metamedian: An R package for meta-analyzing studies reporting medians (preprint)

When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to incorporate primary studies reporting sample medians in meta-analysis, yet there are currently no comprehensive software tools implementing these methods. In this paper, we present the metamedian R package, a freely available and open-source software tool for meta-analyzing primary studies that report sample medians. We summarize the main features of the software and illustrate its application through real data examples involving risk factors for a severe course of COVID-19.

Standard error estimation in meta-analysis of studies reporting medians (preprint)

We consider the setting of an aggregate data meta-analysis of a continuous outcome of interest. When the distribution of the outcome is skewed, it is often the case that some primary studies report the sample mean and standard deviation of the outcome and other studies report the sample median along with the first and third quartiles and/or minimum and maximum values. To perform meta-analysis in this context, a number of approaches have recently been developed to impute the sample mean and standard deviation from studies reporting medians. Then, standard meta-analytic approaches with inverse-variance weighting are applied based on the (imputed) study-specific sample means and standard deviations. In this paper, we illustrate how this common practice can severely underestimate the within-study standard errors, which results in overestimation of between-study heterogeneity in random effects meta-analyses. We propose a straightforward bootstrap approach to estimate the standard errors of the imputed sample means. Our simulation study illustrates how the proposed approach can improve estimation of the within-study standard errors and between-study heterogeneity. Moreover, we apply the proposed approach in a meta-analysis to identify risk factors of a severe course of COVID-19.

Comparison of Mental Health Symptom Changes from pre-COVID-19 to COVID-19 by Sex or Gender: A Systematic Review and Meta-analysis (preprint)

Background: Women and gender-diverse individuals face disproportionate socioeconomic burden during COVID-19. We compared mental health symptom changes since pre-COVID-19 by sex or gender. Methods: We searched MEDLINE, PsycINFO, CINAHL, EMBASE, Web of Science, China National Knowledge Infrastructure, Wanfang, medRxiv, and Open Science Framework December 31, 2019 to March 22, 2021 for studies that reported mental health outcomes prior to and during COVID-19 by sex or gender. We conducted restricted maximum-likelihood random-effects meta-analyses. Results: All 11 included studies (9 unique cohorts) compared females or women to males or men; none included gender-diverse individuals. Continuous symptom change differences were not statistically significant for depression (standardized mean difference [SMD]= 0.15, 95% CI -0.09 to 0.39; 3 studies, 4,159 participants; I2=77%) and stress (SMD= -0.09, 95% CI -0.21 to 0.02; 3 studies, 1,217 participants; I2=0%), but anxiety (SMD= 0.14, 95% CI 0.01 to 0.26; 3 studies, 4,028 participants; I2=34%) and general mental health (SMD= 0.15, 95% CI 0.12 to 0.18; 2 studies, 15,590 participants; I2=0%) worsened more among females or women than males or men. There were no significant differences in changes in proportion above a cut-off: anxiety (difference= 0.00, 95% CI -0.01 to 0.02; 2 studies, 6,684 participants; I2=0%), depression (difference= 0.12, 95% CI -0.04 to 0.28; 1 study, 217 participants), general mental health (difference= -0.03, 95% CI -0.09 to 0.04; 3 studies, 18,985 participants; I2=94%), stress (difference= 0.04, 95% CI -0.11 to 0.18; 1 study, 217 participants). Interpretation: Mental health outcomes did not differ or were somewhat worse among women than men.

Comparison of Mental Health Symptoms prior to and during COVID-19: Evidence from a Living Systematic Review and Meta-analysis (preprint)

ABSTRACT Objectives The rapid pace, high volume, and limited quality of mental health evidence being generated during COVID-19 poses a barrier to effective decision-making. The objective of the present report is to compare mental health outcomes assessed during COVID-19 to outcomes prior to COVID-19 in the general population and other population groups. Design Living systematic review. Data Sources MEDLINE (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Web of Science Core Collection: Citation Indexes, China National Knowledge Infrastructure, Wanfang, medRxiv (preprints), and Open Science Framework Preprints (preprint server aggregator). The initial search was conducted on April 13, 2020 with ongoing weekly updates. Eligibility criteria for selecting studies For this report, we included studies that compared general mental health, anxiety symptoms, or depression symptoms, assessed January 1, 2020 or later, to the same outcomes collected between January 1, 2018 and December 31, 2019. We required ≥ 90% of participants pre-COVID-19 and during COVID-19 to be the same or the use of statistical methods to address missing data. For population groups with continuous outcomes for at least three studies in an outcome domain, we conducted restricted maximum-likelihood random-effects meta-analyses. Results As of March 22, 2021, we had identified 36 unique eligible studies with data from 33 cohorts. All reported COVID-19 outcomes between March and June 2020, and 3 studies also reported outcomes between September and November 2020. Estimates of changes in general mental health were close to zero in the general population (standardized mean difference [SMD] = 0.02, 95% CI -0.11 to 0.16, I 2 = 94.6%; 4 studies, N = 19,707) and among older adults (SMD = 0.02, 95% CI -0.11 to 0.16, I 2 = 90.4%; 4 studies, N = 5,520) and university students (SMD = -0.01, 95% CI -0.33 to 0.30, I 2 = 92.0%; 3 studies, N = 3,372). Changes in anxiety symptoms were close to zero and not statistically significant in university students (SMD = 0.00, 95% CI - 0.35 to 0.36, I 2 = 95.4%; 5 studies, N = 1,537); women or females (SMD = 0.02, 95% CI -0.35 to 0.39, I 2 = 92.3%; 3 studies, N = 2,778); and men or males (SMD = 0.07, 95% CI -0.01 to 0.15; I 2 = 0.01%; 3 studies, N = 1,250); anxiety symptoms increased, however, among people with pre-existing medical conditions (SMD = 0.27, 95% CI 0.01 to 0.54, I 2 = 91.0%; 3 studies, N = 2,053). Changes in depression symptoms were close to zero or small and not statistically significant among university students (SMD = 0.19, 95% CI -0.08 to 0.45, I 2 = 91.8%; 5 studies, N = 1,537); people with pre-existing medical conditions (SMD = 0.01, 95% CI -0.15 to 0.17, I 2 = 14.9%; 3 studies, N = 2,006); women or females (SMD = 0.21, 95% CI -0.14 to 0.55, I 2 = 91.2%; 3 studies, N = 2,843); and men or males (SMD = 0.00, 95% CI -0.21 to 0.22; I 2 = 92.3%; 4 studies, N = 3,661). In 3 studies with data from both March to June 2020 and September to November 2020, symptoms were unchanged from pre-COVID-19 at both time points or there were increases at the first assessment that had largely dissipated by the second assessment. Conclusions Evidence does not suggest a widespread negative effect on mental health symptoms in COVID-19, although it is possible that gaps in data have not allowed identification of changes in some vulnerable groups. Continued updating is needed as evidence accrues. Funding Canadian Institutes of Health Research (CMS-171703; MS1-173070); McGill Interdisciplinary Initiative in Infection and Immunity Emergency COVID-19 Research Fund (R2-42). Registration PROSPERO (CRD42020179703); registered on April 17, 2020.

Effects of COVID-19 Mental Health Interventions among Community-based Children, Adolescents, and Adults: A Living Systematic Review of Randomised Controlled Trials (preprint)

Background: Scalable interventions to address COVID-19 mental health are needed. Our objective was to assess effects of mental health interventions for community-based children, adolescents, and adults. Methods: We searched 9 databases (2 Chinese-language) from December 31, 2019 to March 22, 2021. We included randomised controlled trials with non-hospitalised, non-quarantined participants of interventions to address COVID-19 mental health challenges. We synthesized results descriptively but did not pool quantitatively due to substantial heterogeneity of populations and interventions and concerns about risk of bias. Findings: We identified 9 eligible trials, including 3 well-conducted, well-reported trials that tested interventions designed specifically for COVID-19 mental health challenges, plus 6 trials of standard interventions (e.g., individual or group therapy, expressive writing, mindfulness recordings) minimally adapted for COVID-19, all with risk of bias concerns. Among the 3 COVID-19-specific intervention trials, one (N = 670) found that a self-guided, internet-based cognitive-behavioural intervention targeting dysfunctional COVID-19 worry significantly reduced COVID-19 anxiety (standardized mean difference [SMD] 0.74, 95% CI 0.58 to 0.90) and depression symptoms (SMD 0.38, 95% CI 0.22 to 0.55) in Swedish general population participants. A lay-delivered telephone intervention for homebound older adults in the United States (N = 240) and a peer-moderated education and support intervention for people with a rare autoimmune condition from 12 countries (N = 172) significantly improved anxiety (SMD 0.35, 95% CI 0.09 to 0.60; SMD 0.31, 95% CI 0.03 to 0.58) and depressive symptoms (SMD 0.31, 95% CI 0.05 to 0.56; SMD 0.31, 95% CI 0.07 to 0.55) 6-weeks post-intervention, but these were not significant immediately post-intervention. No trials in children or adolescents were identified. Interpretation: Internet-based programs for the general population and lay- or peer-delivered interventions for vulnerable groups may be effective, scalable options for public mental health in COVID-19. More well-conducted trials, including for children and adolescents, are needed.

Performance of Saliva, Oropharyngeal Swabs, and Nasal Swabs for SARS-CoV-2 Molecular Detection: A Systematic Review and Meta-analysis (preprint)

BackgroundNasopharyngeal (NP) swabs are considered the highest-yield sample for diagnostic testing for respiratory viruses, including SARS-CoV-2. The need to increase capacity for SARS-CoV-2 testing in a variety of settings, combined with shortages of sample collection supplies, have motivated a search for alternative sample types with high sensitivity. We systematically reviewed the literature to understand the performance of alternative sample types compared to NP swabs. MethodsWe systematically searched PubMed, Google Scholar, medRxiv, and bioRxiv (last retrieval October 1st, 2020) for comparative studies of alternative specimen types [saliva, oropharyngeal (OP), and nasal (NS) swabs] versus NP swabs for SARS-CoV-2 diagnosis using nucleic acid amplification testing (NAAT). A logistic-normal random-effects meta-analysis was performed to calculate % positive alternative-specimen, % positive NP, and % dual positives overall and in sub-groups. The QUADAS 2 tool was used to assess bias. ResultsFrom 1,253 unique citations, we identified 25 saliva, 11 NS, 6 OP, and 4 OP/NS studies meeting inclusion criteria. Three specimen types captured lower % positives [NS (0.82, 95% CI: 0.73-0.90), OP (0.84, 95% CI: 0.57-1.0), saliva (0.88, 95% CI: 0.81 - 0.93)] than NP swabs, while combined OP/NS matched NP performance (0.97, 95% CI: 0.90-1.0). Absence of RNA extraction (saliva) and utilization of a more sensitive NAAT (NS) substantially decreased alternative-specimen yield. ConclusionsNP swabs remain the gold standard for diagnosis of SARS-CoV-2, although alternative specimens are promising. Much remains unknown about the impact of variations in specimen collection, processing protocols, and population (pediatric vs. adult, late vs. early in disease course) and head-to head studies of sampling strategies are urgently needed.

Molecular Mimicry Map (3M) of SARS-CoV-2: Prediction of potentially immunopathogenic SARS-CoV-2 epitopes via a novel immunoinformatic approach (preprint)

Currently, more than 33 million peoples have been infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more than a million people died from coronavirus disease 2019 (COVID-19), a disease caused by the virus. There have been multiple reports of autoimmune and inflammatory diseases following SARS-CoV-2 infections. There are several suggested mechanisms involved in the development of autoimmune diseases, including cross-reactivity (molecular mimicry). A typical workflow for discovering cross-reactive epitopes (mimotopes) starts with a sequence similarity search between protein sequences of human and a pathogen. However, sequence similarity information alone is not enough to predict cross-reactivity between proteins since proteins can share highly similar conformational epitopes whose amino acid residues are situated far apart in the linear protein sequences. Therefore, we used a hidden Markov model-based tool to identify distant viral homologs of human proteins. Also, we utilized experimentally determined and modeled protein structures of SARS-CoV-2 and human proteins to find homologous protein structures between them. Next, we predicted binding affinity (IC50) of potentially cross-reactive T-cell epitopes to 34 MHC allelic variants that have been associated with autoimmune diseases using multiple prediction algorithms. Overall, from 8,138 SARS-CoV-2 genomes, we identified 3,238 potentially cross-reactive B-cell epitopes covering six human proteins and 1,224 potentially cross-reactive T-cell epitopes covering 285 human proteins. To visualize the predicted cross-reactive T-cell and B-cell epitopes, we developed a web-based application "Molecular Mimicry Map (3M) of SARS-CoV-2" (available at https://ahs2202.github.io/3M/). The web application enables researchers to explore potential cross-reactive SARS-CoV-2 epitopes alongside custom peptide vaccines, allowing researchers to identify potentially suboptimal peptide vaccine candidates or less ideal part of a whole virus vaccine to design a safer vaccine for people with genetic and environmental predispositions to autoimmune diseases. Together, the computational resources and the interactive web application provide a foundation for the investigation of molecular mimicry in the pathogenesis of autoimmune disease following COVID-19.

Can we predict the severe course of COVID-19? A systematic review and meta-analysis of indicators of clinical outcome. (preprint)

Background: COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19. Methods: We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31st 2020. Random-effects meta- analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies. Results: Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 - 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73). Discussion: This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors in predicting severe COVID-19 outcomes and will inform decision analytical tools to support clinical decision-making.

Evaluation of a home-based 7-day infection control strategy for healthcare workers following high-risk exposure to SARS-CoV-2: a cohort study (preprint)

Background: Evidence-based infection control strategies are needed for healthcare workers (HCWs) following high-risk exposure to SARS-CoV-2. This study evaluated the negative predictive value (NPV) of a home-based 7-day infection control strategy. Methods: HCWs advised by their Infection Control or Occupational Health officer to self-isolate due to a high-risk SARS-CoV-2 exposure were enrolled between May-September 2020. The strategy consisted of symptom-triggered nasopharyngeal SARS-CoV-2 RNA testing from day 0-6 post exposure, followed by standardized home-based nasopharyngeal swab and saliva testing on day 7. The NPV of this strategy was calculated for i) clinical COVID-19 diagnosis from day 8-14 post exposure, and for ii) asymptomatic SARS-CoV-2 detected by standardized nasopharyngeal swab and saliva specimens collected at days 9-10 and 14 post exposure. Interim results are reported in the context of a second wave threatening this essential workforce. Results: Among 30 HCWs enrolled to date (age 31{+/-}9 years, 24 [80.0%] female), 3 were diagnosed with COVID-19 by day 14 post exposure (secondary attack rate 10.0%), with all cases detected by the 7-day infection control strategy: NPV for subsequent clinical COVID-19 or asymptomatic SARS-CoV-2 detection by day 14 was 100.0% (95%CI: 93.1-100.0%). Interpretation: Among HCWs with high-risk exposure to SARS-CoV-2, a home-based 7-day infection control strategy may have a high NPV for subsequent COVID-19 and asymptomatic SARS-CoV-2 detection. While ongoing data collection and data sharing are needed to improve the precision of the estimated NPV, we report interim results to inform infection control strategies in light of a second wave threatening this essential workforce.

Comparison of Mental Health Symptoms Prior to and During COVID-19 among Patients with Systemic Sclerosis from Four Countries: A Scleroderma Patient-centered Intervention Network (SPIN) Cohort Study (preprint)

BackgroundNo studies have reported comparisons of mental health symptoms prior to and during COVID-19 in vulnerable populations. Objectives were to compare anxiety and depression symptoms among people with a pre-existing medical condition, the autoimmune disease systemic sclerosis (SSc; scleroderma), including continuous change scores, proportion with change [≥] 1 minimal clinically important difference (MCID), and factors associated with changes, including country. MethodsPre-COVID-19 Scleroderma Patient-centered Intervention Network Cohort data were linked to COVID-19 data collected April 9 to April 27, 2020. Anxiety symptoms were assessed with the PROMIS Anxiety 4a v1.0 scale (MCID = 4 points) and depression symptoms with the Patient Health Questionnaire-8 (MCID = 3 points). Multiple linear and logistic regression were used to assess factors associated with continuous change and change[≥] 1 MCID. FindingsAmong 435 participants (Canada = 98; France = 159; United Kingdom = 50; United States = 128), mean anxiety symptoms increased 4.9 points (95% confidence interval [CI] 4.0 to 5.7). Depression symptom change was negligible (0.3 points; 95% CI -0.7 to 0.2). Compared to France, adjusted scores from the United States and United Kingdom were 3.8 points (95% CI 1.7 to 5.9) and 2.9 points higher (95% CI 0.0 to 5.7); scores for Canada were not significantly different. Odds of increasing by [≥] 1 MCID were twice as high for the United Kingdom (2.0, 95% CI 1.0 to 4.2) and United States (1.9, 95% CI 1.1 to 3.2). Participants who used mental health services pre-COVID had adjusted increases 3.7 points (95% CI 1.7 to 5.7) less than other participants. InterpretationAnxiety symptoms, but not depression symptoms, increased dramatically during COVID-19 among people with a pre-existing medical condition. Increase was larger in the United Kingdom and United States than in Canada and France but substantially less for people with pre-COVID-19 mental health treatment. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe referred to a living systematic review that is evaluating mental health changes from pre-COVID-19 to COVID-19 by searching 7 databases, including 2 Chinese language databases, plus preprint servers, with daily updates (https://www.depressd.ca/covid-19-mental-health). As of June 13, 2020, only 5 studies had compared mental health symptoms prior to and during COVID-19. In 4 studies of university students, there were small increases in depression or general mental health symptoms but minimal or no increases in anxiety symptoms. A general population study from the United Kingdom reported a small increase in general mental health symptoms but did not differentiate between types of symptoms. No studies have reported changes from pre-COVID-19 among people vulnerable due to pre-existing medical conditions. No studies have compared mental health changes between countries, despite major differences in pandemic responses. Added value of this studyWe evaluated changes in anxiety and depression symptoms among 435 participants with the autoimmune condition systemic sclerosis and compared results from Canada, France, the United Kingdom, and the United States. To our knowledge, this is the first study to compare mental health symptoms prior to and during COVID-19 in any vulnerable population. These are the first data to document the substantial degree to which anxiety symptoms have increased and the minimal changes in depression symptoms among vulnerable individuals. It is also the first study to examine the association of symptom changes with country of residence and to identify that people receiving pre-COVID-19 mental health services may be more resilient and experience less substantial symptom increases than others. Implications of all the available evidenceAlthough this was an observational study, it provided evidence that vulnerable people with a pre-existing medical condition have experienced substantially increased anxiety symptoms and that these increases appear to be associated with where people live and, possibly, different experiences of the COVID-19 pandemic across countries. By comparing with evidence from university samples, which found that depression symptoms were more prominent, these data underline the need for accessible interventions tailored to specific needs of different populations. They also suggest that mental health treatments may help people to develop skills or create resilience, which may reduce vulnerability to major stressors such as COVID-19.