurements for bedroom the others for car) of particles with a size range of 20-1000 nm measured by number concentrations (NC0.02-1), temperature and relatively humidity, and cough/sneeze counts per hour were conducted for each volunteer. The paired t-tests were used for within-group comparisons in a bedroom and in a car. The results showed that there was no significant difference in NC0.02-1 or cough/sneeze counts between volunteers with medical masks and cotton masks in a bedroom or a car. We concluded that the cotton mask could be a potential substitute for medical mask for respiratory infection person in microenvironment with air conditioning. Healthy people may daily use cotton mask in the community since cotton mask is washable and reusable.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid127 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Coronavirus Disease 2019 Catheterization Laboratory Survey. Background The coronavirus disease 2019 pandemic is expected to affect operations and lifestyles of interventional cardiologists around the world in unprecedented ways. Timely gathering of information on this topic can provide valuable insight and improve the handling of the ongoing and future pandemic outbreaks. Methods and Results A survey instrument developed by the authors was disseminated via e-mail, text messaging, WhatsApp, and social media to interventional cardiologists between April 6, 2020, and April 11, 2020. A total of 509 responses were collected from 18 countries, mainly from the United States (51%) and Italy (36%). Operators reported significant decline in coronary, structural heart, and endovascular procedure volumes. Personal protective equipment was available to 95% of respondents; however FIT-tested N95 or equivalent masks were available to only 70%, and 74% indicated absence of coronavirus disease 2019 pretesting. Most (83%) operators expressed concern when asked to perform cardiac catheterization on a suspected or confirmed coronavirus disease 2019 patient, primarily because of fear of viral transmission (88%). Although the survey demonstrated significant compliance with social distancing, high use of telemedicine (69%), and online education platforms (80%), there was concern over impending financial loss. Conclusions Our survey indicates significant reduction in invasive procedure volumes and concern for viral transmission. There is near universal adoption of personal protective equipment; however, coronavirus disease 2019 pretesting and access to FIT-tested N95 masks is suboptimal. Although there is concern over impending financial loss, substantial engagement in telemedicine and online education is reported.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid128 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Novel Coronavirus Polymerase and Nucleotidyl-Transferase Structures: Potential to Target New Outbreaks. The pandemic outbreak of a new coronavirus (CoV), SARS-CoV-2, has captured the world's attention, demonstrating that CoVs represent a continuous global threat. As this is a highly contagious virus, it is imperative to understand RNA-dependent-RNA-polymerase (RdRp), the key component in virus replication. Although the SARS-CoV-2 genome shares 80% sequence identity with severe acute respiratory syndrome SARS-CoV, their RdRps and nucleotidyl-transferases (NiRAN) share 98.1% and 93.2% identity, respectively. Sequence alignment of six coronaviruses demonstrated higher identity among their RdRps (60.9%-98.1%) and lower identity among their Spike proteins (27%-77%). Thus, a 3D structural model of RdRp, NiRAN, non-structural protein 7 (nsp7), and nsp8 of SARS-CoV-2 was generated by modeling starting from the SARS counterpart structures. Furthermore, we demonstrate the binding poses of three viral RdRp inhibitors (Galidesivir, Favipiravir, and Penciclovir), which were recently reported to have clinical significance for SARS-CoV-2. The network of interactions established by these drug molecules affirms their efficacy to inhibit viral RNA replication and provides an insight into their structure-based rational optimization for SARS-CoV-2 inhibition.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid129 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: [COVID-19 and the Hospital Neurologist: How should we confront the COVID pandemic?] Ninety-six patients were admitted to our hospital during the first wave of the 2020 COVID pandemic. Our hospital, a core hospital in Kobe, was in confusion at the beginning of the pandemic. The following three factors were considered important for preventing the collapse of hospitals during the pandemic based on our experiences: avoidance of contact, prompt and accurate communication, and role-sharing among community medical institutions. Of the 96 patients, 36 had severe cases with several neurological problems: 18 had consciousness disorders, 19 had generalized weakness, 7 had polyneuropathy, and 2 had severe limb weakness. There are several unsolved pathological problems, and neurologists should play important roles in the treatment of patients with COVID.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid130 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Comparative Antiviral Efficacy of Viral Protease Inhibitors against the Novel SARS-CoV-2 In Vitro. The recent outbreak of novel coronavirus pneumonia (COVID-19) caused by a new coronavirus has posed a great threat to public health. Identifying safe and effective antivirals is of urgent demand to cure the huge number of patients. Virus-encoded proteases are considered potential drug targets. The human immunodeficiency virus protease inhibitors (lopinavir/ritonavir) has been recommended in the global Solidarity Trial in March launched by World Health Organization. However, there is currently no experimental evidence to support or against its clinical use. We evaluated the antiviral efficacy of lopinavir/ritonavir along with other two viral protease inhibitors in vitro, and discussed the possible inhibitory mechanism in silico. The in vitro to in vivo extrapolation was carried out to assess whether lopinavir/ritonavir could be effective in clinical. Among the four tested compounds, lopinavir showed the best inhibitory effect against the novel coronavirus infection. However, further in vitro to in vivo extrapolation of pharmacokinetics suggested that lopinavir/ritonavir could not reach effective concentration under standard dosing regimen [marketed as Kaletra((R)), contained lopinavir/ritonavir (200 mg/50 mg) tablets, recommended dosage is 400 mg/10 mg (2 tablets) twice daily]. This research concluded that lopinavir/ritonavir should be stopped for clinical use due to the huge gap between in vitro IC50 and free plasma concentration. Nevertheless, the structure-activity relationship analysis of the four inhibitors provided further information for de novel design of future viral protease inhibitors of SARS-CoV-2.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid131 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Rational Use of Tocilizumab in the Treatment of Novel Coronavirus Pneumonia. Since December 2019, a novel coronavirus pneumonia (COVID-19) has broken out in Wuhan, China and spread rapidly. Recent studies have found that 15.7% of patients develop severe pneumonia, and cytokine storm is an important factor leading to rapid disease progression. Currently, there are no specific drugs for COVID-19 and the cytokine storm it causes. IL-6 is one of the key cytokines involved in infection-induced cytokine storm. Tocilizumab, which is the IL-6 receptor antagonist, has been approved by the US FDA for the treatment of cytokine release syndrome (CRS), is expected to treat cytokine storm caused by COVID-19 and is now in clinical trials. In this paper, we will elaborate the role of cytokine storm in COVID-19, the mechanism of tocilizumab on cytokine storm and the key points of pharmaceutical care based on the actual clinical application for COVID-19 in our hospital, the latest research reports, clinical trial progress of tocilizumab, drug instruction from the US FDA, and "Diagnosis and Treatment Plan of Novel Coronavirus Pneumonia (seventh trial edition)" in China, so as to provide reference for the treatment of COVID-19.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid132 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Extracorporeal Membrane Oxygenation as Treatment of Severe COVID-19 Infection: A Case Report. Novel coronavirus 2019 (COVID-19) is a severe respiratory infection leading to acute respiratory distress syndrome (ARDS) accounting for thousands of cases and deaths across the world. Several alternatives in treatment options have been assessed and used in this patient population. However, when mechanical ventilation and prone positioning are unsuccessful, venovenous extracorporeal membrane oxygenation (VV-ECMO) may be used. We present a case of a 41-year-old female, with no significant medical history and no recent history of exposure to sick contacts, presented to the emergency department (ED) with fever, severe shortness of breath, and flu-like symptoms with a positive COVID-19 test. Ultimately, she worsened on mechanical ventilation and prone positioning and required VV-ECMO. The use of VV-ECMO in COVID-19 infected patients is still controversial. While some studies have shown a high mortality rate despite aggressive treatment, such as in our case, the lack of large sample size studies and treatment alternatives places healthcare providers against a wall without options in patients with severe refractory ARDS due to COVID-19.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid133 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Massive cutback in orthopaedic healthcare services due to the COVID-19 pandemic. PURPOSE: Due to the lack of evidence, it was the aim of the study to investigate current possible cutbacks in orthopaedic healthcare due to the coronavirus disease 2019 pandemic (COVID-19). METHODS: An online survey was performed of orthopaedic surgeons in the German-speaking Arthroscopy Society (Gesellschaft fur Arthroskopie und Gelenkchirurgie, AGA). The survey consisted of 20 questions concerning four topics: four questions addressed the origin and surgical experience of the participant, 12 questions dealt with potential cutbacks in orthopaedic healthcare and 4 questions addressed the influence of the pandemic on the particular surgeon. RESULTS: Of 4234 contacted orthopaedic surgeons, 1399 responded. Regarding arthroscopic procedures between 10 and 30% of the participants stated that these were still being performed-with actual percentages depending on the specific joint and procedure. Only 6.2% of the participants stated that elective total joint arthroplasty was still being performed at their centre. In addition, physical rehabilitation and surgeons' postoperative follow-ups were severely affected. CONCLUSION: Orthopaedic healthcare services in Austria, Germany, and Switzerland are suffering a drastic cutback due to COVID-19. A drastic reduction in arthroscopic procedures like rotator cuff repair and cruciate ligament reconstruction and an almost total shutdown of elective total joint arthroplasty were reported. Long-term consequences cannot be predicted yet. The described disruption in orthopaedic healthcare services has to be viewed as historic. LEVEL OF EVIDENCE: V.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid134 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Role of a Pediatric Cardiologist in the COVID-19 Pandemic. Coronavirus disease 2019 (COVID-19) has affected patients across all age groups, with a wide range of illness severity from asymptomatic carriers to severe multi-organ dysfunction and death. Although early reports have shown that younger age groups experience less severe disease than older adults, our understanding of this phenomenon is in continuous evolution. Recently, a severe multisystem inflammatory syndrome in children (MIS-C), with active or recent COVID-19 infection, has been increasingly reported. Children with MIS-C may demonstrate signs and symptoms of Kawasaki disease, but also have some distinct differences. These children have more frequent and severe gastrointestinal symptoms and are more likely to present with a shock-like presentation. Moreover, they often present with cardiovascular involvement including myocardial dysfunction, valvulitis, and coronary artery dilation or aneurysms. Here, we present a review of the literature and summary of our current understanding of cardiovascular involvement in children with COVID-19 or MIS-C and identifying the role of a pediatric cardiologist in caring for these patients.
OUTPUT:
| Diagnosis;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid135 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Anesthesia and COVID-19: What We Should Know and What We Should Do. Coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2), was first reported in Wuhan, Hubei, China, and has spread to more than 200 other countries around the world. COVID-19 is a highly contagious disease with continuous human-to-human transmission. The origin of the virus is unknown. Airway manipulations and intubations, which are common during anesthesia procedures may increasingly expose anesthesia providers and intensive care unit team members to SARS-CoV-2. Through a comprehensive review of existing studies on COVID-19, this article presents the epidemiological and clinical characteristics of COVID-19, reviews current medical management, and suggests ways to improve the safety of anesthetic procedures. Owing to the highly contagious nature of the virus and the lack of therapeutic drugs or vaccines, precautions should be taken to prevent medical staff from COVID-19.
OUTPUT:
| Diagnosis;Prevention;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
1,
0,
0
] |
LitCovid136 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: The association between cardiac injury and outcomes in hospitalized patients with COVID-19. In this study, we aimed to assess the association between development of cardiac injury and short-term mortality as well as poor in-hospital outcomes in hospitalized patients with COVID-19. In this prospective, single-center study, we enrolled hospitalized patients with laboratory-confirmed COVID-19 and highly suspicious patients with compatible chest computed tomography features. Cardiac injury was defined as a rise of serum high sensitivity cardiac Troponin-I level above 99th percentile (men: > 26 ng/mL, women: > 11 ng/mL). A total of 386 hospitalized patients with COVID-19 were included. Cardiac injury was present among 115 (29.8%) of the study population. The development of cardiac injury was significantly associated with a higher in-hospital mortality rate compared to those with normal troponin levels (40.9% vs 11.1%, p value < 0.001). It was shown that patients with cardiac injury had a significantly lower survival rate after a median follow-up of 18 days from symptom onset (p log-rank < 0.001). It was further demonstrated in the multivariable analysis that cardiac injury could possibly increase the risk of short-term mortality in hospitalized patients with COVID-19 (HR = 1.811, p-value = 0.023). Additionally, preexisting cardiovascular disease, malignancy, blood oxygen saturation < 90%, leukocytosis, and lymphopenia at presentation were independently associated with a greater risk of developing cardiac injury. Development of cardiac injury in hospitalized patients with COVID-19 was significantly associated with higher rates of in-hospital mortality and poor in-hospital outcomes. Additionally, it was shown that development of cardiac injury was associated with a lower short-term survival rate compared to patients without myocardial damage and could independently increase the risk of short-term mortality by nearly two-fold.
OUTPUT:
| Treatment;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid137 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Inference from longitudinal laboratory tests characterizes temporal evolution of COVID-19-associated coagulopathy (CAC). Temporal inference from laboratory testing results and triangulation with clinical outcomes extracted from unstructured electronic health record (EHR) provider notes is integral to advancing precision medicine. Here, we studied 246 SARS-CoV-2 PCR-positive (COVIDpos) patients and propensity-matched 2460 SARS-CoV-2 PCR-negative (COVIDneg) patients subjected to around 700,000 lab tests cumulatively across 194 assays. Compared to COVIDneg patients at the time of diagnostic testing, COVIDpos patients tended to have higher plasma fibrinogen levels and lower platelet counts. However, as the infection evolves, COVIDpos patients distinctively show declining fibrinogen, increasing platelet counts, and lower white blood cell counts. Augmented curation of EHRs suggests that only a minority of COVIDpos patients develop thromboembolism, and rarely, disseminated intravascular coagulopathy (DIC), with patients generally not displaying platelet reductions typical of consumptive coagulopathies. These temporal trends provide fine-grained resolution into COVID-19 associated coagulopathy (CAC) and set the stage for personalizing thromboprophylaxis.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid138 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: [Predictive models of the COVID-19 epidemic in Spain with Gompertz curves]. During the international health crisis caused by the COVID-19 pandemic, it is necessary not only to know the data on infections, deaths and the occupation of hospital beds, but also to make predictions that help health authorities in the management of the crisis. The present work aims to describe the methodology used to develop predictive models of infections and deaths for the COVID-19 epidemic in Spain, based on Gompertz curves. The methodology is applied to the country as a whole and to each of its Autonomous Communities. Based on the official data available on the date of this work, and through the models described, we estimate a total of around 240.000 infected and 25.000 deaths at the end of the epidemic. At a national level, we forecast the end of the epidemic between June and July 2020.
OUTPUT:
| Epidemic Forecasting | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
0,
1
] |
LitCovid139 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Lower prevalence of antibodies neutralizing SARS-CoV-2 in group O French blood donors. We investigated the distribution of antibodies neutralizing SARS-CoV-2 according to age, sex or blood group in French blood donors. In 464 samples collected before the emergence of SARS-CoV-2 (2017 and 2018), our virus neutralization assay had a 100% specificity. It was used to test 998 samples collected from blood donors during the last week of March or the first week of April 2020. As expected at this stage of the outbreak, the prevalence was low (2.7%) and, importantly, criteria for blood donation imply that the vast majority of seropositives had asymptomatic or pauci-symptomatic SARS-CoV-2 infections. Seroprevalence values did not differ significantly among age groups (but were slightly higher in donors <30yo and >/=60yo), and between males and females (2.82% vs 2.69%), unlike what has been observed regarding hospitalizations admission to ICU and death rates in France. By contrast, we observed that the proportion of seropositives was significantly lower in group O donors (1.32% vs 3.86% in other donors, p = 0.014). We conclude that virus infection seems to occur with a similar incidence in men and women among French blood donors, but that blood group O persons are less at risk of being infected and not only of suffering from severe clinical presentations, as previously suggested.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid140 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Do checkpoint inhibitors compromise the cancer patients' immunity and increase the vulnerability to COVID-19 infection? The severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) has been declared a pandemic by the WHO that claimed the lives of thousands of people within a few months. Cancer patients represent a vulnerable population due to the acquired immunodeficiency associated with anti-cancer therapy. Immune checkpoint inhibitors have largely impacted the prognosis of a multitude of malignancies with significant improvement in survival outcomes and a different, tolerable toxicity profile. In this paper, we assess the safety of ICI administration in cancer patients during the coronavirus pandemic in order to guide the usage of these highly efficacious agents.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid141 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Prominent changes in blood coagulation of patients with SARS-CoV-2 infection. Background As the number of patients increases, there is a growing understanding of the form of pneumonia sustained by the 2019 novel coronavirus (SARS-CoV-2), which has caused an outbreak in China. Up to now, clinical features and treatment of patients infected with SARS-CoV-2 have been reported in detail. However, the relationship between SARS-CoV-2 and coagulation has been scarcely addressed. Our aim is to investigate the blood coagulation function of patients with SARS-CoV-2 infection. Methods In our study, 94 patients with confirmed SARS-CoV-2 infection were admitted in Renmin Hospital of Wuhan University. We prospectively collect blood coagulation data in these patients and in 40 healthy controls during the same period. Results Antithrombin values in patients were lower than that in the control group (p < 0.001). The values of D-dimer, fibrin/fibrinogen degradation products (FDP), and fibrinogen (FIB) in all SARS-CoV-2 cases were substantially higher than those in healthy controls. Moreover, D-dimer and FDP values in patients with severe SARS-CoV-2 infection were higher than those in patients with milder forms. Compared with healthy controls, prothrombin time activity (PT-act) was lower in SARS-CoV-2 patients. Thrombin time in critical SARS-CoV-2 patients was also shorter than that in controls. Conclusions The coagulation function in patients with SARS-CoV-2 is significantly deranged compared with healthy people, but monitoring D-dimer and FDP values may be helpful for the early identification of severe cases.
OUTPUT:
| Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
0,
0,
0,
0
] |
LitCovid142 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Integrated control of COVID-19 in resource-poor countries. Low- and middle-income countries (LMICs) face many challenges in controlling COVID-19. Healthcare resources are limited and so are ICU beds. RT-PCR testing is conducted on a limited scale and treatment options are few. There is no vaccine. Therefore, what low-cost solutions remain for the prevention, diagnosis, and treatment of SARS-CoV-2? How should these essential health services be delivered in order to reach the most vulnerable in our societies? In this editorial we discuss several important strategies for controlling COVID-19 including: vaccination, molecular and serological diagnostics, hygiene and WaSH interventions, and low-cost therapeutics. We also discuss the delivery of such services in order to reach the most in need. The proposed integrated control strategy requires immediate action and political will in order to reduce the widening health inequalities caused by the pandemic.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid143 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: [Management of the thrombotic risk associated with COVID-19: what is the role of the hemostasis laboratory?] COVID-19 is associated with disturbances of hemostasis in the laboratory and an increased thrombotic risk. Routine laboratory tests - activated partial thromboplastin time (aPTT), prothrombin time, Clauss fibrinogen and D-dimers levels measurement - are used for the evaluation of the thrombotic risk and the monitoring of hemostasis, but are subject to several drawbacks that may affect the reliability and clinical relevance of the delivered results. Another challenge for the hemostasis laboratory is the monitoring of heparin treatment. For instance, the issue of the monitoring of unfractionated heparin remains debated, the more so when there is a tremendous inflammatory response. This brief review considers the role of laboratory tests of hemostasis in the management of COVID-19 and discusses their main limitations to be kept in mind.
OUTPUT:
| Diagnosis;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid144 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Clinical management of lung cancer patients during the outbreak of COVID-19 epidemic. The rapid growth of 2019 novel coronavirus (COVID-19) outbreak in Wuhan, China, at the early December 2019. COVID-19 spread all over the word just a few months. The outbreak of COVID-19 infection poses major threat to international health and economy. World Health Organization (WHO) announced that the new coronavirus was an international public health emergency on January 30, 2020. However, with the spread of COVID-19, the routine medical care of lung cancer patients was affected. Because lung cancer patients have low immunity after anti-tumor treatment, they should become the main targets for epidemic prevention. Lung cancer patients are increasingly concerned about the prevention of COVID-19. It is necessary to provide individualized medical treatment and management for lung cancer patients based on patients' conditions and regional epidemic patterns.
OUTPUT:
| Prevention;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
1,
0,
0
] |
LitCovid145 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: First cases of coronavirus disease 2019 (COVID-19) in France: surveillance, investigations and control measures, January 2020. A novel coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) causing a cluster of respiratory infections (coronavirus disease 2019, COVID-19) in Wuhan, China, was identified on 7 January 2020. The epidemic quickly disseminated from Wuhan and as at 12 February 2020, 45,179 cases have been confirmed in 25 countries, including 1,116 deaths. Strengthened surveillance was implemented in France on 10 January 2020 in order to identify imported cases early and prevent secondary transmission. Three categories of risk exposure and follow-up procedure were defined for contacts. Three cases of COVID-19 were confirmed on 24 January, the first cases in Europe. Contact tracing was immediately initiated. Five contacts were evaluated as at low risk of exposure and 18 at moderate/high risk. As at 12 February 2020, two cases have been discharged and the third one remains symptomatic with a persistent cough, and no secondary transmission has been identified. Effective collaboration between all parties involved in the surveillance and response to emerging threats is required to detect imported cases early and to implement adequate control measures.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid146 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: [Clinical characteristics of 30 medical workers infected with new coronavirus pneumonia]. Objective: To investigate the clinical characteristics of medical staff with novel coronavirus pneumonia(NCP). Methods: 30 patients infected with novel coronavirus referred to jianghan university hospital between January 11, 2020 and January 3, 2020 were studied. The data reviewed included those of clinical manifestations, laboratory investigation and Radiographic features. Results: The patients consisted of 10 men and 20 women, including 22 doctors and 8 nurses,aged 21~59 years(mean 35+/-8 years).They were divided to 26 common type and 4 severe cases, all of whom had close(within 1m) contact with patients infected of novel coronavirus pneumonia. The average contact times were 12 (7,16) and the average cumulative contact time was 2 (1.5,2.7) h.Clinical symptoms of these patients were fever in 23 patients (76.67%) , headache in 16 petients (53.33%) , fatigue or myalgia in 21patients (70%) , nausea, vomiting or diarrhea in 9 petients (30%) , cough in 25 petients (83.33%) , and dyspnea in 14 petients (46.67%) .Routine blood test revealed WBC <4.0x10(9)/L in 8 petients (26.67%) , (4-10) x10(9)/L in 22 petients (73.33%) , and WBC>4.0x10(9)/L in 4 petients (13.33%) during the disease.Lymphocyte count <1.0x10(9)/L occurred in 12 petients (40%),abnormal liver function in 7 petients (23.33%) ,myocardial damage in 5 petients(16.67%), elevated D-dimer (>0.5mg/l) in 5 patients (16.67%). Compared with normal patients, the average exposure times, cumulative exposure time, BMI, Fever time, white blood cell count, liver enzyme, LDH, myoenzyme and D-dimer were significantly increased in severe patients, while the lymphocyte count and albumin levels in peripheral blood were significantly decreased.Chest CT mainly showed patchy shadows and interstitial changes.According to imaging examination, 11 patients (36.67%) showed Unilateral pneumonia and 19 patients (63.33%) showed bilateral pneumonia,4 patients (13.33%) showed bilateral multiple mottling and ground-glass opacity.Compared with the patients infected in the protected period, the proportion of severe infection and bilateral pneumonia were both increased in the patients infected in unprotected period. Conclusion: Medical staffs are at higher risk of infection.Infection rates are associated with contact time, the amount of suction virus. Severe patients had BMI increased, heating time prolonged , white blood cell count, lymphocyte count, D-dimer and albumin level significantly changed and were prone to be complicated with liver damage and myocardial damage.Strict protection measures is important to prevent infection for medical workers.
OUTPUT:
| Mechanism;Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
0,
1,
0,
0
] |
LitCovid147 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system. In 2019-2020 a new coronavirus named SARS-CoV-2 was identified as the causative agent of a several acute respiratory infection named COVID-19, which is causing a worldwide pandemic. There are still many unresolved questions regarding the pathogenesis of this disease and especially the reasons underlying the extremely different clinical course, ranging from asymptomatic forms to severe manifestations, including the Acute Respiratory Distress Syndrome (ARDS). SARS-CoV-2 showed phylogenetic similarities to both SARS-CoV and MERS-CoV viruses, and some of the clinical features are shared between COVID-19 and previously identified beta-coronavirus infections. Available evidence indicate that the so called "cytokine storm" an uncontrolled over-production of soluble markers of inflammation which, in turn, sustain an aberrant systemic inflammatory response, is a major responsible for the occurrence of ARDS. Chemokines are low molecular weight proteins with powerful chemoattractant activity which play a role in the immune cell recruitment during inflammation. This review will be aimed at providing an overview of the current knowledge on the involvement of the chemokine/chemokine-receptor system in the cytokine storm related to SARS-CoV-2 infection. Basic and clinical evidences obtained from previous SARS and MERS epidemics and available data from COVID-19 will be taken into account.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid148 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning. Introduction The need to streamline patient management for coronavirus disease-19 (COVID-19) has become more pressing than ever. Chest X-rays (CXRs) provide a non-invasive (potentially bedside) tool to monitor the progression of the disease. In this study, we present a severity score prediction model for COVID-19 pneumonia for frontal chest X-ray images. Such a tool can gauge the severity of COVID-19 lung infections (and pneumonia in general) that can be used for escalation or de-escalation of care as well as monitoring treatment efficacy, especially in the ICU. Methods Images from a public COVID-19 database were scored retrospectively by three blinded experts in terms of the extent of lung involvement as well as the degree of opacity. A neural network model that was pre-trained on large (non-COVID-19) chest X-ray datasets is used to construct features for COVID-19 images which are predictive for our task. Results This study finds that training a regression model on a subset of the outputs from this pre-trained chest X-ray model predicts our geographic extent score (range 0-8) with 1.14 mean absolute error (MAE) and our lung opacity score (range 0-6) with 0.78 MAE. Conclusions These results indicate that our model's ability to gauge the severity of COVID-19 lung infections could be used for escalation or de-escalation of care as well as monitoring treatment efficacy, especially in the ICU. To enable follow up work, we make our code, labels, and data available online.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid149 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Spinal surgery in COVID-19 pandemic era: One trauma hub center experience in central-southern Italy. The aim of the study is to analyze and report the results of the surgical activity in a spinal unit of a trauma hub in central Italy during COVID-19 pandemic. Surgical activity was compared between COVID 19 pandemic and the same period of time in 2019 at our institution. A 50% reduction of surgical procedures during the last three months was observed compared with the same period of time in 2019. The compliance with the containment rules for the spread of the infection, were sufficient to allow safe surgical activity for the medical teams and patients.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid150 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: COVID-19 and Avoiding Ibuprofen. How Good Is the Evidence? Ibuprofen is an over-the-counter medication that is used widely for the treatment of pain and fever during COVID-19 pandemic. A concern was raised regarding the safety of ibuprofen use because of its role in increasing ACE2 levels within the Renin-Angiotensin-Aldosterone system. ACE2 is the coreceptor for the entry of SARS-CoV-2 into cells, and so, a potential increased risk of contracting COVID-19 disease and/or worsening of COVID-19 infection was feared with ibuprofen use. However, available data from limited studies show administration of recombinant ACE2 improves lung damage caused by respiratory viruses, suggesting ibuprofen use may be beneficial in COVID-19 disease. At this time, there is no supporting evidence to discourage the use of ibuprofen.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid151 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Mask or no mask for COVID-19: A public health and market study. Efficient strategies to contain the coronavirus disease 2019 (COVID-19) pandemic are peremptory to relieve the negatively impacted public health and global economy, with the full scope yet to unfold. In the absence of highly effective drugs, vaccines, and abundant medical resources, many measures are used to manage the infection rate and avoid exhausting limited hospital resources. Wearing masks is among the non-pharmaceutical intervention (NPI) measures that could be effectively implemented at a minimum cost and without dramatically disrupting social practices. The mask-wearing guidelines vary significantly across countries. Regardless of the debates in the medical community and the global mask production shortage, more countries and regions are moving forward with recommendations or mandates to wear masks in public. Our study combines mathematical modeling and existing scientific evidence to evaluate the potential impact of the utilization of normal medical masks in public to combat the COVID-19 pandemic. We consider three key factors that contribute to the effectiveness of wearing a quality mask in reducing the transmission risk, including the mask aerosol reduction rate, mask population coverage, and mask availability. We first simulate the impact of these three factors on the virus reproduction number and infection attack rate in a general population. Using the intervened viral transmission route by wearing a mask, we further model the impact of mask-wearing on the epidemic curve with increasing mask awareness and availability. Our study indicates that wearing a face mask can be effectively combined with social distancing to flatten the epidemic curve. Wearing a mask presents a rational way to implement as an NPI to combat COVID-19. We recognize our study provides a projection based only on currently available data and estimates potential probabilities. As such, our model warrants further validation studies.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid152 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Syncope, Brugada syndrome, and COVID-19 lung disease. A 52-year-old male with no history of familiar sudden death arrived at our Emergency Department after syncope with loss of consciousness occurred during high fever. The thoracic high-resolution computed tomography demonstrated bilateral multiple ground-glass opacities. The nose-pharyngeal swab resulted positive for SARS-CoV-2. The 12-lead ECG presented a "coved-type" aspect in leads V1 and V2 at the fourth intercostal space and a first degree atrio-ventricular block. As soon as the temperature went down, the 12-lead ECG resumed a normal aspect, maintaining a long PR interval.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid153 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Rethinking 'essential' and 'nonessential': the developmental paediatrician's COVID-19 response. While terms such as 'essential' and 'nonessential' used amidst the COVID-19 pandemic may serve a practical purpose, they also pose a risk of obstructing our view of the harmful indirect health consequences of this crisis. SARS-CoV-2 cases and deaths in children are minimal compared to adults, but the pandemic impacts other 'essential' aspects of children's health including child development and the associated areas of paediatric behaviour, mental health, and maltreatment. Alongside the management of severe SARS-CoV-2 cases in emergency rooms and intensive care units, continuing to care for children with developmental disabilities must also be concurrently championed as 'essential' during this crisis. The potentially devastating lifelong effects of the pandemic and isolation on an already vulnerable population demand that action be taken now. Video conferences and phone calls are 'essential' instruments we can use to continue to provide quality care for our patients.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid154 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Clinical Management of Adult Coronavirus Infection Disease 2019 (COVID-19) Positive in the Setting of Low and Medium Intensity of Care: a Short Practical Review. Coronavirus disease 2019 (COVID-2019) is a viral infection which is rapidly spreading on a global scale and causing a severe acute respiratory syndrome that affects today about four and a half million registered cases of people around the world. The aim of this narrative review is to provide an urgent guidance for the doctors who take care of these patients. Recommendations contained in this protocol are based on limited, non-definitive, evidence and experience-based opinions about patients with low and medium intensity of care. A short guidance on the management of COVID-19 is provided for an extensive use in different hospital settings. The evidence-based knowledge of COVID-19 is rapidly evolving, and we hope that, in the near future, a definitive and most efficacious treatment will be available including a specific vaccine for SARS-CoV-2.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid155 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Revisiting hydroxychloroquine and chloroquine for patients with chronic immunity-mediated inflammatory rheumatic diseases. Hydroxychloroquine and chloroquine, also known as antimalarial drugs, are widely used in the treatment of rheumatic diseases and have recently become the focus of attention because of the ongoing COVID-19 pandemic. Rheumatologists have been using antimalarials to manage patients with chronic immune-mediated inflammatory rheumatic diseases for decades. It is an appropriate time to review their immunomodulatory and anti-inflammatory mechanisms impact on disease activity and survival of systemic lupus erythematosus patient, including antiplatelet effect, metabolic and lipid benefits. We also discuss possible adverse effects, adding a practical and comprehensive approach to monitoring rheumatic patients during treatment with these drugs.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid156 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Opportunity of periodic monitoring of COVID-19 patients, asymptomatic virus carriers, and postinfectious individuals with IgM/IgG rapid antibody tests among healthcare workers during SARS-CoV-2 pandemic. The first Hungarian COVID-19 case was reported on March 4, 2020 by Hungarian officials. Healthcare workers (HCWs) are at the highest risk of contracting the novel coronavirus (SARS-CoV-2), with 12% of total coronavirus cases confirmed among them recently. 80% of the infected persons show only mild, moderate symptoms or stay asymptomatic. The single-stranded viral RNA can be detected by RT-PCR from the respiratory tract, urine, blood and, particulary in children, from stool samples for 30-40 days. We have no valid data of how many HCWs have been infected since the Hungarian SARS-CoV-2 outbreak, due to the lack of the systematic screening. HCWs could play a critical role in transmission and might jeopardize the health of both their patients and their own family members. Both cross-sectional and longitudinal sudies are recommended to evaluate the ratio of the recovered, i.e., "already protected", the ones in the acute phase, i.e., "the infectious", and the virus-naive, i.e., "at risk" workers. Of the available molecular diagnostic options, in addition to RT-PCR it would be advisable to introduce the novel rapid antibody tests which can give quick results, reveal the timeline of the infection, are easy to handle, inexpensive and can be used periodically to monitor HCWs' viral status during the still unkown duration of the SARS-CoV-2 pandemic. Orv Hetil. 2020; 161(21): 854-860.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid157 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: JAK Inhibition as a New Treatment Strategy for Patients with COVID-19. After the advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the outbreak of coronavirus disease 2019 (COVID-19) commenced across the world. Understanding the Immunopathogenesis of COVID-19 is essential for interrupting viral infectivity and preventing aberrant immune responses before a vaccine can be developed. In this review, we provide the latest insights into the roles of angiotensin-converting enzyme II (ACE2) and Ang II receptor-1 (AT1-R) in this disease. Novel therapeutic strategies, including recombinant ACE2, ACE inhibitors, AT1-R blockers, and Ang 1-7 peptides, may prevent or reduce viruses-induced pulmonary, cardiac, and renal injuries. However, more studies are needed to clarify the efficacy of these therapeutics. Furthermore, considering the common role of the Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway in AT1-R expressed on peripheral tissues and cytokine receptors on the surface of immune cells, potential targeting of this pathway using JAK inhibitors (JAKinibs) is suggested as a promising approach in patients with COVID-19 who are admitted to hospitals. In addition to antiviral therapy, potential ACE2- and AT1-R-inhibiting strategies, and other supportive care, we suggest other potential JAKinibs and novel anti-inflammatory combination therapies that affect the JAK-STAT pathway in patients with COVID-19. Since the combination of MTX and baricitinib leads to outstanding clinical outcomes, the addition of baricitinib to MTX might be a potential strategy.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid158 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: SARS-CoV-2 transmission dynamics should inform policy. It is generally agreed that striking a balance between resuming economic and social activities and keeping the effective reproductive number (R0) below 1 using non-pharmaceutical interventions is an important goal until and even after effective vaccines become available. Therefore, the need remains to understand how the virus is transmitted in order to identify high-risk environments and activities that disproportionately contribute to its spread so that effective preventative measures could be put in place. Contact tracing and household studies in particular provide robust evidence about the parameters of transmission. In this viewpoint, we discuss the available evidence from large-scale, well-conducted contact tracing studies from across the world and argue that SARS-CoV-2 transmission dynamics should inform policy decisions about mitigation strategies for targeted interventions according to the needs of the society by directing attention to the settings, activities and socioeconomic factors associated with the highest risks of transmission.
OUTPUT:
| Prevention;Transmission | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
0,
0,
1,
0,
0
] |
LitCovid159 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Sterilization plan of the used metered dose inhalers (MDI) to avoid wastage amid COVID-19 pandemic drug shortage. Background Coronavirus is causing a shortage of critical inhalers needed by patients with Asthma and respiratory illness. Patients with Asthma are at higher risk if they tract the novel Coronavirus. As the coronavirus continues to spread, hospitals are turning to use more salbutamol MDI. Salbutamol MDI has become the line of defence for physicians in the emergency room who are treating patients with Corona Virus Disease 2019 (COVID-19) and have respiratory distress .[Hui et al 2020 ,and Center for Drug Evaluation and Research 2020] During the COVID pandemic, there has been a drastic increase in the use of MDI inhalers; therefore, it led to a decrease in availability and a break in the supply chain. Patients with Asthma are at higher risk if they tract the novel Coronavirus, and an inhaler could be a life or death for them. As the coronavirus continues to spread, hospitals are turning to use more salbutamol Metered Dose inhaler (MDI). Salbutamol MDI is now on short supply as the COVID-19 continues to spread. Salbutamol MDI has become the line of defence for physicians in the emergency room who are treating patients with COVID-19 and have respiratory distress. The current shortage of salbutamol MDI could be a result of stockpiling and hoarding of this life-saving inhaler. That had led to a critical shortage of Salbutamol MDI, and even the case shortage continues with some other alternatives such as Ipratropium MDI and even with long-acting B-agonists such as Salmeterol and Formoterol which also starting to have a limitation on ordering these agents. Coronavirus sparks fear of medication shortage. Coronavirus panic-buying also may have led to a shortage of critical inhalers. We have also got elderly patients with COPD who may need Ventolin MDI and also premature babies who may have caught Respiratory Syncytial Virus (RSV) and need salbutamol MDI to support their lungs have since been compromised, and they rely heavily on Asthma inhalers. Finding a safe and creative strategy is essential during the COVID-19 pandemic.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid160 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: COVID-19 in a Patient with Accidental Drug-Induced Neutropenia. Background: Coronavirus disease 2019 (COVID-19) presents with a wide range of illness severity, from asymptomatic disease to severe acute respiratory distress syndrome (ARDS). Immunosuppression is considered a risk factor for severe COVID-19, but there are only few reports on disease progression in immunocompromised patients. Case Summary: We report the case of a 50-year-old patient with acute COVID-19 pneumonia, who had iatrogenic, clinically relevant bone marrow suppression due to accidental overdose with hydroxyurea, and decreased lung capacity due to a left-sided pneumonectomy 6 months earlier. Symptomatic treatment with oxygen supplementation and pulmonary physical therapy was initiated, and hydroxyurea was discontinued. Over 14 days, the patient's blood counts slowly recovered, and his clinical condition gradually improved, such that supplemental oxygen was no longer necessary and he could be discharged. Discussion: A gradual increase in neutrophil and lymphocyte counts may be preferable to dampen a potentially detrimental immunological response triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Whether patients with severe COVID-19 benefit from immunosuppressive therapy should be further evaluated. LEARNING POINTS: Acute respiratory distress syndrome is a serious complication in COVID-19 and appears to be triggered by a proinflammatory cytokine storm.Immunosuppression may avoid an immune hyper-response triggered by SARS-CoV-2.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid161 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Differences in SARS-CoV-2 recommendations from major ophthalmology societies worldwide. Objective: Since the WHO declared the COVID-19 outbreak as a public health emergency, medical societies around the world published COVID-19 recommendations to physicians to ensure patient care and physician safety. During this pandemic, ophthalmologists around the world adapted their clinical and surgical practice following such guidelines. This original research examines all publicly available COVID-19 recommendations from twelve major ophthalmology societies around the world. Methods and analysis: Twelve ophthalmology societies recognised by the International Council of Ophthalmology were included in this study. One society per each WHO region was included: the society selected was the one who had the highest number of national COVID-19 confirmed cases on 11 May 2020. In addition to these countries, the major ophthalmology society in each G7 country was included. Results: Ten out of 12 major international ophthalmology societies from countries covering all six WHO regions have given recommendations regarding urgent patient care, social distancing, telemedicine and personal protective equipment when caring for ophthalmic patients during the COVID-19 pandemic. While all guidelines emphasise the importance of postponing non-urgent care and taking necessary safety measures, specific recommendations differ between countries. Conclusions: As there is no clear consensus on ophthalmology guidelines across countries, this paper highlights the differences in international ophthalmic care recommendations during the COVID-19 pandemic. Knowledge of the differences in ophthalmic management plans will allow ophthalmologists and all eye care providers to consider the variety of international approaches and apply best practices following evidence-based recommendations during pandemics.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid162 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Angiotensin-converting enzyme inhibitors and angiotensin-receptor blockers and the risk of COVID-19 infection or severe disease: Systematic review and meta-analysis. Objective: Animal studies suggested that angiotensin-converting enzyme inhibitors (ACEi) and angiotensin-receptor blockers (ARB) facilitate the inoculation of potentially leading to a higher risk of infection and/or disease severity. We aimed to systematically evaluate the risk of COVID-19 infection and the risk of severe COVID-19 disease associated with previous exposure to (ACEi) and/or ARB). Methods: MEDLINE, CENTRAL, PsycINFO, Web of Science Core Collection were searched in June 2020 for controlled studies. Eligible studies were included and random-effects meta-analyses were performed. The estimates were expressed as odds ratios (OR) and 95% confidence intervals (95%CI). Heterogeneity was assessed with I(2) test. The confidence in the pooled evidence was appraised using the GRADE framework. Results: Twenty-seven studies were included in the review. ACEi/ARB exposure did not increase the risk of having a positive test for COVID-19 infection (OR 0.99, 95%CI 0.89-1.11; I(2) = 36%; 5 studies, GRADE confidence moderate). The exposure to ACEi/ARB did not increase the risk of all-cause mortality among patients with COVID-19 (OR 0.91, 95%CI 0.74-1.11; I(2) = 20%; 17 studies; GRADE confidence low) nor severe/critical COVID-19 disease (OR 0.90, 95%CI 0.74-1.11; I(2) = 55%; 17 studies; GRADE confidence very low). Exploratory analyses in studies enrolling hypertensive patients showed a association of ACEi/ARB with a significant decrease of mortality risk. Conclusions: ACEi/ARB exposure does not seem to increase the risk of having the SARS-CoV-2 infection or developing severe stages of the disease including mortality. The potential benefits observed in mortality of hypertensive patients reassure safety, but robust studies are required to increase the confidence in the results.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid163 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Clinical features, diagnostics, and outcomes of patients presenting with acute respiratory illness: A retrospective cohort study of patients with and without COVID-19. Background: Most data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have been presented as case series without comparison to patients with other acute respiratory illnesses. Methods: We examined emergency department patients between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared clinical presentation, diagnostics, treatment, and outcomes. Findings: Among 316 patients, 33 tested positive for SARS-CoV-2; 31 without COVID-19 tested positive for another respiratory virus. Among patients with additional viral testing (27/33), no SARS-CoV-2 co-infections were identified. Compared to those who tested negative, patients with COVID-19 reported longer symptoms duration (median 7d vs. 3d, p < 0.001). Patients with COVID-19 were more often hospitalized (79% vs. 56%, p = 0.014). When hospitalized, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p < 0.001) and more often developed ARDS (23% vs. 3%, p < 0.001). Most comorbidities, medications, symptoms, vital signs, laboratories, treatments, and outcomes did not differ by COVID-19 status. Interpretation: While we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. Funding: National Center for Advancing Translational Sciences, National Heart Lung Blood Institute, National Institute of Allergy and Infectious Diseases, Chan Zuckerberg Biohub, Chan Zuckerberg Initiative.
OUTPUT:
| Treatment;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid164 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Hepatitis A susceptibility parallels high COVID-19 mortality. The COVID-19 has become the biggest health problem of our century. We hypothesized that immunity against Hepatitis A virus (HAV) may provide protection from COVID- 19. As of June 10, 2020, the infection had spread to 213 countries, with 7.3 million people infected and 413,733 dead . We combined this data with the WHO's susceptibility classification on the prevalence of HAV in the world. We found a significant relationship between Covid 19 mortality and HAV susceptibility (p<0.001). If confirmed, the consequences of this simple discovery will be enormous.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid165 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: A Comprehensive Mapping of the Druggable Cavities within the SARS-CoV-2 Therapeutically Relevant Proteins by Combining Pocket and Docking Searches as Implemented in Pockets 2.0. (1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) require a detailed characterization of their druggable binding sites, and, more generally, a convenient pocket mapping represents a key step for structure-based in silico studies; (2) Methods: Along with a careful literature search on SARS-CoV-2 protein targets, the study presents a novel strategy for pocket mapping based on the combination of pocket (as performed by the well-known FPocket tool) and docking searches (as performed by PLANTS or AutoDock/Vina engines); such an approach is implemented by the Pockets 2.0 plug-in for the VEGA ZZ suite of programs; (3) Results: The literature analysis allowed the identification of 16 promising binding cavities within the SARS-CoV-2 proteins and the here proposed approach was able to recognize them showing performances clearly better than those reached by the sole pocket detection; and (4) Conclusions: Even though the presented strategy should require more extended validations, this proved successful in precisely characterizing a set of SARS-CoV-2 druggable binding pockets including both orthosteric and allosteric sites, which are clearly amenable for virtual screening campaigns and drug repurposing studies. All results generated by the study and the Pockets 2.0 plug-in are available for download.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid166 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Should We Try SARS-CoV-2 Helicase Inhibitors for COVID-19 Therapy? The discovery of new drugs for treating the new coronavirus (SARS-CoV-2) or repurposing those already in use for other viral infections is possible through understanding of the viral replication cycle and pathogenicity. This article highlights the advantage of targeting one of the non-structural proteins, helicase (nsp13), over other SARS-CoV-2 proteins. Highlighting the experience gained from targeting Nsp13 in similar coronaviruses (SARS-CoV and MERS) and known inhibitors, the article calls for research on helicase inhibitors as potential COVID-19 therapy.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid167 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Hydroxychloroquine and Chloroquine Prescribing Patterns by Provider Specialty Following Initial Reports of Potential Benefit for COVID-19 Treatment - United States, January-June 2020. Hydroxychloroquine and chloroquine, primarily used to treat autoimmune diseases and to prevent and treat malaria, received national attention in early March 2020, as potential treatment and prophylaxis for coronavirus disease 2019 (COVID-19) (1). On March 20, the Food and Drug Administration (FDA) issued an emergency use authorization (EUA) for chloroquine phosphate and hydroxychloroquine sulfate in the Strategic National Stockpile to be used by licensed health care providers to treat patients hospitalized with COVID-19 when the providers determine the potential benefit outweighs the potential risk to the patient.* Following reports of cardiac and other adverse events in patients receiving hydroxychloroquine for COVID-19 (2), on April 24, 2020, FDA issued a caution against its use(dagger) and on June 15, rescinded its EUA for hydroxychloroquine from the Strategic National Stockpile.( section sign) Following the FDA's issuance of caution and EUA rescindment, on May 12 and June 16, the federal COVID-19 Treatment Guidelines Panel issued recommendations against the use of hydroxychloroquine or chloroquine to treat COVID-19; the panel also noted that at that time no medication could be recommended for COVID-19 pre- or postexposure prophylaxis outside the setting of a clinical trial (3). However, public discussion concerning the effectiveness of these drugs on outcomes of COVID-19 (4,5), and clinical trials of hydroxychloroquine for prophylaxis of COVID-19 continue.( paragraph sign) In response to recent reports of notable increases in prescriptions for hydroxychloroquine or chloroquine (6), CDC analyzed outpatient retail pharmacy transaction data to identify potential differences in prescriptions dispensed by provider type during January-June 2020 compared with the same period in 2019. Before 2020, primary care providers and specialists who routinely prescribed hydroxychloroquine, such as rheumatologists and dermatologists, accounted for approximately 97% of new prescriptions. New prescriptions by specialists who did not typically prescribe these medications (defined as specialties accounting for </=2% of new prescriptions before 2020) increased from 1,143 prescriptions in February 2020 to 75,569 in March 2020, an 80-fold increase from March 2019. Although dispensing trends are returning to prepandemic levels, continued adherence to current clinical guidelines for the indicated use of these medications will ensure their availability and benefit to patients for whom their use is indicated (3,4), because current data on treatment and pre- or postexposure prophylaxis for COVID-19 indicate that the potential benefits of these drugs do not appear to outweigh their risks.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid168 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Transcription factor-mediated signaling pathways' contribution to the pathology of acute lung injury and acute respiratory distress syndrome. The 2019 novel coronavirus (2019-nCoV) is still spreading rapidly around the world, and one cause of lethality for patients infected with 2019-nCoV is acute respiratory distress syndrome (ARDS). ARDS is a severe syndrome of acute lung injury (ALI) that is predominantly triggered by inflammation and results in a sudden loss of, or damage to, kidney function. Emerging studies reveal that multiple transcription factor-associated signaling pathways are activated in the pathology of ALI/ARDS. Of these pathways, the activation of NF-kappaB (nuclear factor kappa-light-chain-enhancer of activated B cells), AP-1 (activator protein 1), IRFs (interferon regulatory factors), STATs (signal transducer and activator of transcription), Wnt/beta-catenin-TCF/LEF (T-cell factor/lymphoid enhancer-binding factor), and CtBP2 (C-Terminal binding protein 2)-associated transcriptional complex contributes to ALI/ARDS pathology through diverse mechanisms, such as inducing proinflammatory cytokine levels and mediating macrophage polarization. In this review, we present an updated summary of the mechanisms underlying these signaling activations and regulations, as well as their contribution to the pathogenesis of ALI/ARDS. We aim to develop a better understanding of how ALI/ARDS occurs and improve ALI/ARDS therapy.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid169 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets. BACKGROUND: Social distancing is an important component of the response to the COVID-19 pandemic. Minimizing social interactions and travel reduces the rate at which the infection spreads and "flattens the curve" so that the medical system is better equipped to treat infected individuals. However, it remains unclear how the public will respond to these policies as the pandemic continues. OBJECTIVE: The aim of this study is to present the Twitter Social Mobility Index, a measure of social distancing and travel derived from Twitter data. We used public geolocated Twitter data to measure how much users travel in a given week. METHODS: We collected 469,669,925 tweets geotagged in the United States from January 1, 2019, to April 27, 2020. We analyzed the aggregated mobility variance of a total of 3,768,959 Twitter users at the city and state level from the start of the COVID-19 pandemic. RESULTS: We found a large reduction (61.83%) in travel in the United States after the implementation of social distancing policies. However, the variance by state was high, ranging from 38.54% to 76.80%. The eight states that had not issued statewide social distancing orders as of the start of April ranked poorly in terms of travel reduction: Arkansas (45), Iowa (37), Nebraska (35), North Dakota (22), South Carolina (38), South Dakota (46), Oklahoma (50), Utah (14), and Wyoming (53). We are presenting our findings on the internet and will continue to update our analysis during the pandemic. CONCLUSIONS: We observed larger travel reductions in states that were early adopters of social distancing policies and smaller changes in states without such policies. The results were also consistent with those based on other mobility data to a certain extent. Therefore, geolocated tweets are an effective way to track social distancing practices using a public resource, and this tracking may be useful as part of ongoing pandemic response planning.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid170 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Recommendations for treatment of nail psoriasis during the COVID-19 pandemic. The novel coronavirus disease 2019 (COVID-19) pandemic has resulted in a paradigm shift in disease management. Since immunosuppression may cause increased susceptibility to COVID-19, there is uncertainty as to whether systemically treated nail psoriasis patients are at increased infection risk. While specific data on nail psoriasis treatments and COVID-19 is lacking, we present clinical trial data on rates of upper respiratory infections, nasopharyngitis, viral infection, pneumonia and overall infections. Some systemic medications and biologics are associated with increased in infections risk compared to placebo in clinical trials. However, this data should be regarded cautiously since clinical trials on nail psoriasis, particularly controlled studies, are lacking. Our recommendations may be helpful in guiding physicians managing nail psoriasis patients during the COVID-19 pandemic.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid171 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: SARS-CoV-2 and influenza: a comparative overview and treatment implications. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Alphainfluenzavirus are RNA viruses that cause coronavirus disease-19 and influenza, respectively. Both viruses infect the respiratory tract, show similar symptoms, and use surface proteins to infect the host. Influenza requires hemagglutinin and neuraminidase to infect, whereas SARS-CoV-2 uses protein S. Both viruses depend on a viral RNA polymerase to express their proteins, but only SARS-CoV-2 has a proofreading mechanism, which results in a low mutation rate compared to influenza. E1KC4 and camostat mesylate are potential inhibitors of SARS-CoV-2 S protein, achieving an effect similar to oseltamivir. Due to the SARS-CoV-2 low mutation rate, nucleoside analogs have been developed (such as EIDD-2801), which insert lethal mutations in the viral RNA. Furthermore, the SARS-CoV-2 low mutation rate suggests that a vaccine, as well as the immunity developed in recovered patients, could provide long-lasting protection compared to vaccines against influenza, which are rendered obsolete as the virus mutates.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid172 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: COVID-19: pathogenesis, genetic polymorphism, clinical features and laboratory findings COVID-19 caused by a novel agent SARS-CoV-2 progressed to a pandemic condition and resulted in a major public health concern worldwide, leading to social and economic issues at the same time. The pathogenesis of COVID-19 starts with the bonding of the virus to ACE2 receptors expressed in many tissues, and the triggered excessive immune response plays a critical role in the course of the disease. The cytokine storm that occurs upon excessive production of pro-inflammatory cytokines is considered responsible for the severe progression of the disease and the organ damage. However, the accurate pathophysiological mechanism of the disease, which progresses with various clinical presentations, is still substantially unknown. While various studies have been conducted on the effect of genetic polymorphism on the course and severity of the disease, the presence of a significant effect has not been proven yet. The clinical course of the disease is variable, with clinical representation ranging from 81% mild course to 14% severe course along with 5% critical course in patients. Asymptomatic course is considered to be higher than expected, although its frequency is not known exactly. Older adults and those with comorbidities are exposed to a more severe disease course. The disease progress with various symptoms, such as fever, cough, dyspnea, malaise, myalgia, taste and smell dysfunctions, diarrhea, and headache. A range of complications (acute respiratory distress syndrome, thromboembolic conditions, arrhythmia and cardiac events, secondary infections) could be seen during the course of the disease. Varied laboratory tests are vital to determine these verity and prognosis of the disease, along with the condition and exposure of the affected systems during thecourse of COVID-19.
OUTPUT:
| Mechanism;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
1,
0,
0,
0,
0
] |
LitCovid173 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: A mathematical model to guide the re-opening of economies during the COVID-19 pandemic. Despite rigorous global containment and quarantine efforts, the incidence of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19, continues to surge, with more than 12 million laboratory-confirmed cases and over 500,000 deaths worldwide (as of 11 July 2020). Aside from the continued surge in cases and the imperatives of public health concern and saving lives, economic devastation is also mounting with a global depression now seeming inevitable. There is limited attention directed towards people who have recovered from the virus and whether this metric can be useful in guiding when the economy can be re-opened. In this paper, a simpler model is presented in order to guide various countries on the (possible) re-opening of the economy (or re-opening in stages/phases) alongside risk categories and ratios. Factors that need to be considered when applying the model include the healthcare capacity in terms of the number of hospitals, beds and healthcare workers that are available to capacitate this virus. In addition, population size, physical distancing measures, socio-economic disparities, lockdown regulations in each country, and more importantly - the amount and accuracy of testing conducted, is also imperative to consider. Decisions adopted by leaders around the world have the most difficult decision to make (yet), and have to weigh up on what really matters; health or wealth. It is suggested that this model be applied in a number of states/counties and countries in order to gauge the risk of their location being re-opened, by observing their total number of recoveries in proximity to total number of cases.
OUTPUT:
| Epidemic Forecasting;Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
1
] |
LitCovid174 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens. Quantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 RNA from 77 patients, and compared with RT-PCR in terms of the diagnostic accuracy based on the results of follow-up survey. 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by ddPCR. The sensitivity, specificity, PPV, NPV, negative likelihood ratio (NLR) and accuracy were improved from 40% (95% CI: 27-55%), 100% (95% CI: 54-100%), 100%, 16% (95% CI: 13-19%), 0.6 (95% CI: 0.48-0.75) and 47% (95% CI: 33-60%) for RT-PCR to 94% (95% CI: 83-99%), 100% (95% CI: 48-100%), 100%, 63% (95% CI: 36-83%), 0.06 (95% CI: 0.02-0.18), and 95% (95% CI: 84-99%) for ddPCR, respectively. Moreover, 6/14 (42.9%) convalescents were detected as positive by ddPCR at 5-12 days post discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the RT-PCR.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid175 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Kawasaki-like disease in children with COVID-19: A hypothesis. With rapid spread of severe acute respiratory syndrome- corona virus-2 (SARS-COV-2) globally, some new aspects of the disease have been reported. Recently, it has been reported the incidence of Kawasaki-like disease among children with COVID-19. Since, children had been known to be less severely affected by the virus in part due to the higher concentration of Angiotensin converting enzyme (ACE)-2 receptor, this presentation has emerged concerns regarding the infection of children with SARS-COV2. ACE2 has anti-inflammatory, anti-fibrotic and anti-proliferative characteristics through converting angiotensin (Ag)-II to Ang (1-7). ACE2 receptor is downregulated by the SARS-COV through the spike protein of SARS-CoV (SARS-S) via a process that is tightly coupled with Tumor necrosis factor (TNF)-alpha production. TNF-alpha plays a key role in aneurysmal formation of coronary arteries in Kawasaki disease (KD). Affected children by COVID-19 with genetically-susceptible to KD might have genetically under-expression of ACE2 receptor that might further decrease the expression of ACE2 due to the downregulation of the receptor by the virus in these patients. It appears that TNF- alpha might be the cause and the consequence of the ACE2 receptor downregulation which results in arterial walls aneurysm. Conclusion: Genetically under-expression of ACE2 receptor in children with genetically-susceptible to KD who are infected with SARS-CoV-2 possibly further downregulates the ACE2 expression by TNF-alpha and leads to surge of inflammation including TNF-alpha and progression to Kawasaki-like disease.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid176 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Persistence of serum and saliva antibody responses to SARS-CoV-2 spike antigens in COVID-19 patients. While the antibody response to SARS-CoV-2 has been extensively studied in blood, relatively little is known about the antibody response in saliva and its relationship to systemic antibody levels. Here, we profiled by enzyme-linked immunosorbent assays (ELISAs) IgG, IgA and IgM responses to the SARS-CoV-2 spike protein (full length trimer) and its receptor-binding domain (RBD) in serum and saliva of acute and convalescent patients with laboratory-diagnosed COVID-19 ranging from 3-115 days post-symptom onset (PSO), compared to negative controls. Anti-SARS-CoV-2 antibody responses were readily detected in serum and saliva, with peak IgG levels attained by 16-30 days PSO. Longitudinal analysis revealed that anti-SARS-CoV-2 IgA and IgM antibodies rapidly decayed, while IgG antibodies remained relatively stable up to 105 days PSO in both biofluids. Lastly, IgG, IgM and to a lesser extent IgA responses to spike and RBD in the serum positively correlated with matched saliva samples. This study confirms that serum and saliva IgG antibodies to SARS-CoV-2 are maintained in the majority of COVID-19 patients for at least 3 months PSO. IgG responses in saliva may serve as a surrogate measure of systemic immunity to SARS-CoV-2 based on their correlation with serum IgG responses.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid177 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Consumer Reported Care Deferrals Due to the COVID-19 Pandemic, and the Role and Potential of Telemedicine: Cross-Sectional Analysis. BACKGROUND: The COVID-19 pandemic forced many health systems to proactively reduce care delivery to prepare for an expected surge in hospitalizations. There have been concerns that care deferral may have negative health effects, but it is hoped that telemedicine can provide a viable alternative. OBJECTIVE: This study aimed to understand what type of health care services were being deferred during the COVID-19 pandemic lockdown, the role played by telemedicine to fill in care gaps, and changes in attitudes toward telemedicine. METHODS: We conducted a cross-sectional analysis of survey responses from 1694 primary care patients in a mid-sized northeastern city. Our main outcomes were use of telemedicine and reports of care deferral during the shutdown. RESULTS: Deferred care was widespread-48% (n=812) of respondents deferred care-but it was largely for preventive services, particularly dental and primary care, and did not cause concerns about negative health effects. In total, 30.2% (n=242) of those who delayed care were concerned about health effects, with needs centered around orthopedics and surgery. Telemedicine was viewed more positively than prior to the pandemic; it was seen as a viable option to deliver deferred care, particularly by respondents who were over 65 years of age, female, and college educated. Mental health services stood out for having high levels of deferred care. CONCLUSIONS: Temporary health system shutdowns will give rise to deferred care. However, much of the deferrals will be for preventive services. The effect of this on patient health can be moderated by prioritizing surgical and orthopedic services and delivering other services through telemedicine. Having telemedicine as an option is particularly crucial for mental health services.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid178 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Impact of COVID-19 pandemic on residency and fellowship training programs in Saudi Arabia: A nationwide cross-sectional study. Background: Coronavirus disease 2019 (COVID-19) has profoundly impacted residency and fellowship training and education. However, how and to what extent the daily involvement of trainees in clinical and surgical activities was compromised by the COVID-19 pandemic is currently unknown. Materials and methods: We conducted an electronic survey. An invitation was sent through the executive training administration of the Saudi Commission for Health Specialties (SCFHS) randomly to 400 residents and fellows over two weeks period from April 23, 2020 until May 6, 2020. Descriptive statistics were presented using counts and proportions (%). The comparison between the trainees among the socio-demographic and the characteristics of trainees toward the impact of COVID-19 pandemic on their training had been conducted using the Chi-square test. A p-value cut off point of 0.05 at 95% Confidence Interval (CI) used to determine statistical significance. Results: Out of the 400 questionnaires distributed, 240 trainees responded, resulting in a response rate of 60%. The most frequently cited specialty was surgical (41.3%) and medical (38.3%). Approximately 43% of them had direct contact with patients with COVID-19, and 43.8% had enough training regarding the proper use of Personal Protective Equipment (PPE). There were seven responders (2.9%) who had been infected by the disease. Among them, 6 (2.5%) members of their family had also been infected. Approximately 84.6% reported a reduction in training activities due to the current pandemic. Of those with surgical specialties, almost all (97%) reported that their surgical exposure reduced due to the COVID-19 pandemic. Conclusion: The adoption of smart learning is critical. For those who have been affected by examination delays, we recommend continuing to revise steadily using webinars, podcasts, prerecorded sessions, and social media. Routine activities such as journal clubs and departmental teaching should continue through webinars, if possible.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid179 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Racial Disparities in COVID-19 Mortality Among Essential Workers in the United States. Racial disparities are apparent in the impact of coronavirus disease 2019 (COVID-19) in the United States, yet the factors contributing to racial inequities in COVID-19 mortality remain controversial. To better understand these factors, we investigated racial disparities in COVID-19 mortality among America's essential workers. Data from the American Community Survey and Current Population Survey was used to examine the correlation between the prevalence of COVID-19 deaths and occupational differences across racial/ethnic groups and states. COVID-19 mortality was higher among non-Hispanic (NH) Blacks compared with NH Whites, due to more NH Blacks holding essential-worker positions. Vulnerability to coronavirus exposure was increased among NH Blacks, who disproportionately occupied the top nine essential occupations. As COVID-19 death rates continue to rise, existing structural inequalities continue to shape racial disparities in this pandemic. Policies mandating the disaggregation of state-level data by race/ethnicity are vital to ensure equitable and evidence-based response and recovery efforts.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid180 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Chinese Therapeutic Strategy for Fighting COVID-19 and Potential Small-Molecule Inhibitors against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to more than 20 million people infected worldwide with an average mortality rate of 3.6%. This virus poses major challenges to public health, as it not only is highly contagious but also can be transmitted by asymptomatic infected individuals. COVID-19 is clinically difficult to manage due to a lack of specific antiviral drugs or vaccines. In this article, Chinese therapy strategies for treating COVID-19 patients, including current applications of traditional Chinese medicine (TCM), are comprehensively reviewed. Furthermore, 72 small molecules from natural products and TCM with reported antiviral activity against human coronaviruses (CoVs) are identified from published literature, and their potential applications in combating SARS-CoV-2 are discussed. Among these, the clinical efficacies of some accessible drugs such as remdesivir (RDV) and favipiravir (FPV) for COVID-19 are emphatically summarized. We hope this review provides a foundation for managing the worsening pandemic and developing antivirals against SARS-CoV-2.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid181 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Neurological Complications Associated with the Blood-Brain Barrier Damage Induced by the Inflammatory Response During SARS-CoV-2 Infection. The main discussion above of the novel pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has focused substantially on the immediate risks and impact on the respiratory system; however, the effects induced to the central nervous system are currently unknown. Some authors have suggested that SARS-CoV-2 infection can dramatically affect brain function and exacerbate neurodegenerative diseases in patients, but the mechanisms have not been entirely described. In this review, we gather information from past and actual studies on coronaviruses that informed neurological dysfunction and brain damage. Then, we analyzed and described the possible mechanisms causative of brain injury after SARS-CoV-2 infection. We proposed that potential routes of SARS-CoV-2 neuro-invasion are determinant factors in the process. We considered that the hematogenous route of infection can directly affect the brain microvascular endothelium cells that integrate the blood-brain barrier and be fundamental in initiation of brain damage. Additionally, activation of the inflammatory response against the infection represents a critical step on injury induction of the brain tissue. Consequently, the virus' ability to infect brain cells and induce the inflammatory response can promote or increase the risk to acquire central nervous system diseases. Here, we contribute to the understanding of the neurological conditions found in patients with SARS-CoV-2 infection and its association with the blood-brain barrier integrity.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid182 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Attitudes of health professionals towards the response to the COVID-19 pandemic in Maghreb. OBJECTIVE: Measuring the attitudes of health professionals in two Maghreb countries (Tunisia and Algeria) with regard to the response to COVID-19 during the first quarter of 2020. METHODS: This scoping study was based on a "Google Form" covering three constituents of the response plan against COVID-19: responders, activities and crisis communication. The attitudes of health professionals who are working in Tunisia and Algeria were measured through the Likert scale with four propositions, grouped in pairs, during the analysis. RESULTS: The study population consisted of 280 health professionals, 170 of whom are Tunisians along with 110 Algerians. The medians of age and that of professional seniority are, respectively, 37 and 10 years. The role of "health workers", "Mass Media" and "civil society associations" was found to be satisfactory according, respectively, to 92%, 71%, and 55% of the respondents. As far as 72% of health professionals are concerned, the "barrier measures" were respected by the population. Approximately, seven in ten respondents were satisfied with the quality of communication occuring between the Ministries of Health and its epidemiological structures. CONCLUSION: Health professionals of the Maghreb working in Tunisia and Algeria had a generally positive perception of the role of population responders, community engagement, and the quality of official communication in regards to the response plan against COVID- 19. This perception would be a prerequisite for the success of community participation and multisectoral action as well as essential in the strategy of prevention and control of this pandemic and of possible other health emergencies.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid183 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Massively multiplexed nucleic acid detection with Cas13. The great majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples(1-3) while simultaneously testing for many pathogens(4-6). Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanolitre droplets containing CRISPR-based nucleic acid detection reagents(7) self-organize in a microwell array(8) to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN-Cas13) enables robust testing of more than 4,500 crRNA-target pairs on a single array. Using CARMEN-Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with at least 10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN-Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. The intrinsic multiplexing and throughput capabilities of CARMEN make it practical to scale, as miniaturization decreases reagent cost per test by more than 300-fold. Scalable, highly multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health(9-11).
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid184 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Potential of Ocular Transmission of SARS-CoV-2: A Review. PURPOSE OF REVIEW: to provide a prospective on the current mechanisms by which SARS-CoV-2 enters cells and replicates, and its implications for ocular transmission. The literature was analyzed to understand ocular transmission as well as molecular mechanisms by which SARS-CoV-2 enters cells and replicates. Analysis of gene expression profiles from available datasets, published immunohistochemistry, as well as current literature was reviewed, to assess the likelihood that ocular inoculation of SARS-CoV-2 results in systemic infection. RECENT FINDINGS: The ocular surface and retina have the necessary proteins, Transmembrane Serine Protease 2 (TMPRSS2), CD147, Angiotensin-Converting Enzyme 2 (ACE2) and Cathepsin L (CTSL) necessary to be infected with SARS-CoV-2. In addition to direct ocular infection, virus carried by tears through the nasolacrimal duct to nasal epithelium represent a means of ocular inoculation. SUMMARY: There is evidence that SARS-CoV-2 may either directly infect cells on the ocular surface, or virus can be carried by tears through the nasolacrimal duct to infect the nasal or gastrointestinal epithelium.
OUTPUT:
| Transmission;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
1,
0,
0,
0,
0,
0
] |
LitCovid185 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Providing essential clinical care for non-COVID-19 patients in a Seoul metropolitan acute care hospital amidst ongoing treatment of COVID-19 patients. We assessed infection control efforts by comparing data collected over 20 weeks during a pandemic under a dual-track healthcare system. A decline in non-COVID-19 patients visiting the emergency department by 37.6% (P<0.01) was observed since admitting COVID-19 cases. However, patients with acute myocardial infarction (AMI), stroke, severe trauma and acute appendicitis presenting for emergency care did not decrease. Door-to-balloon time (34.3 (+/- 11.3) min vs 22.7 (+/- 8.3) min) for AMI improved significantly (P<0.01) while door-to-needle time (55.7 (+/- 23.9) min vs 54.0 (+/- 18.0) min) in stroke management remained steady (P=0.80). Simultaneously, time-sensitive care involving other clinical services, including patients requiring chemotherapy, radiation therapy and haemodialysis did not change.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid186 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Acute encephalopathy is associated with worse outcomes in COVID-19 patients. Background: Acute encephalopathy with COVID-19 has been reported in several studies but its impact on outcomes remains unclear. We hypothesized that hospitalized COVID-19 patients with encephalopathy have worse COVID-19 related outcomes. Methods: We used TriNetX, with a large COVID-19 database, collecting real-time electronic medical records data. We included hospitalized COVID-19 patients since January 20, 2020 who had encephalopathy based on ICD-10 coding. We examined clinical outcomes comprising need for critical care services, intubation and mortality among these patients and compared it with patients without encephalopathy before and after propensity-score matching. Results: Of 12,601 hospitalized COVID-19 patients, 1092 (8.7%) developed acute encephalopathy. Patients in the acute encephalopathy group were older (67 vs. 61 years) and had higher prevalence of medical co-morbidities including obesity, hypertension, diabetes, heart disease, COPD, chronic kidney and liver disease among others. Before and after propensity score-matching for co-morbidities, patients with acute encephalopathy were more likely to need critical care services (35.6% vs. 16.9%, p < 0.0001), intubation (19.5% vs. 6.0%, p < 0.0001) and had higher 30-day mortality (24.3% vs. 17.9%, p 0.0002). Conclusion: Among hospitalized COVID-19 patients, acute encephalopathy is common and more likely to occur in patients with medical co-morbidities and are more likely to need critical care, intubation and have higher 30-day mortality even after adjusting for age and underlying medical co-morbidities.
OUTPUT:
| Treatment;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid187 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: A retrospective study of the initial chest CT imaging findings in 50 COVID-19 patients stratified by gender and age. OBJECTIVE: To retrospectively analyze and stratify the initial clinical features and chest CT imaging findings of patients with COVID-19 by gender and age. METHODS: Data of 50 COVID-19 patients were collected in two hospitals. The clinical manifestations, laboratory examination and chest CT imaging features were analyzed, and a stratification analysis was performed according to gender and age [younger group: <50 years old, elderly group >/=50 years old]. RESULTS: Most patients had a history of epidemic exposure within 2 weeks (96%). The main clinical complaints are fever (54%) and cough (46%). In chest CT images, ground-glass opacity (GGO) is the most common feature (37/38, 97%) in abnormal CT findings, with the remaining 12 patients (12/50, 24%) presenting normal CT images. Other concomitant abnormalities include dilatation of vessels in lesion (76%), interlobular thickening (47%), adjacent pleural thickening (37%), focal consolidation (26%), nodules (16%) and honeycomb pattern (13%). The lesions were distributed in the periphery (50%) or mixed (50%). Subgroup analysis showed that there was no difference in the gender distribution of all the clinical and imaging features. Laboratory findings, interlobular thickening, honeycomb pattern and nodules demonstrated remarkable difference between younger group and elderly group. The average CT score for pulmonary involvement degree was 5.0+/-4.7. Correlation analysis revealed that CT score was significantly correlated with age, body temperature and days from illness onset (p < 0.05). CONCLUSIONS: COVID-19 has various clinical and imaging appearances. However, it has certain characteristics that can be stratified. CT plays an important role in disease diagnosis and early intervention.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid188 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Epidemic evolution models to the test of Covid-19. We illustrate a suitable adaptation and modification of classical epidemic evolution models that proves helpful in the study of Covid-19 spread in Italy.
OUTPUT:
| Epidemic Forecasting | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
0,
1
] |
LitCovid189 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: [SOFFCO-MM guidelines for the resumption of bariatric and metabolic surgery during and after the Covid-19 pandemic]. Bariatric/metabolic surgery was paused during the Covid-19 pandemic. The impact of social confinement and the interruption of this surgery on the population with obesity has been underestimated, with weight gain and worsened comorbidities. Some candidates for this surgery are exposed to a high risk of mortality linked to the pandemic. Obesity and diabetes are two major risk factors for severe forms of Covid-19. The only currently effective treatment for obesity is metabolic surgery, which confers prompt, lasting benefits. It is thus necessary to resume such surgery. To ensure that this resumption is both gradual and well-founded, we have devised a priority ranking plan. The flow charts we propose will help centres to identify priority patients according to a benefit/risk assessment. Diabetes holds a central place in the decision tree. Resumption patterns will vary from one centre to another according to human, physical and medical resources, and will need adjustment as the epidemic unfolds. Specific informed consent will be required. Screening of patients with obesity should be considered, based on available knowledge. If Covid-19 is suspected, surgery must be postponed. Emphasis must be placed on infection control measures to protect patients and healthcare professionals. Confinement is strongly advocated for patients for the first month post-operatively. Patient follow-up should preferably be by teleconsultation.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid190 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Obesity and diabetes as high-risk factors for severe coronavirus disease 2019 (Covid-19). The outbreak of the coronavirus disease 2019 (Covid-19) has become an evolving worldwide health crisis. With the rising prevalence of obesity and diabetes has come an increasing awareness of their impacts on infectious diseases, including increased risk for various infections, post-infection complications and mortality from critical infections. Although epidemiological and clinical characteristics of Covid-19 have been constantly reported, no article has systematically illustrated the role of obesity and diabetes in Covid-19, or how Covid-19 affects obesity and diabetes, or special treatment in these at-risk populations. Here, we present a synthesis of the recent advances in our understanding of the relationships between obesity, diabetes and Covid-19 along with the underlying mechanisms, and provide special treatment guidance for these at-risk populations.
OUTPUT:
| Treatment;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid191 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Point-of-Care Lung Ultrasound findings in novel coronavirus disease-19 pnemoniae: a case report and potential applications during COVID-19 outbreak. An outbreak of a novel coronavirus disease-19 (nCoV-19) infection began in December 2019 in Wuhan, China, and now involved the whole word. Several health workers have been infected in different countries. We report the case of a young man with documented nCoV-19 infection evaluated with lung ultrasound and discuss potential applications of lung ultrasound in this setting. Lung ultrasound allowed the identification of nCoV-19 infection at bed-side. Moreover, lung ultrasound can have several other advantages, such as reduced health worker exposition to infected patients, repeatability during follow-up, low-costs and easier application in low-resource settings.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid192 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Risks of COVID-19 transmission in blood and serum during surgery A prospective cross-sectional study from a single dedicated COVID-19 center. The present pandemic caused by the SARS COV-2 coronavirus is still ongoing, although it is registered a slowdown in the spread for new cases. The main environmental route of transmission of SARS-CoV-2 is through droplets and fomites or surfaces, but there is a potential risk of virus spread also in smaller aerosols during various medical procedures causing airborne transmission. To date, no information is available on the risk of contagion from the peritoneal fluid with which surgeons can come into contact during the abdominal surgery on COVID-19 patients. We have investigated the presence of SARS-CoV-2 RNA in the peritoneal cavity of patients affected by COVID-19, intraoperatively and postoperatively. KEY WORDS: Covid-19, Laparotomy, Surgery.
OUTPUT:
| Prevention;Transmission | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
0,
0,
1,
0,
0
] |
LitCovid193 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Signal amplification by reversible exchange for COVID-19 antiviral drug candidates. Several drug candidates have been proposed and tested as the latest clinical treatment for coronavirus pneumonia (COVID-19). Chloroquine, hydroxychloroquine, ritonavir/lopinavir, and favipiravir are under trials for the treatment of this disease. The hyperpolarization technique has the ability to further provide a better understanding of the roles of these drugs at the molecular scale and in different applications in the field of nuclear magnetic resonance/magnetic resonance imaging. This technique may provide new opportunities in diagnosis and research of COVID-19. Signal amplification by reversible exchange-based hyperpolarization studies on large-sized drug candidates were carried out. We observed hyperpolarized proton signals from whole structures, due to the unprecedented long-distance polarization transfer by para-hydrogen. We also found that the optimal magnetic field for the maximum polarization transfer yield was dependent on the molecular structure. We can expect further research on the hyperpolarization of other important large molecules, isotope labeling, as well as polarization transfer on nuclei with a long spin relaxation time. A clinical perspective of these features on drug molecules can broaden the application of hyperpolarization techniques for therapeutic studies.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid194 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: The rationale for a multi-step therapeutic approach based on antivirals, drugs and nutrients with immunomodulatory activity in patients with coronavirus-SARS2-induced disease of different severities. In December 2019, a novel human-infecting coronavirus, named Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2), was recognised to cause a pneumonia epidemic outbreak with different degrees of severity in Wuhan, Hubei Province in China. Since then, this epidemic has spread worldwide; in Europe, Italy has been involved. Effective preventive and therapeutic strategies are absolutely required to block this serious public health concern. Unfortunately, few studies about SARS-CoV-2 concerning its immunopathogenesis and treatment are available. On the basis of the assumption that the SARS-CoV-2 is genetically related to SARS-CoV (about 82 % of genome homology) and that its characteristics, like the modality of transmission or the type of the immune response it may stimulate, are still poorly known, a literature search was performed to identify the reports assessing these elements in patients with SARS-CoV-induced infection. Therefore, we have analysed: (1) the structure of SARS-CoV-2 and SARS-CoV; (2) the clinical signs and symptoms and pathogenic mechanisms observed during the development of acute respiratory syndrome and the cytokine release syndrome; (3) the modification of the cell microRNome and of the immune response in patients with SARS infection; and (4) the possible role of some fat-soluble compounds (such as vitamins A, D and E) in modulating directly or indirectly the replication ability of SARS-CoV-2 and host immune response.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid195 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19. The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public health. It is crucial we understand the epidemiological trends and impact of non-pharmacological interventions (NPIs), such as lockdowns for effective management of the disease and control of its spread. We develop and validate a novel intelligent computational model to predict epidemiological trends of COVID-19, with the model parameters enabling an evaluation of the impact of NPIs. By representing the number of daily confirmed cases (NDCC) as a time-series, we assume that, with or without NPIs, the pattern of the pandemic satisfies a series of Gaussian distributions according to the central limit theorem. The underlying pandemic trend is first extracted using a singular spectral analysis (SSA) technique, which decomposes the NDCC time series into the sum of a small number of independent and interpretable components such as a slow varying trend, oscillatory components and structureless noise. We then use a mixture of Gaussian fitting (GF) to derive a novel predictive model for the SSA extracted NDCC incidence trend, with the overall model termed SSA-GF. Our proposed model is shown to accurately predict the NDCC trend, peak daily cases, the length of the pandemic period, the total confirmed cases and the associated dates of the turning points on the cumulated NDCC curve. Further, the three key model parameters, specifically, the amplitude (alpha), mean (mu), and standard deviation (sigma) are linked to the underlying pandemic patterns, and enable a directly interpretable evaluation of the impact of NPIs, such as strict lockdowns and travel restrictions. The predictive model is validated using available data from China and South Korea, and new predictions are made, partially requiring future validation, for the cases of Italy, Spain, the UK and the USA. Comparative results demonstrate that the introduction of consistent control measures across countries can lead to development of similar parametric models, reflected in particular by relative variations in their underlying sigma, alpha and mu values. The paper concludes with a number of open questions and outlines future research directions.
OUTPUT:
| Epidemic Forecasting;Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
1
] |
LitCovid196 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Sequence mismatch in PCR probes may mask the COVID-19 detection in Nepal. *Most of the COVID-19 cases in Nepal are in the Southern districts of Nepal bordering India with travel histories to India.*Very few positive cases of COVID-19 are detected in Nepal which could either be due to early national lockdown.*Low PCR positivity rates could also be due to inefficiency of the PCR methods.*Whole genomes of 93 clinical samples from COVID-19 patients were analyzed to find the primer and probe binding sites.*Mutations in probe binding sites were found which could impact PCR efficiency resulting in false negative results.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid197 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Potential effectiveness and safety of antiviral agents in children with coronavirus disease 2019: a rapid review and meta-analysis. Background: The COVID-19 outbreak presents a new, life-threatening disease. Our aim was to assess the potential effectiveness and safety of antiviral agents for COVID-19 in children. Methods: Electronic databases (MEDLINE, Embase, Web of Science, the Cochrane library, CBM, CNKI, and Wanfang Data) from their inception to March 31, 2020 were searched for randomized controlled trials (RCTs), clinical controlled trials and cohort studies of interventions with antiviral agents for children (less than 18 years of age) with COVID-19. Results: A total of 23 studies with 6,008 patients were included. There was no direct evidence and all of evidence were indirect. The risks of bias in all studies were moderate to high in general. The effectiveness and safety of antiviral agents for children with COVID-19 is uncertain: For adults with COVID-19, lopinavir/ritonavir had no effect on mortality [risk ratio (RR) =0.77; 95% confidence interval (CI), 0.45 to 1.30]. Arbidol and hydroxychloroquine (HCQ) had no benefit on probability of negative PCR test (RR =1.27; 95% CI, 0.93 to 1.73; RR =0.93; 95% CI, 0.73 to 1.18) respectively. For adults with SARS, interferon was associated with reduced corticosteroid dose [weighted mean difference (WMD) = -0.14 g; 95% CI, -0.21 to -0.07] but had no effect on mortality (RR =0.72; 95% CI, 0.28 to 1.88); ribavirin did not reduce mortality (RR =0.68; 95% CI, 0.43 to 1.06) and was associated with high risk of severe adverse reactions; and oseltamivir had no effect on mortality (RR =0.87; 95% CI, 0.55 to 1.38). Ribavirin combined with interferon was also not effective in adults with MERS and associated with adverse reactions. Conclusions: There is no evidence showing the effectiveness of antiviral agents for children with COVID-19, and the clinical efficacy of existing antiviral agents is still uncertain. We do not suggest clinical routine use of antivirals for COVID-19 in children, with the exception of clinical trials.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid198 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Incidental diagnosis of Covid-19 pneumonia on chest computed tomography. PURPOSE: The purpose of this study was to determine the prevalence and imaging characteristics of incidentally diagnosed COVID-19 pneumonia on computed tomography (CT). MATERIALS AND METHODS: This retrospective study was conducted between March 20th and March 31st, 2020 at Cochin hospital, Paris France. Thoracic CT examinations of all patients referred for another reason than a suspicion of SARS-CoV-2 infection were reviewed. CT images were analyzed by a chest radiologist to confirm the presence of findings consistent with COVID-19 pneumonia and quantify disease extent. Clinical and biological data (C-reactive protein serum level [CRP] and white blood cell count) of patients with CT findings suggestive for COVID-19 pneumonia were retrieved from the electronic medical chart. RESULTS: During the study period, among 205 diagnostic CT examinations, six examinations (6/205, 3%) in 6 different patients (4 men, 2 women; median age, 57 years) revealed images highly suggestive of COVID-19 pneumonia. The final diagnosis was confirmed by RT-PCR. Three inpatients were suspected of extra thoracic infection whereas three outpatients were either fully asymptomatic or presented with fatigue only. All had increased CRP serum level and lymphopenia. Disease extent on CT was mild to moderate in 5/6 patients (83%) and severe in 1/6 patient (17%). CONCLUSION: Cumulative incidence of fortuitous diagnosis if COVID-19 pneumonia did not exceed 3% during the highest pandemic phase and was predominantly associated with limited lung involvement.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid199 | ***TASK***
The task is to decide relevant COVID-19 topics of the article based on its abstract.
***INPUT***
The input is an abstract text.
***DOCUMENTATION***
There are 7 topics you will need to decide whether the article is related to. The followings are the topics and their definitions.
Mechanism: underlying cause(s) of COVID-19 infections and transmission and possible drug mechanism of action.
Transmission: characteristics and modes of COVID-19 transmissions.
Diagnosis: COVID-19 assessment through symptoms, test results and radiological features for COVID-19.
Treatment: treatment strategies, therapeutic procedures and vaccine development for COVID-19.
Prevention: prevention, control, mitigation and management strategies for COVID-19.
Case Report: descriptions of specific patient cases related to COVID-19.
Epidemic Forecasting: estimation on the trend of COVID-19 spread and related modeling approach.
***OUTPUT***
The output should be topics from the above 7 topics, that are related to the input article. Please note one article can be related to multiple topics. Output format: provide a semicolon-separated list of relevant topics.
***EXAMPLES***
INPUT: Post myocardial infarction complications during the COVID-19 pandemic - A case series. We report 4 cases of post myocardial infarction complications due to the delay in presentation during COVID-19 era. We highlighted the need for auscultating the chest for early diagnosis. Through this case series, we urge to raise awareness among cardiac patients to access healthcare despite the fear of COVID-19.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |