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CONSIGN-International Meta-analysis Protocol & Statistical Analysis Plan

Authors: É. Maisonneuve; De Bruin, O.; E. Hurley; H. Nordeng; S.J. Siiskonen; F. Ahmadizar; J. Lyons; +8 Authors

CONSIGN-International Meta-analysis Protocol & Statistical Analysis Plan

Abstract

The use of medicines specific for COVID-19 in pregnant women is infrequent, highly correlated with severity of COVID-19 disease and changing over time since the start of the pandemic. Since pregnant women have not been included in most clinical trials for COVID-19 medicines, there is an important gap in knowledge. In this context, regulators and other stakeholders need to be prepared for situations where questions arise regarding the impact of medicines used against COVID-19 during pregnancy, on maternal, pregnancy and neonatal outcomes. This deliverable presents the protocol and statistical analysis plan of CONSIGN International. Two meta-analyses will be conducted including prospective and retrospective data collection with reliable data on the different classes of medicines and associated perinatal outcomes in a real-world clinical setting. The first meta-analaysis will combine population-based health care data sources (meta-analysis 1) and the second will combine case-based registries compiled by health care professionals (meta-analysis 2). The aim of the CONSIGN international meta-analysis is to describe the use of medicines to treat COVID-19 disease by trimester of pregnancy and the effects of medicines used to treat COVID-19 on maternal, pregnancy and neonatal outcomes and to pool as much data available around the world with similar protocols and settings.

Keywords

safety, meta-analysis, utilization, COVID-19, pregnancy, medicines

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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