Prediction Model for Pre-Eclampsia in a Low-Resource Setting: A Systematic Literature Review
DOI:
https://doi.org/10.55175/cdk.v51i9.1102Keywords:
Low-resource setting, prediction model, pre-eclampsiaAbstract
The mechanism of preeclampsia is still unknown, so early diagnosis and termination of pregnancy are definitive therapies. A prediction model to be implemented in a low-resource setting is needed to predict the risk of pre-eclampsia in pregnant women. Pre-eclampsia prediction models also play a role in clinical decision-making, assisting with information, education, and communication (IEC) and considering the administration of aspirin prophylaxis. This study aims to systematically review the development of pre-eclampsia prediction models in a low-resource setting. PubMed, ScienceDirect, and Wiley Online Library databases between January 2019 and June 2023 were systematically reviewed. Article identification, screening, and selection of relevant articles, as well as data extraction, were carried out independently by the authors following PRISMA guidelines. Of the six articles that met the requirements, models that used maternal characteristics, risk factors, and physical examination. Laboratory tests improved the accuracy of pre-eclampsia prediction models in a low-resource setting. Examination with Doppler ultrasound and biomarkers could significantly improve the sensitivity and specificity of prediction models but could not be universally applied in a low-resource setting.
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