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8"title","abstract","authors","link","date","subject","source","initial_decision","q0","q1","q2","q3","q4","q5","q6","q7","q8","q9","q10","q11","q12","q13","q14","q15","q16","q17","q18","q19","q20","q21","q22","q23","q24","q25","q26","q27","q28","q29","q30","q31","q32","q33","q34","q35","q36","q37","q38","q39","q40","q41","q42","q43","q44","q45","q46","q47","q48","q49","q50","q51","q52","q53","q54","q55","q56","q57","q58","q59","q60","q61","q62","q63","q64","q65","q66","q67","q68","q69","q70","q71","q72","q73","q74","q75","q76","q77","q78","q79","q80","exclusion_reason","extraction_date","expert_decision","ID","o1"
"Temporal Analysis of Social Determinants Associated with COVID-19 Mortality","This study examines how social determinants associated with COVID-19 mortality change over time. Using US county-level data from July 5 and December 28, 2020, the effect of 19 high-risk factors on COVID-19 mortality rate was quantified at each time point with negative binomial mixed models. Then, these high-risk factors were used as controls in two association studies between 40 social determinants and COVID-19 mortality rates using data from the same time points. The results indicate that counties with certain ethnic minorities and age groups, immigrants, prevalence of diseases like pediatric asthma and diabetes and cardiovascular disease, socioeconomic inequalities, and higher social association are associated with increased COVID-19 mortality rates. Meanwhile, more mental health providers, access to exercise, higher income, chronic lung disease in adults, suicide, and excessive drinking are associated with decreased mortality. Our temporal analysis also reveals a possible decreasing impact of socioeconomic disadvantage and air quality, and an increasing effect of factors like age, which suggests that public health policies may have been effective in protecting disadvantaged populations over time or that analysis utilizing earlier data may have exaggerated certain effects. Overall, we continue to recognize that social inequality still places disadvantaged groups at risk, and we identify possible relationships between lung disease, mental health, and COVID-19 that need to be explored on a clinical level.","Shayom Debopadhaya; John S Erickson; Kristin P Bennett","https://medrxiv.org/cgi/content/short/2021.06.22.21258971","20210625","","medRxiv","Undecided","","","","","","","","","","","","","False","False","","","","","False","False","False","","False","False","False","False","False","False","False","False","False","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2021-06-26","",15357,""
"Pre-existing anxiety, depression, and neurological disability are associated with long COVID: A prospective and longitudinal cohort study of the United Kingdom Multiple Sclerosis Register","Objectives: To assess the prevalence of and factors associated with developing long COVID among patients with multiple sclerosis (MS), a condition which shares the neurological and psychological symptomatology of long COVID Design: Community-based prospective and longitudinal observational study Setting: The United Kingdom (UK) MS Register (UKMSR) COVID-19 study Participants: A national cohort of MS patients with COVID-19 Main outcome measures: Participants used the online questionnaire-based platform of the UKMSR to update their COVID-19 symptoms and recovery status. Questionnaires were date-stamped for estimation of COVID-19 symptom duration. The UKMSR also holds demographic and up-to-date clinical data on participants including comorbidities, MS type, date of MS diagnosis, disease-modifying therapies, web-based Expanded Disability Status Scale scores (a measure of physical disability in MS), and Hospital Anxiety and Depression Scale. The association between these factors and recovery from COVID-19 was assessed using multivariable Cox regression analysis. Results: Out of 7,977 MS patients who participated in the UKMSR COVID-19 study, 599 had COVID-19 and updated their recovery status prospectively. At least 181 participants (31.1%) had long-standing COVID-19 symptoms for [≥]4 weeks and 76 (13.1 %) for [≥]12 weeks. Participants with higher levels of pre-COVID-19 physical disability, participants with anxiety and/or depression prior to COVID-19 onset, and women were less likely to recover from COVID-19. Conclusions: Long COVID appears to affect patients with a pre-existing chronic condition, especially those with physical disabilities or mental health problems disproportionately when compared to reports in the general population. Long COVID research and the development of post-COVID-19 rehabilitation services need to be inclusive of these at-risk populations. Trial Registration: ClinicalTrials.gov: NCT04354519","Afagh Garjani; Rodden M Middleton; Richard Nicholas; Nikos Evangelou","https://medrxiv.org/cgi/content/short/2021.06.25.21259256","20210625","","medRxiv","Undecided","","","","","","","","","","","","","False","False","","","","","False","False","False","","False","False","False","False","False","False","False","False","False","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2021-06-26","",15358,""
"Meta-Analytic Evidence of Depression and Anxiety in Eastern Europe during the COVID-19 Pandemic","Objective: To perform a systematic and meta-analysis on the prevalence rates of mental health symptoms including anxiety and depression during the COVID-19 pandemic in the general population in Eastern Europe, as well as three select sub-populations: students, general healthcare workers, and frontline healthcare workers. Data sources: Studies in PubMed, Embase, Web of Science, Psycinfo, and medRxiv up to February 6, 2021. Eligibility criteria and data analysis: Prevalence rates of mental health symptoms in the general population and key sub-populations during the COVID-19 pandemic in Eastern Europe. Data were pooled using a random-effects meta-analysis to estimate the prevalence rates of anxiety and depression. Results: The meta-analysis identifies and includes 21 studies and 26 independent samples in Eastern Europe. Poland (n=4), Serbia (n=4), Russia (n=3), and Croatia (n=3) had the greatest number of studies. To our knowledge, no studies have been conducted in eleven Eastern European countries including Hungary, Slovakia, and Slovenia. The pooled prevalence of anxiety in 18 studies with 22 samples was 30% (95% CI: 24%-37%) and pooled prevalence of depression in 18 studies with 23 samples was 27% (95% CI: 21%-34%). Implications: The cumulative evidence from the meta-analysis reveals high prevalence rates of clinically significant symptoms during the COVID-19 pandemic in Eastern Europe. The findings suggest evidence of a potential mental health crisis in Eastern Europe during the ongoing COVID-19 pandemic. Our synthesis also reveals a relative lack of studies in certain Eastern European countries as well as high heterogeneities among the existing studies, calling for more effort to achieve evidence-based mental healthcare in Eastern Europe. Keywords: COVID-19; Epidemic; General Population; Healthcare Workers; Frontline Healthcare Workers; Psychiatry Highlights: The pooled prevalence of anxiety and depression were 30% and 27% in Eastern Europe, respectively.","Stephen X. Olivia Zhang; Saylor Olivia Miller; Wen Xu; Allen Yin; Bryan Chen; Andrew Delios; Rebecca K Dong; Richard Z Chen; Roger McIntyre; Xue Wan; Senhu Wang; Jiyao Chen","https://medrxiv.org/cgi/content/short/2021.06.21.21259227","20210625","","medRxiv","Undecided","","","","","","","","","","","","","False","False","","","","","False","False","False","","False","False","False","False","False","False","False","False","False","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2021-06-26","",15359,""
"Risk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK","The impact of long COVID is increasingly recognised, but risk factors are poorly characterised. We analysed questionnaire data on symptom duration from 10 longitudinal study (LS) samples and electronic healthcare records (EHR) to investigate sociodemographic and health risk factors associated with long COVID, as part of the UK National Core Study for Longitudinal Health and Wellbeing. Methods Analysis was conducted on 6,899 adults self-reporting COVID-19 from 45,096 participants of the UK LS, and on 3,327 cases assigned a long COVID code in primary care EHR out of 1,199,812 adults diagnosed with acute COVID-19. In LS, we derived two outcomes: symptoms lasting 4+ weeks and symptoms lasting 12+ weeks. Associations of potential risk factors (age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma) with these two outcomes were assessed, using logistic regression, with meta-analyses of findings presented alongside equivalent results from EHR analyses. Results Functionally limiting long COVID for 12+ weeks affected between 1.2% (age 20), and 4.8% (age 63) of people reporting COVID-19 in LS. The proportion reporting symptoms overall for 12+ weeks ranged from 7.8 (mean age 28) to 17% (mean age 58) and for 4+ weeks 4.2% (age 20) to 33.1% (age 56). Age was associated with a linear increase in long COVID between age 20-70. Being female (LS: OR=1.49; 95%CI:1.24-1.79; EHR: OR=1.51 [1.41-1.61]), poor pre-pandemic mental health (LS: OR=1.46 [1.17-1.83]; EHR: OR=1.57 [1.47-1.68]) and poor general health (LS: OR=1.62 [1.25-2.09]; EHR: OR=1.26; [1.18-1.35]) were associated with higher risk of long COVID. Individuals with asthma also had higher risk (LS: OR=1.32 [1.07-1.62]; EHR: OR=1.56 [1.46-1.67]), as did those categorised as overweight or obese (LS: OR=1.25 [1.01-1.55]; EHR: OR=1.31 [1.21-1.42]) though associations for symptoms lasting 12+ weeks were less pronounced. Non-white ethnic minority groups had lower 4+ week symptom risk (LS: OR=0.32 [0.22-0.47]), a finding consistent in EHR. Associations were not observed for other risk factors. Few participants in the studies had been admitted to hospital (0.8-5.2%). Conclusions Long COVID is clearly distributed differentially according to several sociodemographic and pre-existing health factors. Establishing which of these risk factors are causal and predisposing is necessary to further inform strategies for preventing and treating long COVID.","Ellen J. Thompson; Dylan M. Williams; Alex J. Walker; Ruth E. Mitchell; Claire L. Niedzwiedz; Tiffany C. Yang; Charlotte Huggins; Alex S. F. Kwong; Richard Silverwood; Giorgio Di Gessa; Ruth C. E. Bowyer; Kate Northstone; Bo Hou; Michael J. Green; Brian Dodgeon; Katie J. Doores; Emma Duncan; Frances M. K. Williams; - OpenSAFELY Collaborative; Andrew Steptoe; David J. Porteous; Rosemary R. C. McEachan; Laurie Tomlinson; Ben Goldacre; Praveetha Patalay; George B. Ploubidis; Srinivasa Vittal Katikireddi; Kate Tilling; Christopher T. Rentsch; Nicholas J. Timpson; Nishi Chaturvedi; Claire J. Steves","https://medrxiv.org/cgi/content/short/2021.06.24.21259277","20210625","","medRxiv","Undecided","","","","","","","","","","","","","False","False","","","","","False","False","False","","False","False","False","False","False","False","False","False","False","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2021-06-26","",15360,""
"The impact of epidemics and pandemics on the mental health of healthcare workers: A systematic review","","","https://doi.org/10.3390/ijerph18136695","20210701","","Scopus","Undecided","","","","","","","","","","","","","False","False","","","","","False","False","False","","False","False","False","False","False","False","False","False","False","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2021-06-26","",15361,""
"Suicidal ideation and predictors of psychological distress during the covid-19 pandemic in eswatini: A population-based household telephone survey","","","https://doi.org/10.3390/ijerph18136700","20210701","","Scopus","Undecided","","","","","","","","","","","","","False","False","","","","","False","False","False","","False","False","False","False","False","False","False","False","False","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2021-06-26","",15362,""