Browsing by Author "Carrasco, Cynthia"
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- ItemMaternal and perinatal outcomes related to COVID-19 and pregnancy: An overview of systematic reviews(2021) Vergara-Merino, Laura; Meza, Nicolás; Couve-Pérez, Constanza; Carrasco, Cynthia; Ortiz Muñoz, Luis Eugenio; Madrid, Eva; Bohorquez-Blanco, Sandra; Bracchiglione, JavierIntroduction: Evidence about coronavirus disease 2019 (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 the 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, and preprint repositories, among other sources relevant to COVID-19), mapping them into PICO (population, intervention, control, and outcomes) questions. The search covered the period from the inception date of each database to 13 September 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 overlap 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% and 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 heterogeneous 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.
- ItemPrognosis of COVID-19 in pregnancy: Protocol for an overview of systematic reviews(2020) Vergara-Merino, Laura; Pérez-Bracchiglione, Javier; Meza, Nicolás; Constanza, Couve; Carrasco, Cynthia; Ortiz Muñoz, Luis Eugenio; Rada G., GabrielObjective: We aim to map and summarise the current evidence about COVID-19 prognosis in pregnant women. Design: This is the protocol of an overview of systematic reviews. Data sources: We will conduct comprehensive searches in PubMed/MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), grey literature, and L·OVE (Living OVerview of Evidence). L·OVE is a platform that maps PICO evidence questions from Epistemonikos database. In response to the COVID-19 emergency, L·OVE was adapted to expand its COVID-19 repository evidence as a way to gather it in one place. The search will cover the period until the day before submission to a journal. Eligibility criteria for selecting studies and methods: We adapted an already published common protocol for multiple parallel systematic reviews and overviews of systematic reviews to the specificities of this question. We will include all systematic reviews about COVID-19 in pregnant women. Two reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. Ethics and dissemination: No ethics approval is considered necessary. The results of this overview will be widely disseminated via peer-reviewed publications, social networks and traditional media.
- ItemTransmission of COVID-19 through breastfeeding(2020) Carrasco, Cynthia; Pizarro, Ana Beatriz; Urrea, Gabriela; Meza, Nicolás; Verdejo, Catalina; Rada G., Gabriel; Ortiz Muñoz, Luis Eugenio; Couve, ConstanzaObjective This living systematic review aims to evaluate the vertical transmission of SARS-CoV-2 through breast milk and breastfeeding in patients with COVID-19 providing a timely, rigorous and continuously updated summary of the evidence available on . Data sources We will conduct searches in the L·OVE (Living OVerview of Evidence) platform for COVID-19, a system that maps PICO questions to a repository maintained through regular searches in electronic databases, preprint servers, trial registries and other resources relevant to COVID-19. No date or language restrictions will be applied. In response to the COVID-19 emergency, L·OVE was adapted to expand the range of evidence it covers and customised to group all COVID-19 evidence in one place. The search will cover the period until the day before submission to a journal. Eligibility criteria for selecting studies and methods We adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this question. We will include primary studies evaluating the role of breast milk and breastfeeding transmission. Randomised trials evaluating breast milk and breastfeeding in infections caused by other coronaviruses, such as MERS-CoV and SARS-CoV, and non-randomised studies in COVID-19 will be searched in case we find no direct evidence from randomised trials, or if the direct evidence provides low- or very low-certainty for critical outcomes. Two reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. We will pool the results using meta-analysis and will apply the GRADE system 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.