Introduction: Evidence about COVID-19 and pregnancy has rapidly increased since December 2019, making it difficult to make rigorous evidence-based decisions. The objective of this overview of systematic reviews is to conduct a comprehensive analysis of the current evidence on prognosis of COVID-19 in pregnant women. Material and methods: We used Living OVerview of Evidence (L•OVE) platform for COVID-19, which continually retrieves studies from 46 data sources (including Pubmed/MEDLINE, Embase, other electronic databases, clinical trials registries, preprint repositories, among other sources relevant to COVID-19), mapping them into PICO questions. The search covered the period from the inception date of each database to September 13, 2020. We included systematic reviews assessing outcomes of pregnant women with COVID-19 and/or their newborns. Two authors independently screened the titles and abstracts, assessed full-texts to select the studies that met the inclusion criteria, extracted data, and appraised the risk of bias of each included systematic review. We measured the overlap of primary studies included among the selected systematic reviews by building a matrix of evidence, calculating the corrected covered area, and assessing the level of overlapping for every pair of systematic reviews. Results: Our search yielded 1132 references. 52 systematic reviews met inclusion criteria and were included in this overview. Only one review had a low risk of bias, three had an unclear risk of bias, and 48 had a high risk of bias. Most of the included reviews were highly overlapped among each other. In the included reviews, rates of maternal death varied from 0% to 11.1%, admission to intensive care from 2.1% to 28.5%, preterm deliveries before 37 weeks from 14.3% to 61.2%, and cesarean delivery from 48.3% to 100%. Regarding neonatal outcomes, neonatal death varied from 0% to 11.7% while the estimated infection status of the newborn varied between 0% and 11.5%. Conclusions: Only one of 52 systematic reviews had a low risk of bias. Results were heterogenous and the overlap of primary studies was frequently very high between pairs of systematic reviews. High quality evidence syntheses of comparative studies are needed to guide future clinical decisions.

Objective This living, systematic review aims to provide a timely, rigorous, and continuously updated summary of the evidence available on the role of macrolides for treating patients with COVID-19. Design A living, systematic review. Database We conducted searches in the centralized repository L·OVE (Living OVerview of Evidence). L·OVE is a platform that maps PICO questions to evidence from the Epistemonikos database. In response to the COVID-19 emergency, L·OVE was adapted to expand the range of evidence it covers and customized to group all COVID-19 evidence in one place. Today it is maintained through regular searches in 39 databases. Methods We included randomized trials evaluating the effect of macrolides — as monotherapy or in combination with other drugs — versus placebo or no treatment in patients with COVID-19. Randomized trials evaluating macrolides in infections caused by other coronaviruses, such as MERS-CoV and SARS-CoV, and non-randomized studies in COVID-19 were searched in case we found no direct evidence from randomized trials. Two reviewers independently screened each study for eligibility, extracted data, and assessed the risk of bias. Measures included all-cause mortality; the need for invasive mechanical ventilation; extracorporeal membrane oxygenation, length of hospital stay, respiratory failure, serious adverse events, time to SARS-CoV-2 RT-PCR negativity. We applied the GRADE approach to assess the certainty of the evidence for each outcome. A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates. Results The search in the L·OVE platform retrieved 424 references. We considered 260 as potentially eligible and were reviewed in full texts. We included one randomized clinical trial that evaluated the use of azithromycin in combination with hydroxychloroquine compared to hydroxychloroquine alone in hospitalized patients with COVID 19. The estimates for all outcomes evaluated resulted in insufficient power to draw conclusions. The quality of the evidence for the main outcomes was low to very low. Conclusions Macrolides in the management of patients with COVID 19 showed no beneficial effects compared to standard of care. The evidence for all outcomes is inconclusive. Larger trials are needed to determine the effects of macrolides on pulmonary and other outcomes in COVID-19 patients. Systematic review registration PROSPERO Registration number: CRD42020181032 Protocol preprint DOI: 10.31219/osf.io/rvp59

The increasing amount of evidence has caused an increasing amount of literature reviews. There are different types of reviews —systematic reviews are the best known—, and every type of review has different purposes. The scoping review is a recent model that aims to answer broad questions and identify and expose the available evidence for a broader question, using a rigorous and reproducible method. In the last two decades, researchers have discussed the most appropriate method to carry out scoping reviews, and recently the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses’ for scoping reviews (PRISMA-ScR) reporting guideline was published. This is the fifth article of a methodological collaborative series of narrative reviews about general topics on biostatistics and clinical epidemiology. This review aims to describe what scoping reviews are, identify their objectives, differentiate them from other types of reviews, and provide considerations on how to carry them out.

This article belongs to a collaborative methodological series of narrative reviews about biostatistics and clinical epidemiology. The goal is to present basics concepts concerning the systematics reviews of multiple treatments comparisons with network meta-analysis. For clinical ques-tions with several therapeutic alternatives to be compared, the central question is how to classify or rank their effectiveness (benefit and harm) to choose the best option. The network meta-analysis aims to answer questions related to the effectiveness and safety of comparing multiple treatments by the simultaneous analysis of results raised from direct and indirect comparisons. The network geometry is the general graphical representation of the network meta-analysis and allows to understand and assess the strength of comparisons. The network meta-analysis should check several assumptions to be valid, especially the transitivity assumption, which allows assuming that there are no systematic differences among the included comparisons, except their compared interventions. Thus, it is possible to know the relative therapeutic effectiveness of each pair of interventions included in the network meta-analysis and their ranking in terms of categorization. It has been proposed to use a modified Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach considering the distinctive features of network meta-analysis to assess the certainty of the evidence for each comparison and the ranking of interventions.