five

Inclusion and exclusion criteria.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Inclusion_and_exclusion_criteria_/28653469
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Introduction Globally, low and middle-income countries (LMICs) account for the majority of the adverse pregnancy outcomes. Risk prediction models (RPMs) can guide physicians in making clinical decisions to improve maternal and newborn health. However, there is scanty data on RPMs in determining adverse maternal and newborn outcomes in LMICs. Hence, this scoping review aims to describe the RPMs and the risk factors which have been used to determine both maternal and newborn adverse outcomes of pregnancy in LMICs. Methods This scoping review will be guided by the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for Scoping Reviews (PRISMA-ScR) and the JBI methodology for scoping reviews. The review would employ the Population, Concept, Context (PCC) framework to include studies that reported RPMs to determine either adverse maternal or newborn outcomes of pregnancy or both in LMICs. A literature search will be conducted in four databases for both published and unpublished articles on RPMs for adverse maternal or newborn outcomes from January 1, 2000, to June 26, 2024. We will use the JBI approach for study selection, data extraction, and presentation. The screening and data extraction will be conducted by two independent reviewers. Conclusion This scoping review will provide a comprehensive assessment of RPMs for adverse maternal and newborn outcomes in LMICs. This study will help gain knowledge on the up-to-date literature on risk prediction models for adverse pregnancy outcomes which can be useful for researchers and clinicians in making clinical decisions. Review registration: Open Science Framework https://doi.org/10.17605/OSF.IO/B9CKJ.
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2025-03-24
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