Evaluation of publication bias for 12 clinical trials of molnupiravir to treat SARS-CoV-2 infection in 13 694 patients with meta-analysis.

In response to the COVID-19 pandemic, Merck Sharp & Dohme (MSD) acquired the global licensing rights for the antiviral molnupiravir, promising affordable access via licensing deals. Numerous Indian pharmaceutical companies subsequently conducted trials of the drug. Registered trials of molnupiravir were searched on the Clinical Trials Registry-India (CTRI) and efforts made to detect resulting public data. Per the CTRI, 12 randomized trials of molnupiravir were conducted in 13 694 Indian patients, from mid-2021. By August 2022, only a preprint and medical conference presentation had resulted. Additionally, two trials were mentioned in press releases suggesting failure of treatment. The available data contain unexplained results that differ significantly from both the PANORAMIC and MSD MOVe-OUT trials. Approximately one-third of the global data on molnupiravir remain unpublished. We conducted a meta-analysis with four studies that provided results and observed that molnupiravir does not have a significant benefit for hospitalizations.

Interstitial lung disease independently associated with higher risk for COVID-19 severity and mortality: A meta-analysis of adjusted effect estimates.

OBJECTIVE: The aim of this study was to address the association between interstitial lung disease and the risk for severity and mortality among patients with coronavirus disease 2019 (COVID-19). METHODS: The electronic databases of PubMed, Web of Science and EMBASE were systematically searched. The pooled effect size with 95 % confidence interval (CI) was computed by a random-effects meta-analysis model. Heterogeneity test, sensitivity analysis, subgroup analysis, meta-regression analysis, Begg's test and Egger's test were performed. RESULTS: A total of sixteen eligible studies with 217,260 COVID-19 patients were enrolled in this meta-analysis. The findings based on adjusted effect estimates indicated that pre-existing interstitial lung disease was significantly associated with higher risk for COVID-19 severity (pooled effect = 1.34 [95 % CI: 1.16-1.55]) and mortality (pooled effect = 1.26 [95 % CI: 1.09-1.46]). Consistent results were observed in the subgroup analysis stratified by sample size, age, the percentage of male patients, study design, setting, the methods for adjustment and the factors for adjustment. The results of meta-regression demonstrated that sample size, age and region might be the potential sources of heterogeneity. Sensitivity analysis exhibited that our results were stable and robust. No publication bias was observed in Egger's test and Begg's test. CONCLUSION: This meta-analysis on the basis of adjusted effect estimates demonstrated that pre-existing interstitial lung disease was independently associated with significantly higher risk for COVID-19 severity and mortality.

Clinical trial registration during COVID-19 and beyond in the African context: what have we learned?

Since the outbreak of COVID-19, many lives have been impacted especially on the African continent which is already fighting the burden of multiple diseases of poverty. However, clinical research has offered hope for treatment and prevention options for this infectious disease. Despite many COVID-19 clinical trials conducted globally, three countries in Africa account for more than 80% of all trials from the continent registered trials in clinical trial registries. This indicates geographic disparity among COVID-19 research in Africa. From the perspective of clinical trial registration, transparency in clinical research and the availability of data became important for making informed decisions to manage the pandemic. Registries serve as a source of planned, ongoing, and completed trials while allowing efficient funding allocation for research that would not duplicate efforts. Additionally, research gaps can be identified, which provide opportunities for collaboration among researchers. Therefore, a critical lesson learnt during this pandemic is that clinical trial registration is important in facilitating the process of tracking changes made to protocols and minimizing publication bias, thereby promoting and advocating for clinical research transparency. Moreover, registration in a clinical trial registry is a condition for publication and allows for trial summary results to be publicly available. Adhering to the principle of results sharing is especially important for the rapidly growing clinical research activities racing to find evidence-based interventions to end the COVID-19 pandemic.

[Citation misuse and its effects on public health]. / Le mésusage des citations et ses conséquences en médecine.

In order to effectively contribute to scientific knowledge, biomedical observations have to be validated and debated by scientists in the relevant field. Along this debate that mainly takes place in the scientific literature, citation of previous studies plays a major role. However, only a few academic studies have quantitatively evaluated the suitability and accuracy of scientific citations. Here we review these academic studies. Two types of misuse have been pointed out: Citation bias and citation distortion. First, scientific citations favor positive results and those supporting authors' conclusion. Second, many statements linked to a reference actually misrepresent the referenced findings. About 10% of all citations in biomedicine are strongly inaccurate and misleading for the reader. Finally, we give two examples illustrating how some citation misuses do affect public health: The opioid crisis in the USA and the unjustified fostering of hydroxychloroquine for Covid-19 treatment in France.

TITLE: Le mésusage des citations et ses conséquences en médecine. ABSTRACT: Les observations biomédicales ne deviennent une source de connaissance qu'après un débat entre chercheurs. Au cours de ce débat, la citation des études antérieures tient un rôle majeur, mais les travaux académiques qui en évaluent l'usage sont rares. Ils ont cependant pu révéler deux types de problèmes : les biais de citation et les écarts de sens entre l'étude antérieure citée et ce qu'en dit l'article citant. Dans cette revue, nous synthétisons ces travaux et en dégageons les principales caractéristiques : les études favorables à la conclusion des auteurs citants sont plus souvent citées que celles qui les questionnent ; des écarts de sens majeurs affectent environ 10 % des citations. Nous illustrons par deux exemples les conséquences de ce mésusage des citations.

Protocol: Benefits and harms of remdesivir for COVID-19 in adults: A systematic review with meta-analysis.

BACKGROUND: Effective drug treatments for Covid-19 are needed to decrease morbidity and mortality for the individual and to alleviate pressure on health care systems. Remdesivir showed promising results in early randomised trials but subsequently a large publicly funded trial has shown less favourable results and the evidence is interpreted differently in clinical guidelines. Systematic reviews of remdesivir have been published, but none have systematically searched for unpublished data, including regulatory documents, and assessed the risk of bias due to missing evidence. METHODS: We will conduct a systematic review of randomised trials comparing remdesivir to placebo or standard of care in any setting. We will include trials regardless of the severity of disease and we will include trials examining remdesivir for indications other than Covid-19 for harms analyses. We will search websites of regulatory agencies, trial registries, bibliographic databases, preprint servers and contact trial sponsors to obtain all available data, including unpublished clinical data, for all eligible trials. Our primary outcomes will be all-cause mortality and serious adverse events. Our secondary outcomes will be length of hospital stay, time to death, severe disease, and adverse events. We will assess the risk of bias using the Cochranes Risk of Bias 2 tool and the risk of bias due to missing evidence (e.g. publication bias, selective reporting bias) using the ROB-ME tool. Where appropriate we will synthesise study results by conducting random-effects meta-analysis. We will present our findings in a Summary of Findings table and rate the certainty of the evidence using the GRADE approach. DISCUSSION: By conducting a comprehensive systematic review including unpublished data (where available), we expect to be able to provide valuable information for patients and clinicians about the benefits and harms of remdesivir for the treatment of Covid-19. This will help to ensure optimal treatment for individual patients and optimal utilisation of health care resources. SYSTEMATIC REVIEW REGISTRATION: CRD42021255915.

Coronavirus disease 2019 pandemic and pregnancy and neonatal outcomes in general population: A living systematic review and meta-analysis (updated Aug 14, 2021).

INTRODUCTION: Conflicting reports of increases and decreases in rates of preterm birth (PTB) and stillbirth in the general population during the coronavirus disease 2019 (COVID-19) pandemic have surfaced. The objective of our study was to conduct a living systematic review and meta-analyses of studies reporting pregnancy and neonatal outcomes by comparing the pandemic and pre-pandemic periods. MATERIAL AND METHODS: We searched PubMed and Embase databases, reference lists of articles published up until August 14, 2021 and included English language studies that compared outcomes between the COVID-19 pandemic time period and the pre-pandemic time periods. Risk of bias was assessed using the Newcastle-Ottawa scale. We conducted random-effects meta-analysis using the inverse variance method. RESULTS: Forty-five studies with low-to-moderate risk of bias, reporting on 1 843 665 pregnancies during the pandemic period and 23 564 552 pregnancies during the pre-pandemic period, were included. There was significant reduction in unadjusted estimates of PTB (35 studies, unadjusted odds ratio [uaOR] 0.95, 95% CI 0.92-0.98), but not in adjusted estimates (six studies, adjusted OR [aOR] 0.95, 95% CI 0.80-1.13). This reduction was noted in studies from single centers/health areas (25 studies, uaOR 0.90, 95% CI 0.86-0.96) but not in regional/national studies (10 studies, uaOR 0.99, 95% CI 0.95-1.02). There was reduction in spontaneous PTB (six studies, uaOR 0.89, 95% CI 0.81-0.96) and induced PTB (five studies, uaOR 0.89, 95% CI 0.81-0.97). There was no difference in the odds of stillbirth between the pandemic and pre-pandemic time periods (24 studies, uaOR 1.11, 95% CI 0.97-1.26 and four studies, aOR 1.06, 95% CI 0.81-1.38). There was an increase in mean birthweight during the pandemic period compared with the pre-pandemic period (six studies, mean difference 17 g, 95% CI 7-28 g). The odds of maternal mortality were increased (four studies, uaOR 1.15, 95% CI 1.05-1.26); however, only unadjusted estimates were available and the result was mostly influenced by one study from Mexico. There was significant publication bias for the outcome of PTB. CONCLUSIONS: The COVID-19 pandemic may be associated with a reduction in PTB; however, referral bias cannot be excluded. There was no statistically significant difference in stillbirth between pandemic and pre-pandemic periods.

Diagnostic performance of deep-learning-based screening methods for diabetic retinopathy in primary care-A meta-analysis.

BACKGROUND: Diabetic retinopathy (DR) affects 10-24% of patients with diabetes mellitus type 1 or 2 in the primary care (PC) sector. As early detection is crucial for treatment, deep learning screening methods in PC setting could potentially aid in an accurate and timely diagnosis. PURPOSE: The purpose of this meta-analysis was to determine the current state of knowledge regarding deep learning (DL) screening methods for DR in PC. DATA SOURCES: A systematic literature search was conducted using Medline, Web of Science, and Scopus to identify suitable studies. STUDY SELECTION: Suitable studies were selected by two researchers independently. Studies assessing DL methods and the suitability of these screening systems (diagnostic parameters such as sensitivity and specificity, information on datasets and setting) in PC were selected. Excluded were studies focusing on lesions, applying conventional diagnostic imaging tools, conducted in secondary or tertiary care, and all publication types other than original research studies on human subjects. DATA EXTRACTION: The following data was extracted from included studies: authors, title, year of publication, objectives, participants, setting, type of intervention/method, reference standard, grading scale, outcome measures, dataset, risk of bias, and performance measures. DATA SYNTHESIS AND CONCLUSION: The summed sensitivity of all included studies was 87% and specificity was 90%. Given a prevalence of DR of 10% in patients with DM Type 2 in PC, the negative predictive value is 98% while the positive predictive value is 49%. LIMITATIONS: Selected studies showed a high variation in sample size and quality and quantity of available data.

Opportunities and Challenges of Observational Studies and Randomized Controlled Trials for Evaluating the Therapeutic Efficacy of COVID-19 Convalescent Plasma.

Large randomized controlled trials (RCTs) remain the gold standard for evaluating treatment efficacy. However, observational studies, including non-randomized cohort studies, as well as small RCTs have gained increasing attention especially during the SARS-CoV-2 pandemic where critical evaluation of limited therapeutic options are sought to improve patient care while awaiting results for subsequent RCTs. As the authors have previously discussed, RCTs and observational studies are complementary approaches which often appear synergistic with one another. While not all real-world studies are the same, the results of observational studies are notoriously subject to both known and unknown confounding factors. The utilization of COVID-19 Convalescent Plasma is a timely illustration of evaluating the efficacy and safety of a COVID-19 therapy given the dangerous and often lethal effects of the virus and the limited approved therapeutic options for the disease. While awaiting the results of large RCTS of convalescent plasma, serval observational cohorts and small RCTs have attempted to assess the efficacy and safety of this approach with very mixed results. Among the likely reasons for this failure to provide a definitive answer concerning the value of convalescent plasma are the many limitations inherent to addressing treatment efficacy in non-randomized studies. While such studies are often able to capture information on large numbers of individuals rapidly, it is important to understand that although larger numbers may enhance the precision of estimates provided, larger numbers, in and of themselves, do not increase the accuracy of estimates due to patient selection and other biases. At the same time, both observational studies and small RCTS are at risk for publication bias due to investigator, reviewer and editorial bias toward positive studies. In this commentary we discuss the advantages and limitations of these methodologic approaches when addressing urgently needed evidence on the effectiveness and safety of therapies in a crisis such as the COVID-19 pandemic.

Methodological assessment of systematic reviews and meta-analyses on COVID-19: A meta-epidemiological study.

RATIONALE, AIMS, AND OBJECTIVES: COVID-19 has caused an ongoing public health crisis. Many systematic reviews and meta-analyses have been performed to synthesize evidence for better understanding this new disease. However, some concerns have been raised about rapid COVID-19 research. This meta-epidemiological study aims to methodologically assess the current systematic reviews and meta-analyses on COVID-19. METHODS: We searched in various databases for systematic reviews with meta-analyses published between 1 January 2020 and 31 October 2020. We extracted their basic characteristics, data analyses, evidence appraisal, and assessment of publication bias and heterogeneity. RESULTS: We identified 295 systematic reviews on COVID-19. The median time from submission to acceptance was 33 days. Among these systematic reviews, 73.9% evaluated clinical manifestations or comorbidities of COVID-19. Stata was the most used software programme (43.39%). The odds ratio was the most used effect measure (34.24%). Moreover, 28.14% of the systematic reviews did not present evidence appraisal. Among those reporting the risk of bias results, 14.64% of studies had a high risk of bias. Egger's test was the most used method for assessing publication bias (38.31%), while 38.66% of the systematic reviews did not assess publication bias. The I2 statistic was widely used for assessing heterogeneity (92.20%); many meta-analyses had high values of I2 . Among the meta-analyses using the random-effects model, 75.82% did not report the methods for model implementation; among those meta-analyses reporting implementation methods, the DerSimonian-Laird method was the most used one. CONCLUSIONS: The current systematic reviews and meta-analyses on COVID-19 might suffer from low transparency, high heterogeneity, and suboptimal statistical methods. It is recommended that future systematic reviews on COVID-19 strictly follow well-developed guidelines. Sensitivity analyses may be performed to examine how the synthesized evidence might depend on different methods for appraising evidence, assessing publication bias, and implementing meta-analysis models.

Drawing Reproducible Conclusions from Observational Clinical Data with OHDSI.

OBJECTIVE: The current observational research literature shows extensive publication bias and contradiction. The Observational Health Data Sciences and Informatics (OHDSI) initiative seeks to improve research reproducibility through open science. METHODS: OHDSI has created an international federated data source of electronic health records and administrative claims that covers nearly 10% of the world's population. Using a common data model with a practical schema and extensive vocabulary mappings, data from around the world follow the identical format. OHDSI's research methods emphasize reproducibility, with a large-scale approach to addressing confounding using propensity score adjustment with extensive diagnostics; negative and positive control hypotheses to test for residual systematic error; a variety of data sources to assess consistency and generalizability; a completely open approach including protocol, software, models, parameters, and raw results so that studies can be externally verified; and the study of many hypotheses in parallel so that the operating characteristics of the methods can be assessed. RESULTS: OHDSI has already produced findings in areas like hypertension treatment that are being incorporated into practice, and it has produced rigorous studies of COVID-19 that have aided government agencies in their treatment decisions, that have characterized the disease extensively, that have estimated the comparative effects of treatments, and that the predict likelihood of advancing to serious complications. CONCLUSIONS: OHDSI practices open science and incorporates a series of methods to address reproducibility. It has produced important results in several areas, including hypertension therapy and COVID-19 research.

Meta-Analysis of Correlations between Altmetric Attention Score and Citations in Health Sciences.

INTRODUCTION: In recent years, several controversial reports of the correlation between altmetric score and citations have been published (range: -0.2 to 0.8). We conducted a meta-analysis to provide an in-depth statistical analysis of the correlation between altmetric score and number of citations in the field of health sciences. METHODS: Three online databases (Web of Science, Scopus, and PubMed) were systematically searched, without language restrictions, from the earliest publication date available through February 29, 2020, using the keywords "altmetric," "citation," and "correlation." Grey literature was also searched via WorldCat, Open Grey, and Google Scholar (first 100 hits only). All studies in the field of health sciences that reported on this correlation were included. Effect sizes were calculated using Fisher's z transformation of correlations. Subgroup analyses based on citation source and sampling methods were performed. RESULTS: From 27 included articles, 8 articles comprise several independent studies. The total sample size was 9,943 articles comprised of 35 studies. The overall pooled effect size was 0.19 (95% confidence interval 0.13 to 0.26). Bivariate partial prediction of interaction between effect size, citation source, and sampling method showed a greater effect size with Web of Science compared with Scopus and Dimensions. Egger's regression showed a marginally nonsignificant publication bias (p = 0.055), and trim-and-fill analysis estimated one missing study in this meta-analysis. CONCLUSION: In health sciences, currently altmetric score has a positive but weak correlation with number of citations (pooled correlation = 0.19, 95% C.I 0.12 to 0.25). We emphasize on future examinations to assess changes of correlation pattern between altmetric score and citations over time.

Unfavorable hydroxychloroquine COVID-19 research associated with authors having a history of political party donations.

We explored the degree to which political bias in medicine and study authors could explain the stark variation in Hydroxychloroquine (HCQ)/Chloroquine (CQ) study favorability in the US compared to the rest of the world. COVID-19/SARS-CoV-2 preprint and published papers between January 1, 2020-July 26, 2020 with Hydroxychloroquine and/or Chloroquine; 267 met study criteria, 68 from the US. A control subset was selected. HCQ/CQ study result favorability (favorable, unfavorable, or neutral) was noted. First and last main authors of each US study were entered into FollowTheMoney.org Website, extracting any history of political party donation. Of all US studies (68 total), 39/68 (57.4%) were unfavorable, with only 7/68 (10.3%) of US studies yielding favorable results-compared to 199 non-US studies, 66/199 (33.2%) unfavorable, 69/199 (34.7%) favorable, and 64/199 (32.2%) neutral. Studies with at least one US main author were 20.4% (SE 0.053, P < 0.05) more likely to report unfavorable results than non-US studies. US Studies with at least one main author donating to any political party were 25.6% (SE 0.085, P < 0.01) more likely to have unfavorable results. US studies with at least one author donating to the Democratic party were 20.4% (SE 0.045, P < 0.05) more likely to have unfavorable results. US authors were more likely to publish studies with medically harmful conclusions than non-US authors. Cardiology-specific HCQ/CQ studies were 44.2% more likely to yield harmful conclusions (P < 0.01). Inaccurate propagation of HCQ/CQ cardiac adverse effects with individual scientific author political bias has contributed to unfavorable US HCQ/CQ publication patterns and political polarization of the medications.

CT findings and dynamic imaging changes of COVID-19 in 2908 patients: a systematic review and meta-analysis.

Quick screening patients with COVID-19 is the most important way of controlling transmission by isolation and medical treatment. Chest computed tomography (CT) has been widely used during the initial screening process, including pneumonia diagnosis, severity assessment, and differential diagnosis of COVID-19. The course of COVID-19 changes rapidly. Serial CT imaging could observe the distribution, density, and range of lesions dynamically, monitor the changes, and then guide towards appropriate treatment. The aim of the review was to explore the chest CT findings and dynamic CT changes of COVID-19 using systematic evaluation methods, instructing the clinical imaging diagnosis. A systematic literature search was performed. The quality of included literature was evaluated with a quality assessment tool, followed by data extraction and meta-analysis. Homogeneity and publishing bias were analyzed. A total of 109 articles were included, involving 2908 adults with COVID-19. The lesions often occurred in bilateral lungs (74%) and were multifocal (77%) with subpleural distribution (81%). Lesions often showed ground-glass opacity (GGO) (68%), followed by GGO with consolidation (48%). The thickening of small vessels (70%) and thickening of intralobular septum (53%) were also common. The dynamic changes of chest CT manifestations showed that lesions were absorbed and improved gradually after reaching the peak (80%), had progressive deterioration (55%), were absorbed and improved gradually (46%), fluctuated (22%), or remained stable (26%). The review showed the common and key CT features and the dynamic imaging change patterns of COVID-19, helping with timely management during COVID-19 pandemic.

Clinical, epidemiological, laboratory, and radiological characteristics of novel Coronavirus (2019-nCoV) in retrospective studies: A systemic review and meta-analysis.

BACKGROUND: In December 2019, a novel pneumonia related to the 2019 coronavirus unexpectedly developed in Wuhan, China. We aimed to review data of the novel Coronavirus (2019-nCoV) by analyzing all the published retrospective studies on the clinical, epidemiological, laboratory, and radiological characteristics of patients with 2019-nCoV. METHODS: We searched in four bibliographic databases PubMed, Scopus, Embase, and Web of Science) for studies March 10, 2020 focused on the clinical, epidemiological, laboratory, and radiological characteristics of patients with 2019-nCoV for meta-analysis. The Newcastle-Ottawa Scale was used to quality assessment, and publication bias was analyzed by Egger's test. In the meta-analysis, a random-effects model with Stata/SE software, v.14.1 (StataCorp, College Station, TX) was used to obtain a pooled incidence rate. RESULTS: Fifty studies were included in this systematic review and meta-analysis with 8815 patients and the mean age was 46 years and 4647 (52.7%) were male. The pooled incidences rate of clinical symptoms were: fever (83%, 95% CI: 0.77, 0.89), cough (59%, 95% CI: 0.48, 0.69), myalgia or fatigue (31%, 95% CI: 0.23, 0.39), sputum production (29%, 95% CI: 0.21, 0.39), and dyspnea (19%, 95% CI: 0.12, 0.26). The pooled incidence rate of acute respiratory distress syndrome (ARDS) was (22%, 95% CI: 0.00, 0.60). CONCLUSION: The results of this systemic review and meta-analysis present a quantitative pooled incidence rate of different characters of 2019-nCoV and has great potential to develop diagnosis and patient's stratification in 2019-nCoV. However, this conclusions of this study still requisite to be warranted by more careful design, larger sample size multivariate studies to corroborate the results of this meta-analysis.

Systematic review and meta-analysis of the effectiveness and safety of hydroxychloroquine in treating COVID-19 patients.

BACKGROUND: Since COVID-19 outbreak, hydroxychloroquine (HCQ) has been tested for effective therapies, and the relevant researches have shown controversial results. METHODS: Systematic review and meta-analysis were conducted after a thorough search of relevant studies from databases. Trials that have evaluated HCQ for COVID-19 treatment were recruited for statistical analysis with fixed- and random-effect models. RESULTS: Nine trials involving 4112 patients were included in present meta-analysis. It was seen that HCQ-azithromycin (HCQ-AZI) combination regimen increased the mortality rate in COVID-19 (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.63-3.36) patients; however, it also showed benefits associated with the viral clearance in patients (OR, 27.18; 95% CI, 1.29-574.32). HCQ-alone when used as a therapy in COVID-19 did not reveal significant changes in mortality rate, clinical progression, viral clearance, and cardiac QT prolongation. Subsequent subgroup analysis showed that HCQ treatment could decrease mortality rate and progression to severe illness in severely infected COVID-19 patients (OR, 0.27; 95% CI, 0.13-0.58). A lower risk of mortality rate was also noted in the stratified group of >14 days follow-up period (OR, 0.27; 95% CI, 0.13-0.58) compared to ≤14 days follow-up period group that conversely showed an increased mortality rate (OR, 2.09; 95% CI, 1.41-3.10). CONCLUSION: Our results indicated that HCQ-AZI combination treatment increased mortality rate in patients with COVID-19, but it also showed benefits associated with viral clearance in patients. HCQ-alone used for treatment has revealed benefits in decreasing the mortality rate among severely infected COVID-19 group and showed potential to be used for COVID-19 treatment in long-term follow-up period group. Accordingly, more rigorous, large-scale, and long follow-up period studies in patients with COVID-19 are needed.

Cardiovascular risk factors and mortality in hospitalized patients with COVID-19: systematic review and meta-analysis of 45 studies and 18,300 patients.

BACKGROUND: A high prevalence of cardiovascular risk factors including age, male sex, hypertension, diabetes, and tobacco use, has been reported in patients with Coronavirus disease 2019 (COVID-19) who experienced adverse outcome. The aim of this study was to investigate the relationship between cardiovascular risk factors and in-hospital mortality in patients with COVID-19. METHODS: MEDLINE, Cochrane, Web of Sciences, and SCOPUS were searched for retrospective or prospective observational studies reporting data on cardiovascular risk factors and in-hospital mortality in patients with COVID-19. Univariable and multivariable age-adjusted analyses were conducted to evaluate the association between cardiovascular risk factors and the occurrence of in-hospital death. RESULTS: The analysis included 45 studies enrolling 18,300 patients. The pooled estimate of in-hospital mortality was 12% (95% CI 9-15%). The univariable meta-regression analysis showed a significant association between age (coefficient: 1.06; 95% CI 1.04-1.09; p < 0.001), diabetes (coefficient: 1.04; 95% CI 1.02-1.07; p < 0.001) and hypertension (coefficient: 1.01; 95% CI 1.01-1.03; p = 0.013) with in-hospital death. Male sex and smoking did not significantly affect mortality. At multivariable age-adjusted meta-regression analysis, diabetes was significantly associated with in-hospital mortality (coefficient: 1.02; 95% CI 1.01-1.05; p = 0.043); conversely, hypertension was no longer significant after adjustment for age (coefficient: 1.00; 95% CI 0.99-1.01; p = 0.820). A significant association between age and in-hospital mortality was confirmed in all multivariable models. CONCLUSIONS: This meta-analysis suggests that older age and diabetes are associated with higher risk of in-hospital mortality in patients infected by SARS-CoV-2. Conversely, male sex, hypertension, and smoking did not independently correlate with fatal outcome.

A meta-analysis of the association between obesity and COVID-19.

Owing to limited data, we conducted a meta-analysis to re-evaluate the relationship between obesity and coronavirus-2019 (COVID-19). Literature published between 1 January 2020 and 22 August 2020 was comprehensively analysed, and RevMan3.5 was used for data analysis. A total of 50 studies, including data on 18 260 378 patients, were available. Obesity was associated with a higher risk of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) infection (odds ratio (OR): 1.39, 95% confidence interval (CI) 1.25-1.54; P < 0.00001) and increased severity of COVID-19 (hospitalisation rate: OR: 2.45, 95% CI 1.78-3.39; P < 0.00001; severe cases: OR: 3.74, 95% CI 1.18-11.87; P: 0.02; need for intensive care unit admission: OR: 1.30, 95% CI 1.21-1.40; P < 0.00001; need for invasive mechanical ventilation: OR: 1.59, 95% CI 1.35-1.88; P < 0.00001 and mortality: OR: 1.65, 95% CI 1.21-2.25; P: 0.001). However, we found a non-linear association between BMI and the severity of COVID-19. In conclusion, we found that obesity could increase the risk of SARS-CoV2 infection and aggregate the severity of COVID-19. Further studies are needed to explore the possible mechanisms behind this association.

Epidemiology of COVID-19 infection in young children under five years: A systematic review and meta-analysis.

INTRODUCTION: Emerging evidence suggests young children are at greater risk of COVID-19 infection than initially predicted. However, a comprehensive understanding of epidemiology of COVID-19 infection in young children under five years, the most at-risk age-group for respiratory infections, remain unclear. We conducted a systematic review and meta-analysis of epidemiological and clinical characteristics of COVID-19 infection in children under five years. METHOD: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses , we searched several electronic databases (Pubmed, EMBASE, Web of Science, and Scopus) with no language restriction for published epidemiological studies and case-reports reporting laboratory-confirmed COVID-19 infection in children under five years until June 4, 2020. We assessed pooled prevalence for key demographics and clinical characteristics using Freeman-Tukey double arcsine random-effects model for studies except case-reports. We evaluated risk of bias separately for case-reports and other studies. RESULTS: We identified 1,964 articles, of which, 65 articles were eligible for systematic review that represented 1,214 children younger than five years with laboratory-confirmed COVID-19 infection. The pooled estimates showed that 50% young COVID-19 cases were infants (95% CI: 36% - 63%, 27 studies); 53% were male (95% CI: 41% - 65%, 24 studies); 43% were asymptomatic (95% CI: 15% - 73%, 9 studies) and 7% (95% CI: 0% - 30%, 5 studies) had severe disease that required intensive-care-unit admission. Of 139 newborns from COVID-19 infected mothers, five (3.6%) were COVID-19 positive. There was only one death recorded. DISCUSSION: This systematic review reports the largest number of children younger than five years with COVID-19 infection till date. Our meta-analysis shows nearly half of young COVID-19 cases were asymptomatic and half were infants, highlighting the need for ongoing surveillance to better understand the epidemiology, clinical pattern, and transmission of COVID-19 to develop effective preventive strategies against COVID-19 disease in young paediatric population.