06/15/2023
Recent Research
Introduction: Hypertensive disorders cause higher mortality in lower to middle income countries (LMIC). Models developed in higher income countries may not work in LMICs due to difference/lack of testing and resources. The aim of the study was to test a model to predict adverse maternal and neonatal outcomes using an algorithm developed for LMIC.
Methods: The study was conducted in Zimbabwe. PE cases included in the study had severe-spectrum preeclampsia (PE). Both maternal and neonatal outcomes were a combination of various possible outcomes (e.g., preterm birth, low birth weight, organ dysfunction, dialysis, etc.).
Sample size: The study analyzed 40,000 deliveries and the incidence of severe preeclampsia/eclampsia was 1.3%, therefore, approximately 520 affected women were included.
Results: The predictive model for composite adverse maternal outcome included maternal age, gestational age on admission, epigastric pain, vaginal bleeding with abdominal pain, hemoglobin concentration, and platelets. The predictive ability of the model was good, few false positives and false negatives resulted. However, when the model was used in a different population, it was unable to accurately predict adverse maternal outcomes. The model for composite adverse neonatal outcome included: gestational age, platelets, alanine transaminase and birth weight and produced an even better model, and thus had good predictive ability for adverse neonatal outcomes. They did not test this model in a different population.
Conclusion: The predictive model developed for LMIC performed well in the study population but was not able to be used in other populations, thus limiting its utility. Other limitations include patients were collected from the only one medical center (limits the ability to generalize to different populations) and it relied on data collected for clinical but not research purposes, therefore, some important variables may not have been available. The study only included women with severe PE and excluded mild PE, hence, it may not be accurate when predicting mild disease.
Ngwenya S, Jones B, Mwembe D, Nare H, Heazell AEP. Development and validation of risk prediction models for adverse maternal and neonatal outcomes in severe preeclampsia in a low-resource setting, Mpilo Central Hospital, Bulawayo, Zimbabwe. Pregnancy Hypertens. 2021 Mar;23:18-26. doi: 10.1016/j.preghy.2020.10.011. Epub 2020 Nov 2. PMID: 33161225.
