ArticleBMC pregnancy and childbirth2023
Prediction of pre-eclampsia at St. Mary's hospital lacor, a low-resource setting in northern Uganda, a prospective cohort study.
Article in BMC pregnancy and childbirth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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5 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Global prevalence of preeclampsia, eclampsia, and HELLP syndrome: a systematic review and meta-analysis.Frontiers in reproductive health · 2025Pooled it
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- Preeclampsia among Omani women: prevalence and associated risk factors.Frontiers in global women's health · 2026Article
- Article
- Clinical study on the difference in intestinal microecology between patients with preeclampsia and pregnant women at different stages of pregnancy.Acta biochimica Polonica · 2024Article
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8 authors at 4 institutions in 1 country.
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Abstract
backgroundPre-eclampsia is the second leading cause of maternal death in Uganda. However, mothers report to the hospitals late due to health care challenges. Therefore, we developed and validated the prediction models for prenatal screening for pre-eclampsia.
methodsThis was a prospective cohort study at St. Mary's hospital lacor in Gulu city. We included 1,004 pregnant mothers screened at 16-24 weeks (using maternal history, physical examination, uterine artery Doppler indices, and blood tests), followed up, and delivered. We built models in RStudio. Because the incidence of pre-eclampsia was low (4.3%), we generated synthetic balanced data using the ROSE (Random Over and under Sampling Examples) package in RStudio by over-sampling pre-eclampsia and under-sampling non-preeclampsia. As a result, we got 383 (48.8%) and 399 (51.2%) for pre-eclampsia and non-preeclampsia, respectively. Finally, we evaluated the actual model performance against the ROSE-derived synthetic dataset using K-fold cross-validation in RStudio.
resultsMaternal history of pre-eclampsia (adjusted odds ratio (aOR) = 32.75, 95% confidence intervals (CI) 6.59-182.05, p = 0.000), serum alkaline phosphatase(ALP) < 98 IU/L (aOR = 7.14, 95% CI 1.76-24.45, p = 0.003), diastolic hypertension ≥ 90 mmHg (aOR = 4.90, 95% CI 1.15-18.01, p = 0.022), bilateral end diastolic notch (aOR = 4.54, 95% CI 1.65-12.20, p = 0.003) and body mass index of ≥ 26.56 kg/m
conclusionThe predictors of pre-eclampsia were maternal age ≥ 35 years, nulliparity, maternal history of pre-eclampsia, body mass index, diastolic pressure, white blood cell count, lymphocyte count, serum ALP and end-diastolic notch of the uterine arteries. This prediction model can predict pre-eclampsia in prenatal clinics with 77% accuracy.
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