Prediction of pre-eclampsia at St. Mary's hospital lacor, a low-resource setting in northern Uganda, a prospective cohort study
Background
Pre-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.
Methods
This 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 (…
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Incidence of preeclampsia and retention to prenatal care in Northern Uganda
Background: Known risk factors for preeclampsia include women of African descent and low socioeconomic status. This means all the mothers in Northern Uganda are at risk. In Uganda preeclampsia causes 12 – 19% of maternal deaths. However, data on its burden is limited. Objective: To determine prenatal care retention and preeclampsia incidence in northern Uganda. Setting: St. Mary’s hospital Lacor, northern Uganda. Design: Prospective cohort study. Participants: Recruited 1,285 mothers at 16-24 weeks of gestation. Their history, physical findings, blood tests, and uterine artery Doppler indices were taken at baseline, and the women were followed up until delivery. Outcome: A combination of…
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Prediction of stillbirth low resource setting in Northern Uganda
Women of Afro-Caribbean and Asian origin are more at risk of stillbirths. However, there are limited tools built for risk-prediction models for stillbirth within sub-Saharan Africa. Therefore, we examined the predictors for stillbirth in low resource setting in Northern Uganda.
Methods
Prospective cohort study at St. Mary’s hospital Lacor in Northern Uganda. Using Yamane’s 1967 formula for calculating sample size for cohort studies using finite population size, the required sample size was 379 mothers. We doubled the number (to > 758) to cater for loss to follow up, miscarriages, and clients opting out of the study during the follow-up period. Recruited 1,285…
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Prediction of low birth weight at term in low resource setting of Gulu city, Uganda: a prospective cohort study
Introduction: despite the widespread poverty in Northern Uganda resulting in undernutrition, not all mothers deliver low birth weight babies. Therefore we developed and validated the risk prediction models for low birth weight at term in Northern Uganda from a prospective cohort study.
Methods: one thousand mothers were recruited from 16 - 24 weeks of gestation and followed up until delivery. Six hundred eighty-seven mothers delivered at term. The others were either lost to follow-up or delivered preterm. Used proportions to compute incidence of low birth weight at term, build models for prediction of low birth weight at term in RStudio…
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