Instruction datasets for Benchmark
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LitCovid0 | ***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 role for tissue factor in the pathogenesis of hypercoagulability associated with in COVID-19. In December 2019, a new and highly contagious infectious disease emerged in Wuhan, China. The etiologic agent was identified as a novel coronavirus, now known as Severe Acute Syndrome Coronavirus-2 (SARS-CoV-2). Recent research has revealed that virus entry takes place upon the union of the virus S surface protein with the type I transmembrane metallo-carboxypeptidase, angiotensin converting enzyme 2 (ACE-2) identified on epithelial cells of the host respiratory tract. Virus triggers the synthesis and release of pro-inflammatory cytokines, including IL-6 and TNF-alpha and also promotes downregulation of ACE-2, which promotes a concomitant increase in levels of angiotensin II (AT-II). Both TNF-alpha and AT-II have been implicated in promoting overexpression of tissue factor (TF) in platelets and macrophages. Additionally, the generation of antiphospholipid antibodies associated with COVID-19 may also promote an increase in TF. TF may be a critical mediator associated with the development of thrombotic phenomena in COVID-19, and should be a target for future study.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid1 | ***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: Dietary therapy and herbal medicine for COVID-19 prevention: A review and perspective. A novel coronavirus disease (COVID-19), transmitted from humans to humans, has rapidly become the pandemic responsible for the current global health crisis. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is said to be of zoonotic origin. This review describes the etiology and signs and symptoms as well as the current allopathic therapy for COVID-19. Additionally, findings of previous studies on the immunomodulatory effects and antiviral activities of particular foods and herbs on influenza virus and coronaviruses have been collated, with the aim of promoting the use of dietary therapy and herbal medicine as COVID-19 preventive therapies, while specific drugs and vaccines are yet to be discovered or are still under development. The volume of existing reports is irrefutable evidence that foods and herbs possess a potential antiviral ability against SARS-CoV-2 and can prevent COVID-19. Foods and herbs could be used as dietary or complementary therapy to prevent infection and strengthen immunity, as antiviral agents for masks, as disinfectants to curb aerosol transmission, or as sanitizing agents to disinfect surfaces. However, these hypotheses need to be experimentally verified for SARS-CoV-2 and COVID-19 patients.
OUTPUT:
| Treatment;Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
1,
0,
0
] |
LitCovid2 | ***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 report of manic-like symptoms in a COVID-19 patient with no previous history of a psychiatric disorder. BACKGROUND: In December 2019, the novel coronavirus (SARS-CoV-2) infection was first reported in Wuhan city, central China, which has spread rapidly. The common clinical features of patients with SARS-CoV-2 infection included fever, fatigue, and damage to the respiratory or digestive system. However, it is still unclear whether SARS-CoV-2 infection could cause damage to the central nervous system (CNS) inducing psychiatric symptoms. CASE REPORT: Herein, we present the first case of SARS-CoV-2 infection with manic-like symptoms and describe the diagnosis, clinical course, and treatment of the case, focusing on the identifications of SARS-CoV-2 in the specimen of cerebrospinal fluid (CSF). The patient developed manic-like symptoms when his vital signs recovered on illness day 17. After manic-like attack, the detection of SARS-CoV-2 specific IgG antibody in CSF was positive, while the reverse transcriptase-polymerase chain reaction (RT-PCR) on CSF for the SARS-CoV-2 was negative. The patient received Olanzapine for treatment and his mood problems concurrently improved as indicated by scores of Young Manic Rating Scale (YMRS). LIMITATION: This is a single case report only, and the RT-PCR test for SARS-CoV-2 in CSF was not performed simultaneously when SARS-CoV-2 was positive in samples of sputum and stool. CONCLUSION: This first case of COVID-19 patient with manic-like symptoms highlights the importance of evaluation of mental health status and may contribute to our understanding of potential risk of CNS impairments by SARS-CoV-2 infection.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid3 | ***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: Epidemiological Investigation of OHCWs with COVID-19. During the coronavirus disease 2019 (COVID-19) pandemic, there is an important risk of infection in health care workers, including oral health care workers (OHCWs), due to the characteristics of dental practice. In this retrospective study, data pertaining to the 31 OHCWs diagnosed with COVID-19 in Wuhan, Hubei Province, were retrieved and analyzed. Questionnaires were administered to the subjects over the Internet and telephone. Clinical and epidemiological characteristics and information on the use of personal protective equipment (PPE) were collected. There were 22 females and 9 males, with a median age of 39 y. Although the severity of most cases of COVID-19 (93.5%) was mild or moderate, 1 case was severe, and another case was critical, resulting in death. Fever was the main first symptom of COVID-19, followed by fatigue and myalgia. Most of the OHCWs routinely used PPE such as medical masks, gloves, caps, and work clothes while performing clinical work. N95 or KN95 masks were rarely available because of the scarcity of PPE during the outbreak. Nineteen OHCWs reported a contact history, among whom 7 worked in a fever clinic, 5 reported contact with dental patients suspected of having COVID-19, and 7 reported contact with family members with COVID-19-related symptoms at least 1 d earlier. Our findings indicated that there were few clusters of COVID-19 in dental settings. Since the outbreak, the Hospital of Stomatology, Wuhan University, has provided emergency dental treatment, and none of their staff were infected while providing dental service, which indicates that comprehensive measures such as the use of advanced PPE and environmental disinfection can prevent cross-infection in dental practice. The analysis of the procedures followed during the emergency treatments indicated that OHCWs preferred to recommend conservative treatment to patients, suggesting that attention should be paid to the psychological impact of COVID-19 on dental practitioners.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid4 | ***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 sofosbuvir/daclatasvir or ribavirin in patients with severe COVID-19. OBJECTIVES: Sofosbuvir and daclatasvir are direct-acting antivirals highly effective against hepatitis C virus. There is some in silico and in vitro evidence that suggests these agents may also be effective against SARS-CoV-2. This trial evaluated the effectiveness of sofosbuvir in combination with daclatasvir in treating patients with COVID-19. METHODS: Patients with a positive nasopharyngeal swab for SARS-CoV-2 on RT-PCR or bilateral multi-lobar ground-glass opacity on their chest CT and signs of severe COVID-19 were included. Subjects were divided into two arms with one arm receiving ribavirin and the other receiving sofosbuvir/daclatasvir. All participants also received the recommended national standard treatment which, at that time, was lopinavir/ritonavir and single-dose hydroxychloroquine. The primary endpoint was time from starting the medication until discharge from hospital with secondary endpoints of duration of ICU stay and mortality. RESULTS: Sixty-two subjects met the inclusion criteria, with 35 enrolled in the sofosbuvir/daclatasvir arm and 27 in the ribavirin arm. The median duration of stay was 5 days for the sofosbuvir/daclatasvir group and 9 days for the ribavirin group. The mortality in the sofosbuvir/daclatasvir group was 2/35 (6%) and 9/27 (33%) for the ribavirin group. The relative risk of death for patients treated with sofosbuvir/daclatasvir was 0.17 (95% CI 0.04-0.73, P = 0.02) and the number needed to treat for benefit was 3.6 (95% CI 2.1-12.1, P < 0.01). CONCLUSIONS: Given these encouraging initial results, and the current lack of treatments proven to decrease mortality in COVID-19, further investigation in larger-scale trials seems warranted.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid5 | ***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 Coronavirus Disease 2019 Pandemic's Effect on Critical Care Resources and Health-Care Providers: A Global Survey. BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has severely affected ICUs and critical care health-care providers (HCPs) worldwide. RESEARCH QUESTION: How do regional differences and perceived lack of ICU resources affect critical care resource use and the well-being of HCPs? STUDY DESIGN AND METHODS: Between April 23 and May 7, 2020, we electronically administered a 41-question survey to interdisciplinary HCPs caring for patients critically ill with COVID-19. The survey was distributed via critical care societies, research networks, personal contacts, and social media portals. Responses were tabulated according to World Bank region. We performed multivariate log-binomial regression to assess factors associated with three main outcomes: limiting mechanical ventilation (MV), changes in CPR practices, and emotional distress and burnout. RESULTS: We included 2,700 respondents from 77 countries, including physicians (41%), nurses (40%), respiratory therapists (11%), and advanced practice providers (8%). The reported lack of ICU nurses was higher than that of intensivists (32% vs 15%). Limiting MV for patients with COVID-19 was reported by 16% of respondents, was lowest in North America (10%), and was associated with reduced ventilator availability (absolute risk reduction [ARR], 2.10; 95% CI, 1.61-2.74). Overall, 66% of respondents reported changes in CPR practices. Emotional distress or burnout was high across regions (52%, highest in North America) and associated with being female (mechanical ventilation, 1.16; 95% CI, 1.01-1.33), being a nurse (ARR, 1.31; 95% CI, 1.13-1.53), reporting a shortage of ICU nurses (ARR, 1.18; 95% CI, 1.05-1.33), reporting a shortage of powered air-purifying respirators (ARR, 1.30; 95% CI, 1.09-1.55), and experiencing poor communication from supervisors (ARR, 1.30; 95% CI, 1.16-1.46). INTERPRETATION: Our findings demonstrate variability in ICU resource availability and use worldwide. The high prevalence of provider burnout and its association with reported insufficient resources and poor communication from supervisors suggest a need for targeted interventions to support HCPs on the front lines.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid6 | ***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: Accelerated launch of video visits in ambulatory neurology during COVID-19: Key lessons from the Stanford experience. The SARS-CoV-2 (COVID-19) pandemic has rapidly moved telemedicine from discretionary to necessary. Here, we describe how the Stanford Neurology Department (1) rapidly adapted to the COVID-19 pandemic, resulting in over 1,000 video visits within 4 weeks, and (2) accelerated an existing quality improvement plan of a tiered roll out of video visits for ambulatory neurology to a full-scale roll out. Key issues we encountered and addressed were related to equipment/software, provider engagement, workflow/triage, and training. On reflection, the key drivers of our success were provider engagement and dedicated support from a physician champion, who plays a critical role understanding stakeholder needs. Before COVID-19, physician interest in telemedicine was mixed. However, in response to county and state stay-at-home orders related to COVID-19, physician engagement changed completely; all providers wanted to convert a majority of visits to video visits as quickly as possible. Rapid deployment of neurology video visits across all its subspecialties is feasible. Our experience and lessons learned can facilitate broader utilization, acceptance, and normalization of video visits for neurology patients in the present as well as the much anticipated postpandemic era.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid7 | ***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 Epidemic in the Middle Province of Northern Italy: Impact, Logistics, and Strategy in the First Line Hospital. The novel coronavirus (COVID-19) began in China in early December 2019 and rapidly has spread to many countries around the globe, with the number of confirmed cases increasing every day. An epidemic has been recorded since February 20 in a middle province in Northern Italy (Lodi province, in the low Po Valley). The first line hospital had to redesign its logistical and departmental structure to respond to the influx of COVID-19-positive patients who needed hospitalization. Logistical and structural strategies were guided by the crisis unit, managing in 8 days from the beginning of the epidemic to prepare the hospital to be ready to welcome more than 200 COVID-19-positive patients with different ventilatory requirements, keeping clean emergency access lines, and restoring surgical interventions and deferred urgent, routine activity.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid8 | ***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: Cohort of Four Thousand Four Hundred Four Persons Under Investigation for COVID-19 in a New York Hospital and Predictors of ICU Care and Ventilation. Study objective: Most coronavirus disease 2019 (COVID-19) reports have focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients. However, at initial presentation, most patients' viral status is unknown. Determination of factors that predict initial and subsequent need for ICU and invasive mechanical ventilation is critical for resource planning and allocation. We describe our experience with 4,404 persons under investigation and explore predictors of ICU care and invasive mechanical ventilation at a New York COVID-19 epicenter. Methods: We conducted a retrospective cohort study of all persons under investigation and presenting to a large academic medical center emergency department (ED) in New York State with symptoms suggestive of COVID-19. The association between patient predictor variables and SARS-CoV-2 status, ICU admission, invasive mechanical ventilation, and mortality was explored with univariate and multivariate analyses. Results: Between March 12 and April 14, 2020, we treated 4,404 persons under investigation for COVID-19 infection, of whom 68% were discharged home, 29% were admitted to a regular floor, and 3% to an ICU. One thousand six hundred fifty-one of 3,369 patients tested have had SARS-CoV-2-positive results to date. Of patients with regular floor admissions, 13% were subsequently upgraded to the ICU after a median of 62 hours (interquartile range 28 to 106 hours). Fifty patients required invasive mechanical ventilation in the ED, 4 required out-of-hospital invasive mechanical ventilation, and another 167 subsequently required invasive mechanical ventilation in a median of 60 hours (interquartile range 26 to 99) hours after admission. Testing positive for SARS-CoV-2 and lower oxygen saturations were associated with need for ICU and invasive mechanical ventilation, and with death. High respiratory rates were associated with the need for ICU care. Conclusion: Persons under investigation for COVID-19 infection contribute significantly to the health care burden beyond those ruling in for SARS-CoV-2. For every 100 admitted persons under investigation, 9 will require ICU stay, invasive mechanical ventilation, or both on arrival and another 12 within 2 to 3 days of hospital admission, especially persons under investigation with lower oxygen saturations and positive SARS-CoV-2 swab results. This information should help hospitals manage the pandemic efficiently.
OUTPUT:
| Diagnosis;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid9 | ***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 (COVID-19): Experiences and protocols from the Department of Prosthodontics at the Wuhan University. STATEMENT OF PROBLEM: The novel Coronavirus Disease 2019 (COVID-19) is a global pandemic, and many countries and regions are still currently in the midst of the outbreak. This pandemic has caused prosthodontics units to suspend their clinical and educational operations in academia. PURPOSE: The purpose of this article was to review the experiences from the Department of Prosthodontics, Wuhan University School and Hospital of Stomatology (DP-WHUSHS), during the COVID-19 outbreak and the protocols DP-WHUSHS used to resume clinical activities after the outbreak. MATERIAL AND METHODS: The descriptive approach was used in this article to provide a chronological narrative of the experiences and protocols from the DP-WHUSHS during the COVID-19 outbreak and after the outbreak. RESULTS: During the COVID-19 outbreak period, clinical care was provided for patients with dental emergencies by using enhanced grade 2 or grade 3 personal protective equipment (PPE). Teledentistry was used to provide care for patients with nonemergency needs. Online webinars and lectures were conducted for the predoctoral students, residents, and dentists to minimize the interruption in their education and engage the dental community amid the pandemic. Various factors were considered before clinical activities resumed after the outbreak subsided. Additional resources were allocated for facility preparation and management and employee training. New infection control and clinical operation protocols were developed to minimize the health-care-associated infection of airborne transmission diseases. The psychological health and mental wellness of the employees were emphasized. Distance or online education is still under rapid development to provide students and dentists opportunities to advance their knowledge amid the pandemic. CONCLUSIONS: Within the limitation of this descriptive review, the following conclusions were drawn. Patient welfare and emergency needs should be considered amid the pandemic. Enhanced grade 2 or grade 3 PPE should be used during the outbreak. Multifactorial considerations for work resumption after the outbreak included facility preparation and management, training for employees, and clinical operation management. In-person psychological consultation and online mental wellness programs were available to employees to improve their mental wellness. Distance or online education was under rapid development to minimize the interruption in education for the students and to engage the dental community amid a pandemic.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid10 | ***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: Chest CT findings in asymptomatic cases with COVID-19: a systematic review and meta-analysis. AIM: To determine the overall rate of chest imaging findings in asymptomatic cases, describe the most common patterns found, and determine the rate of later symptom development in these initially asymptomatic cases. MATERIALS AND METHODS: The PubMed and EMBASE databases were searched until 1 May 2020, for studies examining the proportion of positive chest imaging findings in asymptomatic cases diagnosed with COVID-19 and a random-effects meta-analysis of proportions was performed. Heterogeneity was assessed using the I(2) statistic. RESULTS: Among 858 non-duplicate studies, seven studies with a total of 231 asymptomatic cases met the inclusion criteria. In the primary analysis, the pooled estimate of the overall rate of positive chest computed tomography (CT) findings among asymptomatic cases was 63% (95% confidence interval [CI]: 44-78%). Among 155/231 cases that were followed up for later symptom development, 90/155 remained asymptomatic and 65/155 developed symptoms during the study period (that ranged between seven and 30 days of follow-up). The pooled estimate of the rate of positive chest CT findings was 62% (95% CI: 38-81%) in cases that remained asymptomatic, while it was 90% (95% CI: 49-99%) in cases that developed symptoms. Among CT findings, the pooled estimate of the overall rate of ground-glass opacities (GGO) at CT alone was 71% (95% CI: 50-86%). Among other CT findings reported, 22/231 patients had GGO with consolidation, 7/231 patients had stripe shadows with or without GGO, and 8/231 patients had GGO with interlobular septal thickening. Among initially asymptomatic cases with positive CT findings, the pooled estimate of the overall rate of later symptom development was 26% (95% CI: 14-43%). CONCLUSION: In COVID-19, asymptomatic cases can have positive chest CT findings, and COVID-19 should be considered among cases with CT abnormalities even when there are no other symptoms. There is a need for close clinical monitoring of asymptomatic cases with radiographic findings as a significant percentage will develop symptoms.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid11 | ***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: Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: A nationwide cohort study. BACKGROUND: There is growing concern that racial and ethnic minority communities around the world are experiencing a disproportionate burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19). We investigated racial and ethnic disparities in patterns of COVID-19 testing (i.e., who received testing and who tested positive) and subsequent mortality in the largest integrated healthcare system in the United States. METHODS AND FINDINGS: This retrospective cohort study included 5,834,543 individuals receiving care in the US Department of Veterans Affairs; most (91%) were men, 74% were non-Hispanic White (White), 19% were non-Hispanic Black (Black), and 7% were Hispanic. We evaluated associations between race/ethnicity and receipt of COVID-19 testing, a positive test result, and 30-day mortality, with multivariable adjustment for a wide range of demographic and clinical characteristics including comorbid conditions, health behaviors, medication history, site of care, and urban versus rural residence. Between February 8 and July 22, 2020, 254,595 individuals were tested for COVID-19, of whom 16,317 tested positive and 1,057 died. Black individuals were more likely to be tested (rate per 1,000 individuals: 60.0, 95% CI 59.6-60.5) than Hispanic (52.7, 95% CI 52.1-53.4) and White individuals (38.6, 95% CI 38.4-38.7). While individuals from minority backgrounds were more likely to test positive (Black versus White: odds ratio [OR] 1.93, 95% CI 1.85-2.01, p < 0.001; Hispanic versus White: OR 1.84, 95% CI 1.74-1.94, p < 0.001), 30-day mortality did not differ by race/ethnicity (Black versus White: OR 0.97, 95% CI 0.80-1.17, p = 0.74; Hispanic versus White: OR 0.99, 95% CI 0.73-1.34, p = 0.94). The disparity between Black and White individuals in testing positive for COVID-19 was stronger in the Midwest (OR 2.66, 95% CI 2.41-2.95, p < 0.001) than the West (OR 1.24, 95% CI 1.11-1.39, p < 0.001). The disparity in testing positive for COVID-19 between Hispanic and White individuals was consistent across region, calendar time, and outbreak pattern. Study limitations include underrepresentation of women and a lack of detailed information on social determinants of health. CONCLUSIONS: In this nationwide study, we found that Black and Hispanic individuals are experiencing an excess burden of SARS-CoV-2 infection not entirely explained by underlying medical conditions or where they live or receive care. There is an urgent need to proactively tailor strategies to contain and prevent further outbreaks in racial and ethnic minority communities.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid12 | ***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: Profile of natural anticoagulant, coagulant factor and anti-phospholipid antibody in critically ill COVID-19 patients. The outbreak of novel coronavirus disease 2019 (COVID-19) has now become a global pandemic. Coagulopathy has been reported widely in critically ill COVID-19 patients and was related to high mortality. However, the comprehensive coagulation profiles have not been examined and the underlying mechanism of the coagulopathy in COVID-19 patients is unclear. To study the coagulation profiles of routine hemostasis tests, natural anticoagulants, coagulant factors and antiphospholipid antibodies in critically ill COVID-19 patients. This single-center and cross-section study included 19 patients with COVID-19, who were admitted to intensive care unit (ICU) at Tongji hospital in Wuhan, China, from Feb 23 to Mar 3, 2020. Demographic data, laboratory parameters, treatments and clinical outcomes of the patients were collected and analyzed. The final date of follow-up was Mar 31, 2020. In this study, 12 thrombotic events occurred in 9 patients, including 4 cerebral infarctions, 7 acro-ischemia and 1 internal jugular vein thrombosis. The common abnormalities of routine coagulation tests included evelated D-Dimer level (100%), prolonged prothrombin time (73.7%) and hyperfibrinogenemia (73.7%). The median activities of natural anticoagulants including protein C, protein S and antithrombin were all below the normal range. Factor VIII activities were significantly above normal range (median value 307%, IQR 198-441) in all patients. Factor V and factor VII activities were significantly lower in near-terminal stage patients. Anti-phospholipid antibodies were present in 10 patients. Strikingly, 4 cerebral infarction events were in patients had anti-phospholipid antibodies of multiple isotypes. Sustained hypercoagulable status and thrombotic events were common in critically ill patients with COVID-19. The low activities of natural anticoagulants, elevated factor VIII level and the presence of antiphospholipid antibodies, together, may contribute to the etiopathology of coagulopathy in COVID-19 patients.
OUTPUT:
| Treatment;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid13 | ***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 snapshot of the Covid-19 pandemic among pregnant women in France. OBJECTIVE: To describe the course over time of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in French women from the beginning of the pandemic until mid-April, the risk profile of women with respiratory complications, and short-term pregnancy outcomes. METHODS: We collected a case series of pregnant women with COVID-19 in a research network of 33 French maternity units between March 1 and April 14, 2020. All cases of SARS-CoV-2 infection confirmed by a positive result on real-time reverse transcriptase polymerase chain reaction tests of a nasal sample and/or diagnosed by a computed tomography chest scan were included and analyzed. The primary outcome measures were COVID-19 requiring oxygen (oxygen therapy or noninvasive ventilation) and critical COVID-19 (requiring invasive mechanical ventilation or extracorporeal membrane oxygenation, ECMO). Demographic data, baseline comorbidities, and pregnancy outcomes were also collected. RESULTS: Active cases of COVID-19 increased exponentially during March 1-31, 2020; the numbers fell during April 1-14, after lockdown was imposed on March 17. The shape of the curve of active critical COVID-19 mirrored that of all active cases. By April 14, among the 617 pregnant women with COVID-19, 93 women (15.1 %; 95 %CI 12.3-18.1) had required oxygen therapy and 35 others (5.7 %; 95 %CI 4.0-7.8) had had a critical form of COVID-19. The severity of the disease was associated with age older than 35 years and obesity, as well as preexisting diabetes, previous preeclampsia, and gestational hypertension or preeclampsia. One woman with critical COVID-19 died (0.2 %; 95 %CI 0-0.9). Among the women who gave birth, rates of preterm birth in women with non-severe, oxygen-requiring, and critical COVID-19 were 13/123 (10.6 %), 14/29 (48.3 %), and 23/29 (79.3 %) before 37 weeks and 3/123 (2.4 %), 4/29 (13.8 %), and 14/29 (48.3 %) before 32 weeks, respectively. One neonate (0.5 %; 95 %CI 0.01-2.9) in the critical group died from prematurity. CONCLUSION: COVID-19 can be responsible for significant rates of severe acute, potentially deadly, respiratory distress syndromes. The most vulnerable pregnant women, those with comorbidities, may benefit particularly from prevention measures such as a lockdown.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid14 | ***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: Magnetic Microdevices for MRI-Based Detection of SARS-CoV-2 Viruses. Goal: To develop a micron-scale device that can operate as an MRI-based reporter for the presence of SARS-CoV-2 virus. Methods: Iron rod microdevices were constructed via template-guided synthesis and suspended in phosphate buffered saline (PBS). Heat-inactivated SARS-CoV-2 viruses were added to the samples and imaged with low-field MRI. Results: MRI of microdevices and viruses showed decreased signal intensity at low concentrations of viruses that recovered at higher concentrations. Electron micrographs suggest that reduced MRI intensity may be due to concentration-dependent shielding of water protons from local magnetic inhomogeneities caused by the iron microdevices. Conclusions: The preliminary results presented in this letter provide justification for further studies exploring the potential diagnostic role of magnetic microdevices in assessing the presence and concentration of SARS-CoV-2 viruses.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid15 | ***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: How Much Do Young Italians Know About COVID-19 and What Are Their Attitudes Toward SARS-CoV-2? Results of a Cross-Sectional Study. OBJECTIVES: At the end of 2019, an outbreak of novel coronavirus pneumonia, called severe acute respiratory syndrome coronavirus 1 (SARS-CoV-2), was first identified in Wuhan, Hubei Province, China. It subsequently spread throughout China and elsewhere, becoming a global health emergency. In February 2020, the World Health Organization (WHO) designated the disease coronavirus disease 2019 (COVID-19). The objective of this study was to investigate the degree of knowledge of young Italians about COVID-19 and their current attitudes toward the SARS-CoV-2 and to determine if there were prejudices emerging toward Chinese. METHODS: An online survey was conducted on February 3, 4, 5, 2020, with the collaboration of Italian website "Skuola.net". Young people had the opportunity to participate by answering an ad hoc questionnaire created to investigate knowledge and attitudes about the new coronavirus, using a link published on the homepage. RESULTS: A total of 5234 responses were received, of which 3262 were females and 1972 were males. Most of the participants showed generally moderate knowledge about COVID-19. Male students, middle school students, and those who do not attend school, should increase awareness of the disease; less than half of responders say that their attitudes toward the Chinese population has worsened in the last period. CONCLUSIONS: Global awareness of this emerging infection should be increased, due to its virulence, the significant risk of mortality, and the ability of the virus to spread very quickly within the community.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid16 | ***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: Effect of transfusion convalescent recovery plasma in patients with coronavirus disease 2019. OBJECTIVES: To evaluate curative effects of coronavirus disease 2019 (COVID-19) patients by the transfusion of other convalescent plasma. METHODS: Retrospective analysis of the clinical data of 18 patients with severe and critical COVID-19, who were hospitalized in the ICU of Xianghu Branch of the First Affiliated Hospital of Nanchang University from February 1 to March 15, 2020. Patients were subdivided into an experimental group (n=6, who had transfused the plasma) and an observation group (n=12, who had no plasma transfusion). Basic clinical data and prognosis indexes of these two groups were compared. Moreover, for the experimental group, the dynamic changes of blood oxygen saturation before and after the transfusion, the changes of lymphocyte absolute value 48 hours after the transfusion, and the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid were analyzed. RESULTS: There were no significant differences in age, gender, blood type and other basic clinical data between the two groups (all P>0.05).There were no significant differences in ventilator machine weaning time, extracorporeal membrane oxygenation (ECMO) weaning time, body temperature recovery to normal time, and hospitalization days between these two groups (all P>0.05). For the experimental group, before, during and after the convalescent plasma transfusion, the blood oxygen saturation of all 6 patients at all time (1, 6, 8, 12, 24, 36, and 48 h) was more than 90%, and there was no significant fluctuation. There were 3 patients whose absolute value of lymphocyte was increased 48 hours after the transfusion, and the remaining was decreased. There were 5 patients whose SARS-CoV-2 nucleic acid detection turned negative 48 hours after the transfusion, accounting for 83.3%. CONCLUSIONS: Transfusion of convalescent plasma will not affect outcomesof COVID-19 patients, which can neutralize SARS-CoV-2 in patients and reduce the loading capacity of SARS-CoV-2.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid17 | ***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 Outbreak in Wuhan, China, 2020: Intense Surveillance Is Vital for Preventing Sustained Transmission in New Locations. The outbreak of pneumonia originating in Wuhan, China, has generated 24,500 confirmed cases, including 492 deaths, as of 5 February 2020. The virus (2019-nCoV) has spread elsewhere in China and to 24 countries, including South Korea, Thailand, Japan and USA. Fortunately, there has only been limited human-to-human transmission outside of China. Here, we assess the risk of sustained transmission whenever the coronavirus arrives in other countries. Data describing the times from symptom onset to hospitalisation for 47 patients infected early in the current outbreak are used to generate an estimate for the probability that an imported case is followed by sustained human-to-human transmission. Under the assumptions that the imported case is representative of the patients in China, and that the 2019-nCoV is similarly transmissible to the SARS coronavirus, the probability that an imported case is followed by sustained human-to-human transmission is 0.41 (credible interval [0.27, 0.55]). However, if the mean time from symptom onset to hospitalisation can be halved by intense surveillance, then the probability that an imported case leads to sustained transmission is only 0.012 (credible interval [0, 0.099]). This emphasises the importance of current surveillance efforts in countries around the world, to ensure that the ongoing outbreak will not become a global pandemic.
OUTPUT:
| Transmission;Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
0,
0,
1,
0,
0
] |
LitCovid18 | ***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: Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020. Since December 2019, China has been experiencing a large outbreak of a novel coronavirus (2019-nCoV) which can cause respiratory disease and severe pneumonia. We estimated the basic reproduction number R0 of 2019-nCoV to be around 2.2 (90% high density interval: 1.4-3.8), indicating the potential for sustained human-to-human transmission. Transmission characteristics appear to be of similar magnitude to severe acute respiratory syndrome-related coronavirus (SARS-CoV) and pandemic influenza, indicating a risk of global spread.
OUTPUT:
| Transmission | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
0,
0,
0,
0,
0
] |
LitCovid19 | ***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: Telemedicine: a Bridge Over Knowledge Gaps in Healthcare. Purpose of the Review: The purpose of the review is to describe the Brazilian Telemedicine University Network RUTE concerning the Special Interest Group of Children and Adolescents, the new SIG-COVID19-BR activities for continuing medical education, and to update relevant information regarding diagnosis and treatment, using digital technologies. Recent Findings: A total of 145 sessions of video and webconferences were held with the participation of 6575 health professionals, including medical students, interns, and residents. Major topics involved the healthcare of children and adolescents were combined with the emergence of a new pandemic plus the need to decrease the professional knowledge gaps in geographically distant hospitals. Summary: Telemedicine is a cost-effective tool and a bridge to decrease health disparities access for proper care and assistance for any population. RUTE is a Brazilian model of telemedicine which has a positive impact attracting the participation of health professionals, and even more so, during the Covid-19 virus pandemic outbreak.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid20 | ***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 and prospects of COVID-19 vaccine development based on the progress made in SARS and MERS vaccine development. The outbreak of coronavirus disease 2019 (COVID-19) as a pandemic has shaken the global health system and economy by their roots. This epidemic is still spreading and showing no signs of decreasing trend. Vaccination could be the only effective and economical means to control this pandemic. A number of research institutions and pharmaceutical companies have plunged into the race of vaccine development against COVID-19 which are in various stages of development. An intriguing fact of coronavirus infections is that in every decade of the 21st century there is a new major coronavirus epidemic, namely, severe acute respiratory syndrome (SARS) in 2002, Middle East respiratory syndrome (MERS) in 2012, and now COVID-19; and such epidemics are expected in future too. Since most of the biological characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are still obscure, the scientists are relying on the information available on SARS-CoV and to some extent on MERS-CoV for designing and developing COVID-19 vaccines. But there is a need of vigorous testing for immunogenicity, safety, efficacy, and level of protection conferred in the hosts. This review focuses on the challenges and prospects of vaccine development against COVID-19. It highlights seriousness, bottlenecks in vaccine development, possible vaccine candidates, different vaccine strategies, safety evaluation issues, and vaccine production processes pertaining to COVID-19 based on the knowledge acquired on SARS and MERS vaccine development in the past.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid21 | ***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 Geroscience Perspective on COVID-19 Mortality. A novel coronavirus, SARS-CoV-2, emerged in December 2019, leading within a few months to a global pandemic. COVID-19, the disease caused by this highly contagious virus, can have serious health consequences, though risks of complications are highly age-dependent. Rates of hospitalization and death are less than 0.1% in children, but increase to 10% or more in older people. Moreover, at all ages, men are more likely than women to suffer serious consequences from COVID-19. These patterns are familiar to the geroscience community. The effects of age and sex on mortality rates from COVID-19 mirror the effects of aging on almost all major causes of mortality. These similarities are explored here, and underscore the need to consider the role of basic biological mechanisms of aging on potential treatment and outcomes of COVID-19.
OUTPUT:
| Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
0,
0,
0,
0
] |
LitCovid22 | ***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: Inactivating Three Interferon Antagonists Attenuates Pathogenesis of an Enteric Coronavirus. Coronaviruses (CoVs) have repeatedly emerged from wildlife hosts and infected humans and livestock animals to cause epidemics with significant morbidity and mortality. CoVs infect various organs, including respiratory and enteric systems, as exemplified by newly emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The constellation of viral factors that contribute to developing enteric disease remains elusive. Here, we investigated CoV interferon antagonists for their contribution to enteric pathogenesis. Using an infectious clone of an enteric CoV, porcine epidemic diarrhea virus (icPEDV), we generated viruses with inactive versions of interferon antagonist nonstructural protein 1 (nsp1), nsp15, and nsp16 individually or combined into one virus designated icPEDV-mut4. Interferon-responsive PK1 cells were infected with these viruses and produced higher levels of interferon responses than were seen with wild-type icPEDV infection. icPEDV-mut4 elicited robust interferon responses and was severely impaired for replication in PK1 cells. To evaluate viral pathogenesis, piglets were infected with either icPEDV or icPEDV-mut4. While the icPEDV-infected piglets exhibited clinical disease, the icPEDV-mut4-infected piglets showed no clinical symptoms and exhibited normal intestinal pathology at day 2 postinfection. icPEDV-mut4 replicated in the intestinal tract, as revealed by detection of viral RNA in fecal swabs, with sequence analysis documenting genetic stability of the input strain. Importantly, icPEDV-mut4 infection elicited IgG and neutralizing antibody responses to PEDV. These results identify nsp1, nsp15, and nsp16 as virulence factors that contribute to the development of PEDV-induced diarrhea in swine. Inactivation of these CoV interferon antagonists is a rational approach for generating candidate vaccines to prevent disease and spread of enteric CoVs, including SARS-CoV-2.IMPORTANCE Emerging coronaviruses, including SARS-CoV-2 and porcine CoVs, can infect enterocytes, cause diarrhea, and be shed in the feces. New approaches are needed to understand enteric pathogenesis and to develop vaccines and therapeutics to prevent the spread of these viruses. Here, we exploited a reverse genetic system for an enteric CoV, porcine epidemic diarrhea virus (PEDV), and outline an approach of genetically inactivating highly conserved viral factors known to limit the host innate immune response to infection. Our report reveals that generating PEDV with inactive versions of three viral interferon antagonists, nonstructural proteins 1, 15, and 16, results in a highly attenuated virus that does not cause diarrhea in animals and elicits a neutralizing antibody response in virus-infected animals. This strategy may be useful for generating live attenuated vaccine candidates that prevent disease and fecal spread of enteric CoVs, including SARS-CoV-2.
OUTPUT:
| Mechanism;Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid23 | ***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 Encephalitis in a 20-year old Healthy Female. We report a 20-year-old female with SARS-CoV-2 encephalitis who presented with 4 days of upper respiratory symptoms, fevers and sudden acute altered mental status. An extensive work up led to the most likely cause for the neurologic decompensation to be viewed as SARS-CoV-2 symptomology.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid24 | ***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: Screening for obstructive sleep apnea with novel hybrid acoustic smartphone app technology. Background: Obstructive sleep apnea (OSA) has a high prevalence, with an estimated 425 million adults with apnea hypopnea index (AHI) of >/=15 events/hour, and is significantly underdiagnosed. This presents a significant pain point for both the sufferers, and for healthcare systems, particularly in a post COVID-19 pandemic world. As such, it presents an opportunity for new technologies that can enable screening in both developing and developed countries. In this work, the performance of a non-contact OSA screener App that can run on both Apple and Android smartphones is presented. Methods: The subtle breathing patterns of a person in bed can be measured via a smartphone using the "Firefly" app technology platform [and underpinning software development kit (SDK)], which utilizes advanced digital signal processing (DSP) technology and artificial intelligence (AI) algorithms to identify detailed sleep stages, respiration rate, snoring, and OSA patterns. The smartphone is simply placed adjacent to the subject, such as on a bedside table, night stand or shelf, during the sleep session. The system was trained on a set of 128 overnights recorded at a sleep laboratory, where volunteers underwent simultaneous full polysomnography (PSG), and "Firefly" smartphone app analysis. A separate independent test set of 120 recordings was collected across a range of Apple iOS and Android smartphones, and withheld for performance evaluation by a different team. An operating point tuned for mid-sensitivity (i.e., balancing sensitivity and specificity) was chosen for the screener. Results: The performance on the test set is comparable to ambulatory OSA screeners, and other smartphone screening apps, with a sensitivity of 88.3% and specificity of 80.0% [with receiver operating characteristic (ROC) area under the curve (AUC) of 0.92], for a clinical threshold for the AHI of >/=15 events/hour of detected sleep time. Conclusions: The "Firefly" app based sensing technology offers the potential to significantly lower the barrier of entry to OSA screening, as no hardware (other than the user's personal smartphone) is required. Additionally, multi-night analysis is possible in the home environment, without requiring the wearing of a portable PSG or other home sleep test (HST).
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid25 | ***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: Stress proteins: the biological functions in virus infection, present and challenges for target-based antiviral drug development. Stress proteins (SPs) including heat-shock proteins (HSPs), RNA chaperones, and ER associated stress proteins are molecular chaperones essential for cellular homeostasis. The major functions of HSPs include chaperoning misfolded or unfolded polypeptides, protecting cells from toxic stress, and presenting immune and inflammatory cytokines. Regarded as a double-edged sword, HSPs also cooperate with numerous viruses and cancer cells to promote their survival. RNA chaperones are a group of heterogeneous nuclear ribonucleoproteins (hnRNPs), which are essential factors for manipulating both the functions and metabolisms of pre-mRNAs/hnRNAs transcribed by RNA polymerase II. hnRNPs involve in a large number of cellular processes, including chromatin remodelling, transcription regulation, RNP assembly and stabilization, RNA export, virus replication, histone-like nucleoid structuring, and even intracellular immunity. Dysregulation of stress proteins is associated with many human diseases including human cancer, cardiovascular diseases, neurodegenerative diseases (e.g., Parkinson's diseases, Alzheimer disease), stroke and infectious diseases. In this review, we summarized the biologic function of stress proteins, and current progress on their mechanisms related to virus reproduction and diseases caused by virus infections. As SPs also attract a great interest as potential antiviral targets (e.g., COVID-19), we also discuss the present progress and challenges in this area of HSP-based drug development, as well as with compounds already under clinical evaluation.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid26 | ***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: Estimates of serial interval for COVID-19: A systematic review and meta-analysis. Background: On 11(th) March 2020, the World Health Organization declared COVID-19 as Pandemic. The estimation of transmission dynamics in the initial days of the outbreak of any infectious disease is crucial to control its spread in a new area. The serial interval is one of the significant epidemiological measures that determine the spread of infectious disease. It is the time interval between the onset of symptoms in the primary and secondary case. Objective: The present study aimed at the qualitative and quantitative synthesis of the currently available evidence for the serial interval of COVID-19. Methodology: Data on serial intervals were extracted from 11 studies following a systematic review. A meta-analysis was performed to estimate the pooled estimate of the serial interval. The heterogeneity and bias in the included studies were tested by various statistical measures and tests, including I(2) statistic, Cochran's Q test, Egger's test, and Beggs's test. Result: The pooled estimate for the serial interval was 5.40 (5.19, 5.61) and 5.19 (4.37, 6.02) days by the fixed and random effects model, respectively. The heterogeneity between the studies was found to be 89.9% by I(2) statistic. There is no potential bias introduced in the meta-analysis due to small study effects. Conclusion: The present review provides sufficient evidence for the estimate of serial interval of COVID-19, which can help in understanding the epidemiology and transmission of the disease. The information on serial interval can be useful in developing various policies regarding contact tracing and monitoring community transmission of COVID-19.
OUTPUT:
| Transmission;Epidemic Forecasting;Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
0,
0,
1,
0,
1
] |
LitCovid27 | ***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: Direct Comparison of SARS-CoV-2 Analytical Limits of Detection across Seven Molecular Assays. Analytical sensitivity for SARS-CoV-2 detection is a key performance metric for the evaluation of viral detection assays. We determined analytical limits of detection for seven SARS-CoV-2 assays using serial dilutions of pooled patient material quantified with droplet digital PCR. Limits of detection ranged from </=10 to 74 copies/ml for commercial high-throughput laboratory analyzers (Roche Cobas, Abbott m2000, and Hologic Panther Fusion) and 167 to 511 copies/ml for sample-to-answer (DiaSorin Simplexa, GenMark ePlex) and point-of-care instruments (Abbott ID NOW). The CDC assay yielded limits of detection ranging from 85 to 499 copies/ml, depending on the extraction method and thermocycler used. These results can help to inform the assay choice for testing approaches to manage the current COVID-19 outbreak.
OUTPUT:
| Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
0,
0,
0
] |
LitCovid28 | ***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: Rehabilitation of a Post-Intensive Care Unit Patient After Severe COVID-19 Pneumonia. The recent novel severe acute respiratory syndrome coronavirus 2 infection resulted in a coronavirus disease 2019 pandemic that significantly strained healthcare systems globally. The early wave of patients in Singapore with severe pneumonia requiring intensive care units are gradually being referred for post-critical illness management with our inpatient medical rehabilitation unit. There is growing information regarding the actual rehabilitation process for patients severely affected by coronavirus disease 2019. This case report shares experiences and challenges faced during rehabilitation of severe coronavirus disease 2019 pneumonia and post-intensive care syndrome. It also describes the post-discharge rehabilitation program in a setting of strict nationwide safe distancing and stay-home policies.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid29 | ***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: Placental Pathology Findings during and after SARS-CoV-2 Infection: Features of Villitis and Malperfusion. Since the outbreak of coronavirus disease 2019 (COVID-19), there has been a debate whether pregnant women are at a specific risk for COVID-19 and whether it might be vertically transmittable through the placenta. We present a series of five placentas of SARS coronavirus 2 (SARS-CoV-2)-positive women who had been diagnosed with mild symptoms of COVID-19 or had been asymptomatic before birth. We provide a detailed histopathologic description of morphological changes accompanied by an analysis of presence of SARS-CoV-2 in the placental tissue. All placentas were term deliveries (40th and 41st gestational weeks). One SARS-CoV-2-positive patient presented with cough and dyspnoea. This placenta showed prominent lymphohistiocytic villitis and intervillositis and signs of maternal and foetal malperfusion. Viral RNA was present in both placenta tissue and the umbilical cord and could be visualized by in situ hybridization in the decidua. SARS-CoV-2 tests were negative at the time of delivery of 3/5 women, and their placentas did not show increased inflammatory infiltrates. Signs of maternal and/or foetal malperfusion were present in 100% and 40% of cases, respectively. There was no transplacental transmission to the infants. In our cohort, we can document different time points regarding SARS-CoV-2 infection. In acute COVID-19, prominent lymphohistiocytic villitis may occur and might potentially be attributable to SARS-CoV-2 infection of the placenta. Furthermore, there are histopathological signs of maternal and foetal malperfusion, which might have a relationship to an altered coagulative or microangiopathic state induced by SARS-CoV-2, yet this cannot be proven considering a plethora of confounding factors.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid30 | ***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: Prognostic value of interleukin-18 and its association with other inflammatory markers and disease severity in COVID-19. BACKGROUND: The effectual immune response is crucial to defeat viral infections. However, exuberant immune response with features of macrophage activation syndrome (MAS) lead detrimental consequences in COVID-19 patients. Interleukin (IL)-18 is one of the leading cytokines in MAS which has not been studied in COVID-19. OBJECTIVE: To investigate the association of IL-18 with the other inflammatory markers and disease severity in COVID-19 for predicting disease prognosis. METHODS: Patients with COVID-19 who had confirmed diagnosis with SARS-CoV-2 nucleic acid RT-PCR were enrolled into the study. Data on demographic and clinical characteristics, and laboratory values of CRP, ferritin, d-dimer and procalcitonin were measured on admission. Patients were followed up prospectively with a standardized approach until hospital discharge or death. Individuals were classified as asymptomatic, mild and severe pneumonia according to their clinical, laboratory and radiological characteristics. Worse outcome was defined as requirement of intensive care unit (ICU) admission or death. Blood samples were collected at enrollment and serum levels of IL-6 and IL-18 were determined by ELISA. Association between IL-18 and other inflammatory markers and prognosis were analyzed. RESULTS: There were 58 COVID-19 patients (50% male) with a median age of 43 (min 22-max 81) years. Twenty age and sex matched healthy subjects were served as control group. The study population was divided into three groups according to disease severity: asymptomatic (n = 20), mild pneumonia group (n = 27) and a severe group (n = 11). During follow up nine (15.5%) patients required ICU admission and three of them were died eventually. Serum IL-18 were correlated with other inflammatory markers and biochemical markers of organ injury; creatinine, liver enzymes and troponin. Serum IL-18 levels were remarkably higher in COVID-19 patients compared to healthy subjects with being highest in severe pneumonia group (p < 0.001). IL-18 serum concentrations were almost four-fold higher in patients with worse outcome compared to good outcome (p < 0.001). Serum IL-18 above the cut off value of 576 pg/mL on admission was associated with 11.7 fold increased risk of ICU admission. CONCLUSIONS: The serum concentrations of IL-18 correlate with other inflammatory markers and reflect disease severity. Results of the present study shed light on role of IL-18 on COVID-19 pathogenesis and might provide an evidence for the clinical trials on IL-18 antagonists for the treatment of severe COVID-19 patients.
OUTPUT:
| Treatment;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
1,
0,
0,
0
] |
LitCovid31 | ***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: Non-COVID Diseases during the Pandemic: Where Have All Other Emergencies Gone? Background and objectives: the emergency department (ED) is frequently identified by patients as a possible solution for all healthcare problems, leading to a high rate of misuse of the ED, possibly causing overcrowding. The coronavirus disease 2019 (COVID-19) pandemic started in China; it then spread throughout Italy, with the first cases confirmed in Lombardy, Italy, in February 2020. This has totally changed the type of patients referred to EDs. The aim of this study was to analyze the reduction of ED admissions at a Second level urban teaching (Fondazione Policlinico Universitario Agostino Gemelli IRCCS) during the COVID-19 pandemic. Materials and Methods: in this retrospective observational cross-sectional study, we reviewed and compared clinical records of all the patients consecutively admitted to our ED over a 40-day period (21 February -31 March) in the last three years (2018-2019-2020). Mean age, sex, triage urgency level, day/night admission, main presentation symptom, and final diagnosis, according to different medical specialties, hospitalization, and discharge rate, were analyzed. Results: we analyzed 16,281 patient clinical records. The overall reduction in ED admissions in 2020 was 37.6% compared to 2019. In 2020, we observed an increase in triage urgency levels for ED admissions (the main presentation symptom was a fever). We noticed a significant drop in admissions for cardio-thoracic, gastroenterological, urological, otolaryngologic/ophthalmologic, and traumatological diseases. Acute neurological conditions registered only a slight, but significant, reduction. Oncology admissions were stable. Admissions for infectious diseases were 30% in 2020, compared to 5% and 6% in 2018 and 2019, respectively. In 2020, the hospitalization rate increased to 42.9% compared to 27.7%, and 26.4% in previous years. Conclusions: the drastic reduction of ED admissions during the pandemic may be associated with fear of the virus, suggesting that patients with serious illnesses did not go to the emergency room. Moreover, there was possible misuse of the ED in the previous year. In particular, worrisome data emerged regarding a drop in cardiology and neurology admissions. Those patients postponed medical attention, possibly with fatal consequences, just for fear of exposure to COVID-19, leading to unnecessary morbidity and mortality.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid32 | ***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: Aerosol generating procedures in orthopaedics and recommended protective gear. The prime of COVID-19 forced institutions and hospitals to convert operating rooms into intensive care units. Now as the disease prevalence drops and plateaus in several countries, elective surgeries are being slowly resuming. Such that asymptomatic carriers too would approach hospitals for surgical needs. Coronaviruses are understood to transmit both by droplets and aerosols. Orthopaedic surgery requires regular use of high-speed instruments like power drills, oscillating saws and burrs. Several medical procedures are known to create aerosols thereby exposing the surgeon to contract the virus. Adequate know-how and protective means are mandatory to safeguard the surgical team from inevitable exposure.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid33 | ***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: Dataset for country profile and mobility analysis in the assessment of COVID-19 pandemic. Understanding the COVID-19 pandemic is a multidisciplinary effort that requires a significant number of variables. This dataset comprises (i) sociodemographic characteristics, compiled from 35 datasets obtained at UN Data; (ii) mobility metrics that can assist the analysis of social distancing, from Google Community Mobility Reports and; (iii) daily counts of cases and deaths by COVID-19, from the European Centre for Disease Prevention and Control and the Johns Hopkins University Center for Systems Science and Engineering. This unified dataset ranges from February 15, 2020 to May 7, 2020, a total of 83 days, and is provided as a collection of time series for 131 countries with 192 variables. The pipeline to preprocess and generate the dataset, along with the dataset itself, are versioned with the Data Version Control tool (DVC) and are thus easily reproducible.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid34 | ***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 - Important considerations for developing and using a vaccine. The novel coronavirus SARS-CoV-2 after emerging in China has caused a global pandemic that is risking the lives of millions. COVID-19 has spread across the world at a very rapid rate raising concerns of capacity limitations and lack of unified responses at the global level, particularly from the world's most developed countries. The spread of further infection has been curtailed by lockdown and mass social distancing that has been enforced in most parts of the world. There are no clinical data yet suggesting that any available candidate vaccine will be effective for COVID-19 which will be a critical need for eventually preventing this disease. Extensive research is underway with some success in identification of monoclonal antibodies from COVID-19 recovered patients, which may inform on vaccine development. The clinical evaluations of COVID-19 vaccines need to follow standardized protocols that are essential for safeguarding humans. In absence of a vaccine or a widely available effective therapy, quarantine and other preventive measures are essential in curtailing the risk of pandemic spread.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid35 | ***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: Current Scenario and Future Prospect in the Management of COVID-19. The COVID-19 pandemic continues to wreak havoc worldwide due to the lack of risk assessment, rapid spreading ability, and propensity to precipitate severe disease in comorbid conditions. In an attempt to fulfill the demand for prophylactic and treatment measures to intercept the ongoing outbreak, the drug development process is facing several obstacles and renaissance in clinical trials, including vaccines, antivirals, immunomodulators, plasma therapy, and traditional medicines. This review outlines the overview of SARS-CoV-2 infection, significant recent findings, and ongoing clinical trials concerning current and future therapeutic interventions for the management of advancing pandemic of the century.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid36 | ***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: Seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection among Veterans Affairs healthcare system employees suggests higher risk of infection when exposed to SARS-CoV-2 outside the work environment. OBJECTIVE: The seroprevalence of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) IgG antibody was evaluated among employees of a Veterans Affairs healthcare system to assess potential risk factors for transmission and infection. METHODS: All employees were invited to participate in a questionnaire and serological survey to detect antibodies to SARS-CoV-2 as part of a facility-wide quality improvement and infection prevention initiative regardless of clinical or nonclinical duties. The initiative was conducted from June 8 to July 8, 2020. RESULTS: Of the 2,900 employees, 51% participated in the study, revealing a positive SARS-CoV-2 seroprevalence of 4.9% (72 of 1,476; 95% CI, 3.8%-6.1%). There were no statistically significant differences in the presence of antibody based on gender, age, frontline worker status, job title, performance of aerosol-generating procedures, or exposure to known patients with coronavirus infectious disease 2019 (COVID-19) within the hospital. Employees who reported exposure to a known COVID-19 case outside work had a significantly higher seroprevalence at 14.8% (23 of 155) compared to those who did not 3.7% (48 of 1,296; OR, 4.53; 95% CI, 2.67-7.68; P < .0001). Notably, 29% of seropositive employees reported no history of symptoms for SARS-CoV-2 infection. CONCLUSIONS: The seroprevalence of SARS-CoV-2 among employees was not significantly different among those who provided direct patient care and those who did not, suggesting that facility-wide infection control measures were effective. Employees who reported direct personal contact with COVID-19-positive persons outside work were more likely to have SARS-CoV-2 antibodies. Employee exposure to SARS-CoV-2 outside work may introduce infection into hospitals.
OUTPUT:
| Prevention;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
1,
0,
0
] |
LitCovid37 | ***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 Method of Assessing Clinical Preparedness for COVID-19 and Other Disasters. QUALITY ISSUE: The emergence of COVID-19 highlights the necessity of rapidly identifying and isolating potentially infected individuals. Evaluating this preparedness requires an assessment of the full clinical system, from intake to isolation. INITIAL ASSESSMENT: Unannounced Standardized Patients (USPs) present a nimble, sensitive methodology for assessing this readiness. CHOICE OF SOLUTION: Pilot the Unannounced Standardized Patient methodology, which employs an actor trained to present as a standardized, incognito potentially infected patient, to assess clinical readiness for potential COVID-19 patients at an urban, community safety-net clinic. IMPLEMENTATION: The Unannounced Standardized Patient was trained to present at each team's front desk with the complaint of feeling unwell (reporting a fever of 101 degrees Fahrenheit in the past 24 hours) and exposure to a roommate recently returned from Beijing. The Unannounced Standardized Patient was trained to complete a behaviorally-anchored assessment of the care she received from the clinical system. EVALUATION: There was clear variation in care Unannounced Standardized Patients received; some frontline clerical staff followed best practices; others did not. Signage and information on disease spread prevention publicly available was inconsistent. Qualitative comments shared by the Unannounced Standardized Patients and those gathered during group debrief reinforced the experiences of the Unannounced Standardized Patients and hospital leadership. LESSONS LEARNED: Unannounced Standardized Patients revealed significant variation in care practices within a clinical system. Utilization of this assessment methodology can provide just-in-time clinical information about readiness and safety practices, particularly during emerging outbreaks. Unannounced Standardized Patients will prove especially powerful as clinicians and systems return to outpatient visits while remaining vigilant about potentially infected individuals.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid38 | ***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: Hospital reengineering against COVID-19 outbreak: 1-month experience of an Italian tertiary care center. OBJECTIVE: The recent outbreak of SARS-CoV-2 infection in Italy has resulted in a sudden and massive flow of patients into emergency rooms, and a high number of hospitalizations with the need for respiratory isolation. Massive admission of patients to the Policlinico "Agostino Gemelli" Foundation of Rome, Italy, determined the need for reengineering the entire hospital. MATERIALS AND METHODS: In this article, we consider some of the structural and organizational changes that have been necessary to deal with the emergency, with particular reference to non-intensive medicine wards, and the preventive measures aimed at limiting the spread of SARS-CoV-2 infection among hospital staff and patients themselves. RESULTS: 577 staff members were subjected to molecular tests in 1-month period and 3.8% of the total were positive. 636 patients admitted to the COVID-19 pathway were included and analyzed: 45.4% were identified as SARS-CoV-2 positive. More SARS-CoV-2 negative patients were discharged in comparison to SARS-CoV-2 positive patients (59% vs. 41%, respectively). On the other hand, more SARS-CoV-2 positive patients were transferred to ICUs in comparison to SARS-CoV-2 negative patients (16% vs. 1%, respectively). Occurrence of death was similar between the two groups, 11% vs. 7%, for SARS-CoV-2 negative and positive patients, respectively. 25% of >/=80 years old SARS-CoV-2 positive patients died during the hospitalization, while death rate was lower in other age groups (5% in 70-79 years old patients and 0% in remaining age groups). CONCLUSIONS: Rapid hospital reengineering has probably had an impact on the management of patients with and without SARS-CoV-2 infection, and on in-hospital mortality rates over the reporting period.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid39 | ***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: Palliative Care Pandemic Pack: A Specialist Palliative Care Service Response to Planning the COVID-19 Pandemic. Specialist palliative care services (SPCS) have a vital role to play in the global coronavirus disease 2019 pandemic. Core expertise in complex symptom management, decision making in uncertainty, advocacy and education, and ensuring a compassionate response are essential, and SPCS are well positioned to take a proactive approach in crisis management planning. SPCS resource capacity is likely to be overwhelmed, and consideration needs to be given to empowering and supporting high-quality primary palliative care in all care locations. Our local SPCS have developed a Palliative Care Pandemic Pack to disseminate succinct and specific information, guidance, and resources designed to enable the rapid upskilling of nonspecialist clinicians needing to provide palliative care. It may be a useful tool for our SPCS colleagues to adapt as we face this global challenge collaboratively.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid40 | ***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 prospect on the use of antiviral drugs to control local outbreaks of COVID-19. BACKGROUND: Current outbreaks of COVID-19 are threatening the health care systems of several countries around the world. Control measures, based on isolation, contact tracing, and quarantine, can decrease and delay the burden of the ongoing epidemic. With respect to the ongoing COVID-19 epidemic, recent modeling work shows that these interventions may be inadequate to control local outbreaks, even when perfect isolation is assumed. The effect of infectiousness prior to symptom onset combined with asymptomatic infectees further complicates the use of contact tracing. We aim to study whether antivirals, which decrease the viral load and reduce infectiousness, could be integrated into control measures in order to augment the feasibility of controlling the epidemic. METHODS: Using a simulation-based model of viral transmission, we tested the efficacy of different intervention measures to control local COVID-19 outbreaks. For individuals that were identified through contact tracing, we evaluate two procedures: monitoring individuals for symptoms onset and testing of individuals. Additionally, we investigate the implementation of an antiviral compound combined with the contact tracing process. RESULTS: For an infectious disease in which asymptomatic and presymptomatic infections are plausible, an intervention measure based on contact tracing performs better when combined with testing instead of monitoring, provided that the test is able to detect infections during the incubation period. Antiviral drugs, in combination with contact tracing, quarantine, and isolation, result in a significant decrease of the final size and the peak incidence, and increase the probability that the outbreak will fade out. CONCLUSION: In all tested scenarios, the model highlights the benefits of control measures based on the testing of traced individuals. In addition, the administration of an antiviral drug, together with quarantine, isolation, and contact tracing, is shown to decrease the spread of the epidemic. This control measure could be an effective strategy to control local and re-emerging outbreaks of COVID-19.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid41 | ***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 the Pandemic on Otolaryngology Patients With Negative COVID-19 Status: Commentary and Insights From Orbital Emergencies. Efforts aimed at minimizing the spread of COVID-19 and "flattening the curve" may be affecting clinical care delivery for non-COVID-19 cases that include otolaryngologic and orbital conditions. We are witnessing changes in the manner that patients present, as well as modifications in clinical management strategies. An improved understanding of these phenomena and the contributing factors is essential for otolaryngologists to provide sound clinical care during this unprecedented pandemic.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid42 | ***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 Review of the State of the Art in Non-Contact Sensing for COVID-19. COVID-19, caused by SARS-CoV-2, has resulted in a global pandemic recently. With no approved vaccination or treatment, governments around the world have issued guidance to their citizens to remain at home in efforts to control the spread of the disease. The goal of controlling the spread of the virus is to prevent strain on hospitals. In this paper, we focus on how non-invasive methods are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. Early detection of COVID-19 can allow for early isolation to prevent further spread. This study outlines the advantages and disadvantages and a breakdown of the methods applied in the current state-of-the-art approaches. In addition, the paper highlights some future research directions, which need to be explored further to produce innovative technologies to control this pandemic.
OUTPUT:
| Prevention;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
1,
0,
1,
0,
0
] |
LitCovid43 | ***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: Global Comparison of Changes in the Number of Test-Positive Cases and Deaths by Coronavirus Infection (COVID-19) in the World. Global differences in changes in the numbers of population-adjusted daily test-positive cases (NPDP) and deaths (NPDD) by COVID-19 were analyzed for 49 countries, including developed and developing countries. The changes as a proportion of national population were compared, adjusting by the beginning of test-positive cases increase (BPI) or deaths increase (BDI). Remarkable regional differences of more than 100-fold in NPDP and NPDD were observed. The trajectories of NPDD after BDI increased exponentially within 20 days in most countries. Machine learning analysis suggested that NPDD on 30 days after BDI was the highest in developed Western countries (1180 persons per hundred million), followed by countries in the Middle East (128), Latin America (97), and Asia (7). Furthermore, in Western countries with positive rates of the PCR test of less than 7.0%, the increase in NPDP was slowing-down two weeks after BPI, and subsequent NPDD was only 15% compared with those with higher positive rates, which suggested that the situation of testing might have affected the velocity of COVID-19 spread. The causes behind remarkable differences between regions possibly include genetic factors of inhabitants because distributions of the race and of the observed infection increasing rates were in good agreement globally.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid44 | ***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: Cytologic and molecular correlates of SARS-CoV-2 infection of the nasopharynx. Infection by SARS-CoV-2 commonly begins in the nasopharynx, and the cytologic and molecular correlates are not characterized. Fifty-eight cytologic preps (20 oral and 38 from the nasopharynx) were obtained from ten patients and analyzed in a blinded fashion for SARS-CoV-2 spike and envelope protein by immunohistochemistry and viral RNA by in situ hybridization. qRTPCR identified three positive cases and seven controls; the three cases reported mild symptoms that resolved in 2-3 days. Blinded analyses confirmed the presence of the SARS-CoV-2 spike and envelope proteins and viral RNA in the three cases and viral absence in the seven controls. A signal for the positive cases was evident in each nasopharyngeal and none of the oral samples. Viral RNA/proteins localized exclusively to glandular cells and was present in high copy number. Blinded analysis of the cytology documented that the glandular cells infected by SARS-CoV-2 showed marked degeneration with ciliocytophthoria; viral inclusions were not evident. Co-expression analysis showed viral infected cells had increased apoptosis, marked by strong expression of activated caspase 3. Weekly serial testing of two of the cases showed persistence of productive viral infection for up to 2 weeks after symptom onset. It is concluded that the target cell of SARS-CoV-2 in the head and neck region is the glandular cell of the nasal passages, that viral infection is lytic and associated with high copy number that facilitates viral spread. The method outlines a simple, rapid test for productive SARS-CoV-2 based on immunohistochemistry or in situ hybridization of the glandular cells from the nasopharynx.
OUTPUT:
| Mechanism;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
1,
0,
0,
0,
0
] |
LitCovid45 | ***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 Role of Pharmacists in the Fight Against COVID-19. COVID-19 is a respiratory infection caused by SARSCoV-2, a newly identified coronavirus. The disease has quickly spread throughout the world and was declared a pandemic. Older people and those with comorbid conditions carry the highest burden of morbidity and mortality associated with COVID-19. As the most accessible health care professionals, community and ambulatory care pharmacists are well positioned to respond to this public health crisis by testing eligible patients-recently allowed by federal regulation-counseling them on treatment options for symptomatic relief, reinforcing prevention measures, and managing drug shortages. Hospital pharmacists also play an important role by assisting prescribers in selecting the best treatment regimens for patients, evaluating and securing investigational agents, developing criteria for drug use, mitigating drug shortages, and preserving personal protective equipment. In addition, long-term care pharmacists are instrumental in optimizing medication management and developing policies to reduce the risk of COVID-19 transmission among vulnerable residents.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid46 | ***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 pregnancy: creating an outpatient surveillance model in a public hospital system. Objectives We describe a standardized, scalable outpatient surveillance model for pregnant women with COVID-19 with several objectives: (1) to identify and track known, presumed, and suspected COVID-positive pregnant patients both during their acute illness and after recovery, (2) to regularly assess patient symptoms and escalate care for those with worsening disease while reducing unnecessary hospital exposure for others, (3) to educate affected patients on warning symptoms, hygiene, and quarantine recommendations, and (4) to cohort patient care, isolating stable infected patients at home and later within the same physical clinic area upon their return to prenatal care. Methods Pregnant women in an urban public hospital system with presumed or confirmed COVID-19 were added to a list in our electronic medical record as they came to the attention of providers. They received a series of phone calls based on their illness severity and were periodically assessed until deemed stable. Results A total of 83 patients were followed between March 19 and May 31, 2020. Seven (8%) were asymptomatic, 62 (75%) had mild disease, 11 (13%) had severe disease, and three (4%) had critical illness. Conclusions We encourage others to develop and utilize outpatient surveillance systems to facilitate appropriate care and to optimize maternal and fetal well-being.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid47 | ***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: Identification of phytochemicals as potential therapeutic agents that binds to Nsp15 protein target of coronavirus (SARS-CoV-2) that are capable of inhibiting virus replication. BACKGROUND: Coronavirus disease 2019 (COVID-19) playing havoc across the globe caused 585,727 deaths and 13,616,593 confirmed cases so far as per World Health Organization data released till 17th July 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2) is responsible for causing this pandemic across different continents. It is not only impacting the world economy but also quarantined millions of people in their homes or hospitals. PURPOSE: At present, there is no Food and Drug Administration-approved drug or vaccine available to treat this disease. Still, people are trying various pre-existing medicines that are known to have anti-viral or anti-parasitic effects. In view of this, the present study aimed to study the binding potential of various phytochemicals present in multiple natural plant extract as a secondary metabolite to non-structural protein 15 (Nsp15) protein, a drug target known to play a crucial role in virulence of coronavirus. METHOD: Nsp15 protein was selected because it shows 89% similarity to the other SARS-CoV, which caused the earlier outbreak. The assumption is that inhibition of Nsp15 slowdowns the viral replication. Phytochemicals are selected as these are present in various plant parts (seed, flower, roots, etc.), which are used in different food cuisines in different geographical regions across the globe. The molecular docking approach was performed using two different software, i.e., Autodock, and Swissdock, to study the interaction of various phytochemicals with Nsp15 protein. Hydroxychloroquine is used as a positive control as it is used by medical professionals showing some positive effects in dealing with coronavirus. RESULTS: The present study demonstrated the binding potential of approximately 50 phytochemicals with Nsp15 and capable of inhibiting the viral replication, although in vitro and in vivo tests are required to confirm these findings. CONCLUSIONS: In conclusion, the present study successfully demonstrated the binding of phytochemicals such as sarsasapogenin, ursonic acid, curcumin, ajmalicine, novobiocin, silymarin and aranotin, piperine, gingerol, rosmarinic acid, and alpha terpinyl acetate to Nsp15 viral protein and they might play a key role in inhibiting SARS-CoV-2 replication.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid48 | ***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: Caring for Bereaved Family Members During the COVID-19 Pandemic: Before and After the Death of a Patient. Bereavement care is considered an integral component of quality end-of-life care endorsed by the palliative care movement. However, few hospitals and health care institutions offer universal bereavement care to all families of patients who die. The current coronavirus disease 2019 pandemic has highlighted this gap and created a sense of urgency, from a public health perspective, for institutions to provide support to bereaved family members. In this article, drawing on the palliative care and bereavement literature, we offer suggestions about how to incorporate palliative care tools and psychological strategies into bereavement care for families during this pandemic.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid49 | ***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: Microwave-Generated Steam Decontamination of N95 Respirators Utilizing Universally Accessible Materials. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused a severe, international shortage of N95 respirators, which are essential to protect health care providers from infection. Given the contemporary limitations of the supply chain, it is imperative to identify effective means of decontaminating, reusing, and thereby conserving N95 respirator stockpiles. To be effective, decontamination must result in sterilization of the N95 respirator without impairment of respirator filtration or user fit. Although numerous methods of N95 decontamination exist, none are universally accessible. In this work, we describe a microwave-generated steam decontamination protocol for N95 respirators for use in health care systems of all sizes, geographies, and means. Using widely available glass containers, mesh from commercial produce bags, a rubber band, and a 1,100-W commercially available microwave, we constructed an effective, standardized, and reproducible means of decontaminating N95 respirators. Employing this methodology against MS2 phage, a highly conservative surrogate for SARS-CoV-2 contamination, we report an average 6-log10 plaque-forming unit (PFU) (99.9999%) and a minimum 5-log10 PFU (99.999%) reduction after a single 3-min microwave treatment. Notably, quantified respirator fit and function were preserved, even after 20 sequential cycles of microwave steam decontamination. This method provides a valuable means of effective decontamination and reuse of N95 respirators by frontline providers facing urgent need.IMPORTANCE Due to the rapid spread of coronavirus disease 2019 (COVID-19), there is an increasing shortage of protective gear necessary to keep health care providers safe from infection. As of 9 April 2020, the CDC reported 9,282 cumulative cases of COVID-19 among U.S. health care workers (CDC COVID-19 Response Team, MMWR Morb Mortal Wkly Rep 69:477-481, 2020, https://doi.org/10.15585/mmwr.mm6915e6). N95 respirators are recommended by the CDC as the ideal method of protection from COVID-19. Although N95 respirators are traditionally single use, the shortages have necessitated the need for reuse. Effective methods of N95 decontamination that do not affect the fit or filtration ability of N95 respirators are essential. Numerous methods of N95 decontamination exist; however, none are universally accessible. In this study, we describe an effective, standardized, and reproducible means of decontaminating N95 respirators using widely available materials. The N95 decontamination method described in this work will provide a valuable resource for hospitals, health care centers, and outpatient practices that are experiencing increasing shortages of N95 respirators due to the COVID-19 pandemic.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid50 | ***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 5G Conspiracy Theory: Social Network Analysis of Twitter Data. BACKGROUND: Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. OBJECTIVE: The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. METHODS: This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph's vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. RESULTS: Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. CONCLUSIONS: The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid51 | ***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 serological survey of SARS-CoV-2 in cat in Wuhan. COVID-19 is a new respiratory illness caused by SARS-CoV-2, and has constituted a global public health emergency. Cat is susceptible to SARS-CoV-2. However, the prevalence of SARS-CoV-2 in cats remains largely unknown. Here, we investigated the infection of SARS-CoV-2 in cats during COVID-19 outbreak in Wuhan by serological detection methods. A cohort of serum samples were collected from cats in Wuhan, including 102 sampled after COVID-19 outbreak, and 39 prior to the outbreak. Fifteen sera collected after the outbreak were positive for the receptor binding domain (RBD) of SARS-CoV-2 by indirect enzyme linked immunosorbent assay (ELISA). Among them, 11 had SARS-CoV-2 neutralizing antibodies with a titer ranging from 1/20 to 1/1080. No serological cross-reactivity was detected between SARS-CoV-2 and type I or II feline infectious peritonitis virus (FIPV). In addition, we continuously monitored serum antibody dynamics of two positive cats every 10 days over 130 days. Their serum antibodies reached the peak at 10 days after first sampling, and declined to the limit of detection within 110 days. Our data demonstrated that SARS-CoV-2 has infected cats in Wuhan during the outbreak and described serum antibody dynamics in cats, providing an important reference for clinical treatment and prevention of COVID-19.
OUTPUT:
| Diagnosis;Transmission;Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
1,
0,
1,
0,
0
] |
LitCovid52 | ***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: Acupuncture for corona virus disease 2019: A protocol for systematic review and meta analysis. BACKGROUND: There is a worldwide outbreak of coronavirus disease 2019 (COVID-19), at present, accumulative attention has been paid to COVID-19 due to its global prevalence. Acupuncture may play a beneficial role in patients who suffer from COVID-19. In China and East Asia, acupuncture has been widely used to treat diverse diseases for thousands of years, as an important method of treatment now, it plays an indispensable role in the treatment of respiratory diseases in China. This study is designed to determine the efficacy and safety of acupuncture in COVID-19. METHODS: We will search the following sources for the Randomized controlled trials (RCT): The Cochrane Library, PubMed, EMBASE, Web of Science, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure Database (CNKI), Chinese Science, and the Wanfang Database. All the above databases will be searched from the available date of inception until the latest issue. No language or publication restriction will be used. Primary outcomes will include chest CT and nucleic acid detection of respiratory samples. RESULTS: The results will provide a high-quality synthesis of current evidence for researchers in this subject area. CONCLUSION: The conclusion of our study will provide evidence to evaluate whether acupuncture is an effective treatments for patients suffering from COVID-19. PROSPERO REGISTRATION NUMBER: CRD42020180875.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid53 | ***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: Changing paradigms of dermatology practice in developing nations in the shadow of COVID-19: Lessons learnt from the pandemic. At present, routine dermatology practices stay mostly disrupted worldwide owing to the ongoing COVID-19 pandemic. However, dermatology services need to be resumed in future and dermatologists especially in developing countries face a mammoth task of devising plans to tackle the upcoming surge of patients while still maintaining the precautions to avoid risk of infection to health care workers and our patients. Teledermatology practice is a viable alternative and there is need of starting functioning teledermatology centers at primary health care centers and training health care workers in telemedicine. Several steps like increasing the working hours of outpatient clinics, posting dermatologists and health staffs in shifts, encouraging online registration and payment, providing time slots to patients should be taken to prevent overcrowding at outpatient departments in hospitals of developing countries like India where the usual patient turnover during summers maybe around 600 to 800 per day. Once diagnosed by the dermatologist, a subsequent meticulous use of teledermatology can limit the number of follow-up visits. To avoid student gatherings, the undergraduate and postgraduate teaching schedule should be replaced by online or virtual teaching in form of webinars and video conferencing. Above all, intense upgradation of health care infrastructure, recruitment, training of new health care staffs on mass level and huge investment in health care sector is required in all the developing countries.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid54 | ***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: Relationship between hand hygiene and cutaneous findings during COVID-19 pandemic. BACKGROUND: In the current situation of the COVID-19 pandemic, healthcare workers (HCWs) have to comply with hygiene conditions and use gloves more frequently and for a longer period of time than they would previously to avoid infection and prevent transmission. AIMS: We aimed to characterize the adverse skin reactions occurring after hand hygiene and glove use in HCWs in a tertiary university hospital to determine the possible causative factors and whether the use of these measures is affected. METHODS: Between April 15 and May 1, 2020, a cross-sectional survey was conducted, using online questionnaire, answered by HCWs in a tertiary university hospital. RESULTS: The increase in general hand-skin problems during the pandemic period was statistically significant (P = .004). The most common symptom was dryness. During the pandemic period, 67 (24.3%) HCWs thought that the conditions were caused by glove use, and 197 (71.4%) thought that they were due to alcohol-based hand antiseptics. The incidence of other hand-skin conditions except for vesicles was statistically higher in women than in men (P < .001). CONCLUSIONS: Increased number of hand-skin conditions during the pandemic should not be ignored, since hand hygiene and glove use are expected to increase.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid55 | ***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: Smoking Cessation as a Public Health Measure to Limit the Coronavirus Disease 2019 Pandemic. The novel coronavirus disease 2019 (COVID-19) has already evolved into a rapidly expanding pandemic. Risk factors for COVID-19, such as cardiovascular disease, chronic obstructive pulmonary disease and diabetes, are all strongly associated with smoking habits. The effects of cigarette smoking on the transmission of the virus and worsening of COVID-19 have been less addressed. Emerging data indicate that smoking history is the major determinant of worsening COVID-19 outcomes. Smoking cessation recovers airway ciliary clearance and immune function. Thus, smoking cessation awareness is strongly encouraged as a public health measure to limit the global impact of COVID-19.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |
LitCovid56 | ***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: High dose subcutaneous Anakinra to treat acute respiratory distress syndrome secondary to cytokine storm syndrome among severely ill COVID-19 patients. OBJECTIVE: Severely ill COVID-19 patients may end in acute respiratory distress syndrome (ARDS) and multi-organ failure. Some of them develop a systemic hyperinflammatory state produced by the massive release of inflammatory agents, known as cytokine storm syndrome (CSS). Inhibition of IL-1 by Anakinra (ANK) is a potential life-saving therapy for severe CSS cases. We propose a rationale for the use of subcutaneous ANK and review our initial experience in a small cohort of severe COVID-19 CSS patients. METHODS: Retrospective cohort study of COVID-19 patients developing ARDS (PaO2/FiO2 <300) and exhibiting signs of hyperinflammation (ferritin >1000 ng/mL and/or d-dimers > 1.5 mug/mL, plus IL-6 < 40 mg/mL) that received ANK. For comparison, a propensity score matched historical cohort of patients treated with IL-6 inhibitor Tocilizumab (TCZ) was used. Patients had previously received combinations of azithromycin, hydroxy-chloroquine, and methyl-prednisolone. Laboratory findings, respiratory function and adverse effects were monitored. Resolution of ARDS within the first 7 days of treatment was considered a favorable outcome. RESULTS: Subcutaneous ANK (100 mg every 6 h) was given to 9 COVID-19 ARDS CSS patients (77.8% males). Median age was 62 years (range, 42 to 87). A TCZ cohort of 18 patients was selected by propensity score matching and treated with intravenous single dose of 600 mg for patients weighing >75 Kg, or 400 mg if < 75 Kg. Prior to treatment, median PaO2/FiO2 ratio of the ANK and TCZ cohorts were 193 and 249, respectively (p = 0.131). After 7 days of treatment, PaO2/FiO2 ratio improved in both groups to 279 (104-335) and 331 (140-476, p = 0.099) respectively. On day 7, there was significant reduction of ferritin (p = 0.046), CRP (p = 0.043), and IL-6 (p = 0.043) levels in the ANK cohort but only of CRP (p = 0.001) in the TCZ group. Favorable outcome was achieved in 55.6% and 88.9% of the ANK and TCZ cohorts, respectively (p = 0.281). Two patients that failed to respond to TCZ improved after ANK treatment. Aminotransferase levels significantly increased between day 1 and day 7 (p = 0.004) in the TCZ group. Mortality was the same in both groups (11%). There were not any opportunistic infection in the groups nor other adverse effects attributable to treatment. CONCLUSION: Overall, 55.6% of COVID-19 ARDS CSS patients treated with ANK exhibited favorable outcome, not inferior to a TCZ treated matched cohort. ANK may be a potential alternative to TCZ for patients with elevated aminotransferases, and may be useful in non-responders to TCZ.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid57 | ***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: Stem Cell-Based Therapy for Coronavirus Disease 2019. The novel coronavirus disease 2019 (COVID-19) has grown to be a global public-health emergency since patients were first detected in Wuhan, China, in December 2019. As of April 9, 2020, the novel coronavirus (named as SARS-CoV-2 by the International Committee on Taxonomy of Viruses on February 11) has infected 83,251 and 1,484,811 patients in China and the world, respectively. However, we have neither confirmed effective antiviral medications nor vaccines available to deal with this emergency. In this commentary, we offer an alternative promising therapy for COVID-19, that is, mesenchymal stem cell transplantation.
OUTPUT:
| Treatment | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
1,
0,
0,
0
] |
LitCovid58 | ***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 (SARS-CoV-2) Infection in Pregnancy: A Systematic Review. INTRODUCTION: To review published studies related to the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections with pregnancy, foetal, and neonatal outcomes during coronavirus disease 2019 (COVID-19) pandemic in a systematic manner. METHODS: A comprehensive electronic search was done through PubMed, Scopus, Medline, Cochrane database, and Google Scholar from December 01, 2019, to May 22, 2020, along with the reference list of all included studies. All cohort studies that reported on outcomes of COVID-19 during pregnancy were included. Qualitative assessment of included studies was performed using the Newcastle-Ottawa scale. RESULTS: Upon admission, most pregnant women underwent a low-dose radiation CT scan; the reports of which included unilateral/bilateral pneumonia in most patients. A marked lymphopenia was also noted in many patients with COVID-19. 513 titles were screened, and 22 studies were included, which identified 156 pregnant women with COVID-19 and 108 neonatal outcomes. The most common maternal/foetal complications included intrauterine/foetal distress (14%) and premature rupture of membranes (8%). The neonatal clinical manifestations of COVID-19 commonly included shortness of breath (6%), gastrointestinal symptoms (4%), and fever (3%). CONCLUSION: COVID-19 infection in pregnancy leads to increased risk in pregnancy complications such as preterm birth, PPROM, and may possibly lead to maternal death in rare cases. There is no evidence to support vertical transmission of SARS-CoV-2 infection to the unborn child. Due to a paucity of inconsistent data regarding the impact of COVID-19 on the newborn, caution should be undertaken to further investigate and monitor possible infection in the neonates born to COVID-19-infected mothers.
OUTPUT:
| Treatment;Transmission;Diagnosis | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
1,
1,
1,
0,
0,
0
] |
LitCovid59 | ***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: Bowel ulceration following tocilizumab administration in a COVID-19 patient. Tocilizumab, a monoclonal antibody against interleukin-6, has been used to treat cytokine release syndrome (CRS) in a subset of patients with severe COVID-19 disease. Acute ulcerative bowel disease has been only rarely documented in patients treated for rheumatological conditions. The gastrointestinal side effects seen when used in the context of COVID-19 are unknown. We present a case of COVID-19 CRS in which acute terminal ileum and perforated caecal ulceration evolved after tocilizumab exposure. We raise awareness of a possible causal relationship between even a single dose of tocilizumab and gut ulceration in patients with COVID-19. Any such drug enteropathy relationship requires watchful monitoring during upcoming trials of tocilizumab in patients with COVID-19.
OUTPUT:
| Case Report | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
0,
1,
0
] |
LitCovid60 | ***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: 2019_nCoV/SARS-CoV-2: rapid classification of betacoronaviruses and identification of Traditional Chinese Medicine as potential origin of zoonotic coronaviruses. The current outbreak of a novel severe acute respiratory syndrome-like coronavirus, 2019_nCoV (now named SARS-CoV-2), illustrated difficulties in identifying a novel coronavirus and its natural host, as the coding sequences of various Betacoronavirus species can be highly diverse. By means of whole-genome sequence comparisons, we demonstrate that the noncoding flanks of the viral genome can be used to correctly separate the recognized four betacoronavirus subspecies. The conservation would be sufficient to define target sequences that could, in theory, classify novel virus species into their subspecies. Only 253 upstream noncoding sequences of Sarbecovirus are sufficient to identify genetic similarities between species of this subgenus. Furthermore, it was investigated which bat species have commercial value in China, and would thus likely be handled for trading purposes. A number of coronavirus genomes have been published that were obtained from such bat species. These bats are used in Traditional Chinese Medicine, and their handling poses a potential risk to cause zoonotic coronavirus epidemics. SIGNIFICANCE AND IMPACT OF THE STUDY: The noncoding upstream and downstream flanks of coronavirus genomes allow for rapid classification of novel Betacoronavirus species and correct identification of genetic relationships. Although bats are the likely natural host of 2019_nCoV, the exact bat species that serves as the natural host of the virus remains as yet unknown. Chinese bat species with commercial value were identified as natural reservoirs of coronaviruses and are used in Traditional Chinese Medicine. Since their trading provides a potential risk for spreading zoonoses, a change in these practices is highly recommended.
OUTPUT:
| Mechanism;Transmission | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
1,
0,
0,
0,
0,
0
] |
LitCovid61 | ***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 SARS-CoV-2 host cell receptor ACE2 correlates positively with immunotherapy response and is a potential protective factor for cancer progression. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 29 million people and has caused more than 900,000 deaths worldwide as of September 14, 2020. The SARS-CoV-2 human cell receptor ACE2 has recently received extensive attention for its role in SARS-CoV-2 infection. Many studies have also explored the association between ACE2 and cancer. However, a systemic investigation into associations between ACE2 and oncogenic pathways, tumor progression, and clinical outcomes in pan-cancer remains lacking. Using cancer genomics datasets from the Cancer Genome Atlas (TCGA) program, we performed computational analyses of associations between ACE2 expression and antitumor immunity, immunotherapy response, oncogenic pathways, tumor progression phenotypes, and clinical outcomes in 13 cancer cohorts. We found that ACE2 upregulation was associated with increased antitumor immune signatures and PD-L1 expression, and favorable anti-PD-1/PD-L1/CTLA-4 immunotherapy response. ACE2 expression levels inversely correlated with the activity of cell cycle, mismatch repair, TGF-beta, Wnt, VEGF, and Notch signaling pathways. Moreover, ACE2 expression levels had significant inverse correlations with tumor proliferation, stemness, and epithelial-mesenchymal transition. ACE2 upregulation was associated with favorable survival in pan-cancer and in multiple individual cancer types. These results suggest that ACE2 is a potential protective factor for cancer progression. Our data may provide potential clinical implications for treating cancer patients infected with SARS-CoV-2.
OUTPUT:
| Treatment;Mechanism | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
1,
0,
0,
1,
0,
0,
0
] |
LitCovid62 | ***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: Triage of Scarce Critical Care Resources in COVID-19 An Implementation Guide for Regional Allocation: An Expert Panel Report of the Task Force for Mass Critical Care and the American College of Chest Physicians. Public health emergencies have the potential to place enormous strain on health systems. The current pandemic of the novel 2019 coronavirus disease has required hospitals in numerous countries to expand their surge capacity to meet the needs of patients with critical illness. When even surge capacity is exceeded, however, principles of critical care triage may be needed as a means to allocate scarce resources, such as mechanical ventilators or key medications. The goal of a triage system is to direct limited resources towards patients most likely to benefit from them. Implementing a triage system requires careful coordination between clinicians, health systems, local and regional governments, and the public, with a goal of transparency to maintain trust. We discuss the principles of tertiary triage and methods for implementing such a system, emphasizing that these systems should serve only as a last resort. Even under triage, we must uphold our obligation to care for all patients as best possible under difficult circumstances.
OUTPUT:
| Prevention | [
"Mechanism",
"Transmission",
"Diagnosis",
"Treatment",
"Prevention",
"Case Report",
"Epidemic Forecasting"
] | [
0,
0,
0,
0,
1,
0,
0
] |