Protocol for a sequential, prospective metaanalysis to describe coronavirus disease 2019 (COVID-19) in the pregnancy and postpartum periods

Emily R. Smith*, Erin Oakley, Siran He, Rebecca Zavala, Kacey Ferguson, Lior Miller, Gargi Wable Grandner, Ibukun Oluwa Omolade Abejirinde, Yalda Afshar, Homa Ahmadzia, Grace Aldrovandi, Victor Akelo, Beth A. Tippett Barr, Elisa Bevilacqua, Justin S. Brandt, Natalie Broutet, Irene Fernandez Buhigas, Jorge Carrillo, Rebecca Clifton, Jeanne ConryErich Cosmi, Camille Delgado-Lopez, Hema Divakar, Amanda J. Driscoll, Guillaume Favre, Valerie Flaherman, Christopher Gale, Maria M. Gil, Christine Godwin, Sami Gottlieb, Olivia Hernandez Bellolio, Edna Kara, Sammy Khagayi, Caron Rahn Kim, Marian Knight, Karen Kotloff, Antonio Lanzone, Kirsty Le Doare, Christoph Lees, Ethan Litman, Erica M. Lokken, Valentina Laurita Longo, Laura A. Magee, Raigam Jafet Martinez-Portilla, Elizabeth McClure, Torri D. Metz, Deborah Money, Edward Mullins, Jean B. Nachega, Alice Panchaud, Rebecca Playle, Liona C. Poon, Daniel Raiten, Lesley Regan, Gordon Rukundo, Jose Sanin-Blair, Marleen Temmerman, Anna Thorson, Soe Thwin, Jorge E. Tolosa, Julia Townson, Miguel Valencia-Prado, Silvia Visentin, Peter Von Dadelszen, Kristina Adams Waldorf, Clare Whitehead, Huixia Yang, Kristian Thorlund, James M. Tielsch

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

We urgently need answers to basic epidemiological questions regarding SARS-CoV-2 infection in pregnant and postpartum women and its effect on their newborns. While many national registries, health facilities, and research groups are collecting relevant data, we need a collaborative and methodologically rigorous approach to better combine these data and address knowledge gaps, especially those related to rare outcomes. We propose that using a sequential, prospective meta-analysis (PMA) is the best approach to generate data for policy- and practice-oriented guidelines. As the pandemic evolves, additional studies identified retrospectively by the steering committee or through living systematic reviews will be invited to participate in this PMA. Investigators can contribute to the PMA by either submitting individual patient data or running standardized code to generate aggregate data estimates. For the primary analysis, we will pool data using two-stage meta-analysis methods. The meta-analyses will be updated as additional data accrue in each contributing study and as additional studies meet study-specific time or data accrual thresholds for sharing. At the time of publication, investigators of 25 studies, including more than 76,000 pregnancies, in 41 countries had agreed to share data for this analysis. Among the included studies, 12 have a contemporaneous comparison group of pregnancies without COVID-19, and four studies include a comparison group of non-pregnant women of reproductive age with COVID-19. Protocols and updates will be maintained publicly. Results will be shared with key stakeholders, including the World Health Organization (WHO) Maternal, Newborn, Child, and Adolescent Health (MNCAH) Research Working Group. Data contributors will share results with local stakeholders. Scientific publications will be published in open-access journals on an ongoing basis.

Original languageEnglish
Article numbere0270150
JournalPLoS ONE
Volume17
Issue number6 June
DOIs
Publication statusPublished - Jun 2022
Externally publishedYes

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