Epidemiological, virological and serological investigation into a SARS-CoV-2 outbreak (Alpha variant) in a primary school: a prospective longitudinal study We report a prospective epidemiological, virological and serological investigation of a SARS-CoV-2 outbreak in a primary school, as part of a longitudinal, prospective, primary school-based surveillance study. It involved repeated testing of pupils and teachers and household members of participants who tested positive, with rapid antigen tests and/or RT-PCR (Day 0-2 and Day 5-7), serologies on dried capillary blood samples (Day 0-2 and Day 30), contact tracing interviews and SARS-CoV-2 whole genome sequencing. This SARS-CoV-2 outbreak caused by the Alpha variant involved 20 children aged 4 to 6 years from 4 classes, 2 teachers and a total of 4 household members. Infection attack rates were between 11.8 and 62.0% among pupils from the 4 classes, 22.2% among teachers and 0% among non-teaching staff. Secondary attack rate among household members was 15.4%. Symptoms were reported by 63% of infected children, 100% of teachers and 50% of household members. All analysed sequences but one showed 100% identity. Serological tests detected 8 seroconversions unidentified by SARS-CoV-2 virological tests. This study confirmed child-to-child and child-to-adult transmission of the infection. Effective measures to limit transmission in schools have the potential to reduce the overall community circulation.
Prevalence of RT-qPCR-detected SARS-CoV-2 infection at schools: First results from the Austrian School-SARS-CoV-2 prospective cohort study BackgroundThe role of schools in the SARS-CoV-2 pandemic is much debated. We aimed to quantify reliably the prevalence of SARS-CoV-2 infections at schools detected with reverse-transcription quantitative polymerase-chain-reaction (RT-qPCR).

MethodsThis nationwide prospective cohort study monitors a representative sample of pupils (grade 1-8) and teachers at Austrian schools throughout the school year 2020/2021. We repeatedly test participants for SARS-CoV-2 infection using a gargling solution and RT-qPCR. We herein report on the first two rounds of examinations. We used mixed-effect logistic regression to estimate odds ratios and robust 95% confidence intervals (95% CI).

FindingsWe analysed data on 10734 participants from 245 schools (9465 pupils, 1269 teachers). Prevalence of SARS-CoV-2 infection increased from 0.39% at round 1 (95% CI 0.28-0{middle dot}55%, 29 September-22 October 2020) to 1{middle dot}39% at round 2 (95% CI 1{middle dot}04-1{middle dot}85%, 10-16 November). Odds ratios for SARS-CoV-2 infection were 2{middle dot}26 (95% CI 1{middle dot}25-4{middle dot}12, P=0{middle dot}007) in regions with >500 vs. [&le;]500 inhabitants/km2, 1{middle dot}67 (95% CI 1{middle dot}42-1{middle dot}97, P<0{middle dot}001) per two-fold higher regional 7-day incidence, and 2{middle dot}78 (95% CI 1{middle dot}73-4{middle dot}48, P<0{middle dot}001) in pupils at schools with high/very high vs. low/moderate social deprivation. Associations of community incidence and social deprivation persisted in a multivariable adjusted model. Prevalence did not differ by average number of pupils per class nor between age groups, sexes, pupils vs. teachers, or primary (grade 1-4) vs. secondary schools (grade 5-8).

InterpretationThis monitoring study in Austrian schools revealed SARS-CoV-2 infection in 0{middle dot}39%-1{middle dot}39% of participants and identified associations of regional community incidence and social deprivation with higher prevalence.

FundingBMBWF Austria.
The kidney releases a non-polymerizing form of Uromodulin in the urine and circulation that retains the external hydrophobic patch domain Uromodulin (Tamm-Horsfall protein, THP) is a glycoprotein uniquely produced in the kidney. It is released by cells of the thick ascending limbs (TAL) apically in the urine, and basolaterally in the renal interstitium and systemic circulation. Processing of mature urinary THP, which polymerizes into supra-molecular filaments, requires cleavage of an external hydrophobic patch (EHP) at the C terminus. However, THP in the circulation is not polymerized, and it remains unclear if non-aggregated forms of THP exist natively in the urine. We propose that an alternative processing path, which retains the EHP domain, can lead to a non-polymerizing form of THP. We generated an antibody that specifically recognizes THP with retained EHP (THP+EHP) and established its presence in the urine in a non-polymerized native state. Proteomic characterization of urinary THP+EHP revealed its C-terminus to end at F617. In the human kidney, THP+EHP was not only detected in TAL cells, but also diffusely in the renal parenchyma. Using immunoprecipitation followed by proteomic sequencing and immunoblotting, we then demonstrated that serum THP has also retained EHP. In a small cohort of patients at risk for acute kidney injury (AKI), admission urinary THP+EHP was significantly lower in patients who subsequently developed AKI during hospitalization. Our findings uncover novel insights into uromodulin biology by establishing the presence of an alternative path for cellular processing, which could explain the release of non-polymerizing THP in the circulation. Larger studies are needed to establish the utility of urinary THP+EHP as a sensitive biomarker of kidney health and susceptibility to injury. Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant ImportanceOutpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, in particular whether to hospitalize a patient and if managed as an outpatient, how closely to follow them.

ObjectiveTo develop and prospectively validate a clinical prediction rule to predict the likelihood of hospitalization for outpatients with COVID-19 that does not require laboratory testing or imaging.

DesignDerivation and temporal validation of a clinical prediction rule, and prospective validation of two externally derived clinical prediction rules.

SettingPrimary and Express care clinics in a Pennsylvania health system.

ParticipantsPatients 12 years and older presenting to outpatient clinics who had a positive polymerase chain reaction test for COVID-19.

Main outcomes and measuresClassification accuracy (percentage in each risk group hospitalized) and area under the receiver operating characteristic curve (AUC).

ResultsOverall, 7.4% of outpatients in the early derivation cohort (5843 patients presenting before 3/1/21) and 5.5% in the late validation cohort (3806 patients presenting 3/1/21 or later) were ultimately hospitalized. We developed and temporally validated three risk scores that all included age, dyspnea, and the presence of comorbidities, adding respiratory rate for the second score and oxygen saturation for the third. All had very good overall accuracy (AUC 0.77 to 0.78) and classified over half of patients in the validation cohort as very low risk with a 1.7% or lower likelihood of hospitalization. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization (2.8%).

Conclusions and relevanceSimple risk scores applicable to outpatient and telehealth settings can identify patients with very low (1.6% to 1.7%), low (5.2% to 5.9%), moderate (14.7% to 15.6%), and high risk (32.0% to 34.2%) of hospitalization. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/. Distinct temporal characteristics of circulating alveolar epithelial and endothelial injury markers in ARDS with COVID-19: a preliminary retrospective report The time course and specific contributions of alveolar epithelial and endothelial injury to the pathogenesis of acute respiratory distress syndrome (ARDS) with coronavirus disease (COVID-19) remain unclear. Here, we evaluated the characteristics of circulating markers of alveolar epithelial and endothelial injury in serum samples from eleven ARDS patients and ten non-ARDS patients, all with COVID-19. Our results indicates that the alveolar epithelial injury at the very early disease stage and the endothelial injury which continues to exacerbate during the later disease stage seem to be the hallmarks of ARDS with COVID-19. Survey of Contaminated Percutaneous Injuries in Anesthesia Practitioners BackgroundAnesthesia practitioners are at inherent risk for percutaneous injuries by blood-contaminated needles and sharp objects. These exposures may result in transmission of HIV and hepatitis viruses. Data about this occupational hazard from contaminated needles and sharp devices is limited and decades old. We conducted a web-based survey to assess the occurrence, reporting, characteristics, and outcome of contaminated percutaneous injuries (CPI) in anesthesia residents, fellows, and attendings.

MethodsAfter institutional research board approval, an email was sent to 217 anesthesia practitioners requesting their participation in an online survey about contaminated percutaneous injuries. Responses were collected from February through March 2020. Results are reported as absolute numbers and proportions with 95% confidence interval (CI).

ResultsThe overall survey response rate was 51% (110/217). 59% (65/110) (95% CI, 50-68) of participants reported having one or more contaminated percutaneous injury during their years of anesthesia practice (42% (21/50) of residents, 50% (4/8) of fellows, 77% (40/52) of anesthesia attendings). Prevalence of injuries related to attendings years of anesthesia practice was 69% (95% CI, 44-94) for 5-10 years, 62.5% (95% CI, 29-96) for 10-15 years, and 79% (95% CI, 63- 95) for greater than 15 years of practice.

35% (95% CI, 26-44) of participants reported having one or more CPI within the last 5 years (40% of residents, 50% of fellows, 29% of attendings). Occurrence of CPI within the last 5 years based on attending anesthesiologist years of practice was 57% for less than 5 years, 37.5% for 10-15 years, and 20% for 15-20 years of practice. 75% (95% CI, 65-85) reported the incident at the time of injury. 59% (95% CI, 48-70) of injuries were due to hollow bore needles. 50% (95% CI, 39-61) of total injuries were high risk. 26% of injured anesthesia practitioners received post-exposure prophylaxis and there were zero seroconversions.

ConclusionMost anesthesiologists will sustain a contaminated percutaneous injury during their careers. Incidence of these injuries decreases with years of practice. Occurrence of these injuries is high among anesthesia residents, with the majority reporting their injuries. Half of the injuries are high risk with a quarter requiring postexposure prophylaxis. More education and interventions are needed to reduce percutaneous injuries and improve reporting. Development of machine learning models for the prediction of complications after colorectal and small intestine surgery in psychiatric and non-psychiatric patient collectives (P-Study) Psychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative Risk factor, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and length of hospital stay via predictive modeling techniques.

MethodPatient data will be collected from several participating national and international surgical centers The machine learning models will be calculated and coded, but also published according to the TRIPOD guidelines (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis).

ResultIt is conceivable to arrive at generalizable models predicting the abovementioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool using the Shiny environment [47]. The cost for the hosting server and digital infrastructure will be covered by Dr. Anas Taha. The sponsor will store the data for ten years. Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis Fecal microbiota transplant is a promising therapy for ulcerative colitis. Parameters maximizing effectiveness and tolerability are not yet clear, and it is not known how import the transmission of donor microbes to patients is. Here (clinicaltrails.gov: NCT03006809) we have tested the effects of antibiotic pretreatment and compared two modes of maintenance dose delivery, capsules versus enema, in a randomized, pilot, open-label, 2x2 factorial design with 22 patients analyzed with mild to moderate UC. Clinically, the treatment was well-tolerated with favorable safety profile. Of patients who received antibiotic pretreatment, 6 of 11 experienced remission after six weeks of treatment, versus 2 of 11 non-pretreated patients (odds ratio: 1.69, 95% confidence interval: -0.25 to 3.62). No significant differences were found between maintenance dosing via capsules versus enema. In exploratory analyses, microbiome turnover at both the species and strain levels was extensive and significantly more pronounced in the pretreated patients. Associations were also revealed between taxonomic turnover and changes in the composition of primary and secondary bile acids. Together these findings suggest that antibiotic pretreatment contributes to microbiome engraftment and possibly clinical effectiveness, and validate longitudinal strain tracking as a powerful way to monitor the dynamics and impact of microbiota transfer. Patient attrition in Molecular Tumour Boards: A Systematic Review Molecular Tumour Boards (MTBs) were created with the purpose of supporting clinical decision making within precision medicine. Though these meetings are in use globally reporting often focuses on the small percentages of patients that receive treatment via this process and are less likely to report on, and assess, patients who do not receive treatment. A literature review was performed to understand patient attrition within MTBs and barriers to patients receiving treatment. A total of 54 papers were reviewed spanning a 6 year period from 11 different countries. 20% of patients received treatment through the MTB process. Of those that did not receive treatment the main reasons were no mutations identified (26%), no actionable mutations (22%) and clinical deterioration (15%). However, the data was often incomplete due to inconsistent reporting of MTBs with only 53% reporting on patients having no mutations, 48% reporting on presence of actionable mutations with no treatment options and 57% reporting on clinical deterioration. As patient attrition in MTBs is an issue which is very rarely alluded to in reporting, more transparent reporting is needed to understand barriers to treatment and integration of new technologies is required to process increasing omic and treatment data. The tumor suppressor Adenomatous polyposis coli regulates T lymphocyte migration. Insights from familial polyposis patients Adenomatous polyposis coli (APC) is a tumor suppressor whose mutations underlie familial adenomatous polyposis (FAP) and colorectal cancer. Although its role in intestinal epithelial cells is well characterized, APC importance for anti-tumor immunity is ill defined. APC regulates cytoskeleton organization, cell polarity and migration in various cells types. Here we address whether APC plays a role in T lymphocyte migration, a key step of anti-tumor immune responses.

Using a series of cell biology tools, we demonstrated that T cells from FAP patients carrying APC mutations display adhesion and migration defects. Concomitantly, they presented lower expression of the integrin VLA-4. To further dissect the cellular mechanisms underpinning these defects, we depleted APC in the CEM T cell line. We found that APC is critical not only for VLA-4-dependent adhesion but also for actomyosin and microtubule organization in migrating T cells. Finally, APC-silenced CEM cells preferentially adopt an ameboid-like migration featuring unstructured pseudopodia and blebbing.

These findings underscore a role of APC in T cell migration via modulation of integrin-dependent adhesion and cytoskeleton reorganization. Hence, APC mutations in FAP patients not only drive intestinal neoplasms, but also impair T cell migration, potentially leading to inefficient T cell-mediated anti-tumor immunity. Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data For a medical diagnosis, health professionals use different kinds of pathological ways to make a decision for medical reports in terms of patients medical condition. In the modern era, because of the advantage of computers and technologies, one can collect data and visualize many hidden outcomes from them. Statistical machine learning algorithms based on specific problems can assist one to make decisions. Machine learning data driven algorithms can be used to validate existing methods and help researchers to suggest potential new decisions. In this paper, Multiple Imputation by Chained Equations was applied to deal with missing data, and Principal Component Analysis to reduce the dimensionality. To reveal significant findings, data visualizations were implemented. We presented and compared many binary classifier machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Machine) which were used to classify blood donors and non-blood donors with hepatitis, fibrosis and cirrhosis diseases. From the data published in UCI-MLR, all mentioned techniques were applied to find one better method to classify blood donors and non-blood donors (hepatitis, fibrosis, and cirrhosis) that can help health professionals in a laboratory to make better decisions. Our proposed ML-method showed a better accuracy score (e.g. 98.23% for SVM). Thus, it improved the quality of classification. Factors affecting first return to work following arthroscopic rotator cuff repair: A retrospective observational study in an occupational medicine clinic and single-surgeon practice BackgroundReturn to work (RTW) following arthroscopic rotator cuff repair (aRCR) within New South Wales (NSW), Australia, under compensable schemes has not been reported.

AimsDetermine factors affecting RTW status and time in patients treated with aRCR under state-based compensation schemes, compared to those outside such schemes.

MethodsPatients undergoing aRCR by one surgeon with minimum 1-year follow-up were grouped into those under (CP) or outside (non-CP) workers or vehicle accident compensation schemes, matched by age and gender. RTW status and time were assessed using chi-square analysis and multivariable linear regression.

ResultsOf 1054 available patients, 90 CP patients were identified with 29 consented and matched to non-CP (N=29). A higher proportion of CP patients (17.2 vs 0%, P<0.001) never returned to work and a lower proportion resumed pre-injury duties at first RTW (3 vs 52%, P<0.01). Median time to first RTW did not differ between CP and non-CP groups (5.1 vs 4.4, P=0.86). Smoking (P=0.007) and post-injury activity level (P=0.004) were significantly associated with longer time to first RTW, whereas compensation status was not.

ConclusionsCP patients undergoing aRCR in NSW are at risk of not returning to work. For those that return, there is no significant difference compared to non-CP in time to first RTW. Particularly, patient and management factors associated with extended time to first RTW have been identified. Interventions aimed at modifiable factors such as smoking cessation and increasing preoperative activity may improve future outcomes.

What is already known about this subjectO_LIWork-related injury and disease present a significant financial burden to the Australian economy ($AUD61.8billion per annum), with shoulder conditions due to body stressing accounting for 7% of this total cost (>$AUD4.2billion)
C_LIO_LIPatients receiving compensation appear to have poorer outcomes and take longer to return to work than their non-compensated counterparts, but the degree to which this occurs is variably reported in the literature
C_LIO_LIThe effect of modifiable factors on return to work status and time remain unclear, and have not previously been reported for the Australian population under the New South Wales workers compensation scheme
C_LI

What this study addsO_LIPatients receiving arthroscopic rotator cuff repair under a compensable scheme in New South Wales are at increased risk of not returning to work compared to patients presenting outside of a compensable scheme and patients in equivalent schemes internationally
C_LIO_LIPatients reporting a longer duration of symptoms and smokers are at increased risk of extended time to first return to work
C_LI

What impact this may have on practice or policyO_LIThe study has identified smoking and pre-surgery activity levels as key targets for intervention in patients receiving arthroscopic rotator cuff repair under a workers compensation scheme in New South Wales
C_LIO_LIBy further investigating whether interventions designed to modify these factors are able to favourably affect patient outcomes, there is potential to return patients to their preoperative level of work sooner
C_LI COVID Outcome Prediction in the Emergency Department (COPE): Development and validation of a model for predicting death and need for intensive care in COVID-19 patients Background and aimCOVID-19 is putting extraordinary pressure on emergency departments (EDs). To support decision making in the ED, we aimed to develop a simple and valid model for predicting mortality and need for intensive care unit (ICU) admission in suspected COVID-19 patients.

MethodsFor model development, we retrospectively collected data of patients who were admitted to 4 large Dutch hospitals with suspected COVID-19 between March and August 2020 (first wave of the pandemic). Based on prior literature we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. Logistic regression analyses with post-hoc uniform shrinkage was used to obtain predicted probabilities of in-hospital death and of the need for ICU admission, both within 28 days after hospital admission. We assessed model performance (Area Under the ROC curve (AUC); calibration plots) with temporal validation in patients who presented between September and December 2020 (second wave). We used multiple imputation to account for missing values.

ResultsThe development data included 5,831 patients, of whom 629 (10.8%) died and 5,070 (86.9%) were discharged within 28 days after admission. ICU admission was fully recorded for 2,633 first wave patients in 2 hospitals, with 214 (8%) ICU admissions within 28 days. A simple model - COVID Outcome Prediction in the Emergency Department (COPE) - with age, respiratory rate, C-reactive protein, lactic dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well-calibrated and showed good discrimination in 3,252 second wave patients (AUC in 4 hospitals: 0.82 [0.78; 0.86]; 0.82 [0.74; 0.90]; 0.79 [0.70; 0.88]; 0.83 [0.79; 0.86]). COPE was also able to identify patients at high risk of needing IC in 706 second wave patients with complete information on ICU admission (AUC: 0.84 [0.78; 0.90]; 0.81 [0.66; 0.95]). The models are implemented in web-based and mobile applications.

ConclusionCOPE is a simple tool that is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.

CONTRIBUTION TO THE LITERATUREO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIPrediction models have the potential to support decision making about hospital admission of patients presenting to the emergency department with suspected COVID-19
C_LIO_LIMost currently available models that were independently assessed contain a high risk of bias
C_LIO_LIPromising models were developed in different patient selections and included predictors that are not quickly and objective obtainable in emergency departments
C_LI

What this study addsO_LIA simple and objective tool ("COPE") is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19
C_LIO_LICOPE may support ED physicians to identify high-risk patients - i.e. those at high risk of deterioration and/or death - requiring treatment in the ICU, intermediate-risk patients requiring admission to the clinical ward, and low-risk patients who can potentially be sent home
C_LI A collaborative maternity and newborn dashboard (CoMaND) for the COVID-19 pandemic: a protocol for timely, adaptive monitoring of perinatal outcomes in Melbourne, Australia BackgroundThe COVID-19 pandemic has resulted in a range of unprecedented disruptions to the delivery of maternity care globally and has been associated with regional changes in perinatal outcomes such as stillbirth and preterm birth. Metropolitan Melbourne endured one of the longest and most stringent lockdowns in 2020. This paper presents the protocol for a collaborative maternity dashboard project to monitor perinatal outcomes in Melbourne, Australia, during the COVID-19 pandemic.

MethodsDe-identified maternal and newborn outcomes will be collected monthly from all public maternity services in Melbourne, allowing rapid analysis of a multitude of perinatal indicators. Weekly outcomes will be displayed as run charts according to established methods for detecting non-random  signals in health care. A pre-pandemic median for all indicators will be calculated for the period of January 2018 to March 2020. A significant shift is defined as [&le;] six consecutive weeks, all above or below the pre-pandemic median. Additional statistical analyses such as regression, time-series, and survival analyses will be performed for an in-depth examination of maternal and perinatal outcomes of interests.

Ethics and DisseminationThis study has been registered as an observational study with the Australian and New Zealand Clinical Trials Registry (ACTRN12620000878976).

Strengths and weaknesses of this study This project is the first clinician-led, multi-centre perinatal data collection system for metropolitan Melbourne.
 It complements the state government data collection, with the significant benefits of more timely and flexible reporting of outcomes, and granular detail on emerging areas of concern.
 The study relies on primary source coding of exposure and outcomes from each hospital that have not been internally validated during the study period.
 Data from private maternity hospitals, containing 25% of Melbourne births, are not available.
 This resource will support data-informed hospital pandemic responses through to the end of 2022. Serum Vitamin D levels are associated with increased COVID-19 severity and mortality independent of whole-body and visceral adiposity INTRODUCTIONCoronavirus disease (COVID-19) is a global pandemic. Vitamin D deficiency has been associated with susceptibility to infectious disease. In this study, the association between COVID-19 outcomes and vitamin D levels in patients attending a COVID-19 reference center in Mexico City are examined.

METHODSConsecutive patients with confirmed COVID-19 were evaluated. All patients underwent clinical evaluation and follow-up, laboratory measurements and a thoracic computerized tomography, including the measurement of epicardial fat thickness. Low vitamin D was defined as levels <20ng/mL (<50nmol/L) and deficient Vitamin D as a level [&le;]12ng/mL (<30nmol/L)

RESULTSOf the 551 patients included, low vitamin D levels were present in 45.6% and deficient levels in 10.9%. Deficient Vitamin D levels were associated with mortality (HR 2.11, 95%CI 1.24-3.58, p=0.006) but not with critical COVID-19, adjusted for age, sex, body-mass index and epicardial fat. Using model-based causal mediation analyses the increased risk of COVID-19 mortality conferred by low vitamin D levels was partly mediated by its effect on D-dimer and cardiac ultrasensitive troponins. Notably, increased risk of COVID-19 mortality conferred by low vitamin D levels was independent of BMI and epicardial fat.

CONCLUSIONVitamin D deficiency ([&le;]12ng/mL or <30nmol/L), is independently associated with COVID-19 mortality after adjustment for visceral fat (epicardial fat thickness). Low vitamin D may contribute to a pro-inflammatory and pro-thrombotic state, increasing the risk for adverse COVID-19 outcomes. One Year of Evidence on Mental Health Disorders in China during the COVID-19 Crisis - A Systematic Review and Meta-Analysis This paper provides a systematic review and meta-analysis on the prevalence rate of mental health issues of general population, general and frontline healthcare workers (HCWs) in China over one year of the COVID-19 crisis. We systematically searched PubMed, Embase, Web of Science, and Medrxiv at November 16th, 2020, pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the heterogeneity. The meta-regression results uncovered several predictors of the prevalence rates, including severity, type of mental issues, population, sampling location, and study quality. Pooled prevalence rates are significantly different from, yet largely between, the findings of previous meta-analyses, suggesting the results of our larger study are consistent with yet more accurate than the findings of the smaller, previous meta-analyses. The prevalence rates of distress and insomnia and those of frontline HCWs are higher suggest future research and interventions should pay more attention to those mental outcomes and populations. Our findings suggest a need to examine the prevalence rates at varying levels of severity. The one-year cumulative evidence on sampling locations (Wuhan vs. non-Wuhan) corroborates the typhoon eye effect theory.

Trial registrationCRD4202022059 COVID-19 vaccine-associated cerebral venous thrombosis in Germany ObjectiveReports of cerebral sinus and venous thrombosis (CVT) after ChAdOx1 vaccination against SARS-CoV-2 have raised safety concerns. We aimed to estimate the incidence of CVT within one month from first dose administration and the frequency of vaccine-induced immune thrombotic thrombocytopenia (VITT) as the underlying mechanism after vaccination with BNT162b2, ChAdOx1, and mRNA-1273, in Germany.

MethodsA web-based questionnaire was e-mailed to all Departments of Neurology. We asked to report cases of CVT within one month of a COVID-19 vaccination. Other cerebral events could also be reported. Incidence rates of CVT were calculated by using official statistics of nine German States.

ResultsA total of 45 CVT cases were reported. In addition, 9 primary ischemic strokes, 4 primary intracerebral hemorrhages, and 4 other neurological events were recorded. Of the CVT patients, 35 (77.8%) were female, and 36 (80.0%) were below the age of 60 years. Fifty-three events were observed after vaccination with ChAdOx1 (85.5%), 9 after BNT162b2 (14.5%), and none after mRNA-1273 vaccination. After 7,126,434 first vaccine doses, the incidence rate of CVT within one month from first dose administration was 6.5 (95% CI, 4.4-9.2) per 100,000 person-years for all vaccines and 17.9 (11.8-26.1) for ChAdOx1 (after 2,320,535 ChAdOx1 first doses). The adjusted incidence rate ratio was 9.68 (3.46-34.98) for ChAdOx1 compared to mRNA-based vaccines and 3.14 (1.22-10.65) for women compared to non-women. In 26/45 patients with CVT (57.8%), VITT was graded highly probable.

ConclusionsGiven an incidence of 0.22-1.75 per 100,000 person-years for CVT in the general population, these findings point towards a higher risk for CVT after ChAdOx1 vaccination, especially for women. Diagnostic Model of in-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction Used Artificial Intelligence Methods BackgroundPreventing in-hospital mortality in Patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step.

ObjectivesThe objective of our research was to to develop and externally validate the diagnostic model of in-hospital mortality in acute STEMI patients used artificial intelligence methods.

MethodsWe divide non-randomly the American population with acute STEMI into a training set, a test set,and a validation set. We converted the unbalanced data into balanc ed data. We used artificial intelligence methods to develop and externally validate the dia gnostic model of in-hospital mortality in acute STEMI patients. We used confusion matrix combined with the area under the receiver operating characteristic curve (AUC) to evaluat e the pros and cons of the above models.

ResultsThe strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, atrial fibrillation(AF), ventricular fibrillation(VF),third degree atrioventricular block,in-hospital bleeding, underwent percutaneous coronary intervention(PCI) during hospitalization, underwent coronary artery bypass grafting (CABG) during hospitalization, hypertension history, diabetes history, and myocardial infarction history.The F2 score of logistic regression in the training set, the test set, and the validation data set were 0.81, 0.6, and 0.59 respectively.The AUC of logistic regression in the training set, the test set, and the validation data set were 0.77, 0.78, and 0.8 respectively. The diagnostic model built by logistic regression was the best.

ConclusionWe had used artificial intelligence methods developed and externally validated the diagnostic model of in-hospital mortality in acute STEMI patients.

We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027129; registered date: 1 November 2019). Deep learning for caries detection using optical coherence tomography Early detection of dental caries has been one of the most predominant topics studied over the last few decades. Conventional examination through visual-tactile inspection and radiography can be inaccurate and destructive to the tooth structure. The development of optical coherence tomography (OCT) has given dentistry an alternative diagnostic technique, which has been proven by numerous studies, that it has better sensitivity, specificity, and non-invasive characteristics. The growing popularity of artificial intelligence (AI) also contributes to a more efficient and effective way of image-based detection and decision-making. However, previous studies, which have attempted to employ AI for caries assessment, did not incorporate high-quality ground truth data. Therefore, this study aims to bypass this issue and highlights the importance of high-quality data. A two-phase study was carried out to explore different methods for caries detection. Initially, the comparison of caries detection based on OCT and apical radiography by 5 experienced clinicians was conducted. Then, five convolutional neural networks (CNNs), including AlexNet, VGG-16, ResNet-152, Xception, and ResNext-101, in the scope of AI were employed to detect caries and compared with the findings of the 5 clinicians. The data was preprocessed and labeled with the ground truth corresponding to microcomputed tomography (micro-CT) with rigorous definition. The weighted Kappa statistics suggested that OCT ({varkappa}= .699, SD = .090) showed a higher accuracy rate than radiography ({varkappa}= .407, SD = .049), and CNNs ({varkappa}= .860, SD = .049) were rated higher than clinicians ({varkappa}= .679, SD = .113), both at a .05 significance level. The best result was carried out by ResNet-152, which demonstrated a high accuracy rate of 95.21% and a sensitivity of 98.85%. These findings illustrate the importance of ground truth data for AI training and the potential of deep CNN algorithms combined with OCT for diagnosing dental caries. Social support & sustained physical activity during the COVID-19 pandemic COVID-19 lockdown introduced substantial barriers to physical activity, providing a unique  natural experiment to understand the social factors associated with sustained physical activity.

ObjectivesThe objectives of this study were to identify the proportion of people who successfully sustained physical activity during lockdown and to explore whether social support, loneliness and social isolation were associated with maintenance of physical activity during COVID-19 lockdown

MethodLongitudinal data from the COVID-19 Social Study was used to identify a sample of participants who maintained their physical activity despite lockdown.

Results16% were consistently active while 44% were completely inactive. After adjustment for multiple confounders high social support was associated with a 39% (95% CI, 12-74%) increased odds of sustaining physical activity. Associations between physical activity and loneliness and social isolation were not found.

ConclusionThis study supports previous research showing the importance of social support for the long-term maintenance of physical activity behaviour but shows that such effects extend to contexts of social restrictions. The effect of stimulus duration on preferences for gain adjustments when listening to speech ObjectivesIn the personalisation of hearing aid fittings, gain is often adjusted to suit patient preferences using live speech. When using brief sentences as stimuli, the minimum gain adjustments necessary to elicit consistent preferences ( preference thresholds) were previously found to be much greater than typical adjustments in current practice. The current study examined the role of duration on preference thresholds.

DesignParticipants heard 2, 4 and 6-s segments of a continuous monologue presented successively in pairs. The first segment of each pair was presented at each individuals real-ear or prescribed gain. The second segment was presented with a {+/-}0-12 dB gain adjustment in one of three frequency bands. Participants judged whether the second was "better", "worse" or "no different" from the first.

Study SampleTwenty-nine adults, all with hearing-aid experience.

ResultsThe minimum gain adjustments needed to elicit "better" or "worse" judgments decreased with increasing duration for most adjustments. Inter-participant agreement and intra-participant reliability increased with increasing duration up to 4 s, then remained stable.

ConclusionsProviding longer stimuli improves the likelihood of patients providing reliable judgments of hearing-aid gain adjustments, but the effect is limited, and alternative fitting methods may be more viable for effective hearing-aid personalisation. A Cross-Sectional Examination of Conflict-of-Interest Disclosures of Physician-Authors Publishing in High-Impact US Medical Journals ObjectiveTo assess the accuracy of self-reported financial conflict-of-interest (COI) disclosures in the New England Journal of Medicine (NEJM) and Journal of the American Medical Association (JAMA) within the requisite disclosure period prior to article submission.

DesignCross-sectional investigation.

Data SourcesOriginal clinical-trial research articles published in NEJM (n = 206) or JAMA (n = 188) from January 1 to December 31, 2017; self-reported COI disclosure forms submitted to NEJM or JAMA with the authors published articles; Open Payments website (from database inception; latest search: August 2019).

Main outcome measuresFinancial data reported to Open Payments from 2014 to 2016 (time period that included all subjects requisite disclosure windows) were compared to self-reported disclosure forms submitted to the journals. Payments were defined as those not associated with a research study or formal research funding. Payment types were categorized as "disclosed," "undisclosed," "indeterminate," or "unrelated."

ResultsThirty-one articles from NEJM and 31 articles from JAMA met inclusion criteria. The physician-authors (n = 118) received a combined total of $7.48 million. Of the 106 authors (89.8%) who received payments, 86 (81.1%) received undisclosed payments. The top 23 most highly compensated received $6.32 million, of which $3.00 million (47.6%) was undisclosed. Disclosure rates were the equivalent between the top 23 and the entire sample.

ConclusionsHigh payment amounts, as well as high proportions of undisclosed financial compensation, regardless of amount received, comprised potential COIs for two influential US medical journals. Further research is needed to explain why such high proportions of general payments were undisclosed and whether journals that rely on self-reported COI disclosure need to reconsider their policies. Estimating the impact of Angelman syndrome on parental productivity in Australia using productivity-adjusted life years Angelman syndrome (AS) is a severe neurodevelopmental condition associated with a significant socioeconomic impact. This is the first study to estimate the impact of AS on parental productivity in Australia using cost-of-illness modelling with simulated follow-up over a 10-year period using 2019 as the baseline year. Key data were obtained from a prospective cohort of AS families, peer-reviewed literature, and publicly-available sources. The base-case productivity burden borne by the estimated 330 living parents of the 428 prevalent-persons with AS totalled AUD$1.25 million, corresponding to a loss of 38.42% of PALYs per-parent. This shows that caring for a child with AS has a significant impact on the productivity of affected parents, with a large associated impact on the broader Australian economy.