CONSIGN-International Meta-analysis Protocol & Statistical Analysis Plan
Authors/Creators
- 1. University Lausanne/Bern (UniBern), Switzerland
- 2. University Medical Center Utrecht (UMCU), the Netherlands
- 3. University Oslo (UiO), Norway
- 4. Utrecht University (UU), the Netherlands
- 5. Harvard Pilgrim Health Care, USA
- 6. Université de Montréal, Canada
- 7. Copenhagen University Hospital-Holbæk and Copenhagen University Hospital-Nordsjælland-Hillerød, Denmark
- 8. The George Washington University, USA
- 9. Centers for Disease Control and Prevention (CDC), USA
- 10. SFDA, Saudi Arabia
Description
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.
Files
Annex_19_CODEBOOK_CONSIGN_MA2.pdf
Files
(5.8 MB)
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