School of Medicine (Sch. of Med.)

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Browsing School of Medicine (Sch. of Med.) by Author "Abola, Benard"
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    Incidence of preeclampsia and retention to prenatal care in Northern Uganda.
    (East African Medical Journal, 2022-08-23) Awor, Silvia ; Byanyima, Rosemary ; Abola, Benard ; Nakimuli, Annettee ; Orach Garimoi, Christopher ; Kiondo, Paul ; Ogwal-Okeng, Jasper ; Kaye Kabonge, Dan
    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 hypertension with proteinuria was taken as preeclampsia. Statistical analysis: Means, medians, and proportions were used to describe the population. The incidence per 104 women weeks of follow-up computed for different gestation ages. Results: Seventy-eight percent of the women delivered at the health facility. Women who were not retained through to delivery were younger (p<0.0001), had low BMI (p=0.0001) and more likely to be unemployed (p<0.0001). Overall, 43 women developed preeclampsia giving a prevalence of 4.3% (95% CI 3.1% 5.7%), and an incidence of 11 per 104 women weeks. The incidence of preeclampsia was 68 per 104 women weeks’ for women delivered at < 34 completed weeks of pregnancy, and 6.0 per 104 June 2022 women weeks for those delivered at > 37 weeks. Conclusion: Retention to prenatal care is 78% while the incidence of preeclampsia is 4.3% in Northern Uganda. This incidence is higher at lower gestation ages.
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    Prediction of low birth weight at term in low resource setting of Gulu City, Uganda : a prospective cohort study
    (PAMJ Clinical Medicine, 2022-11-08) Awor, Silvia ; Byanyima, Rosemary ; Abola, Benard ; Kiondo, Paul ; Garimoi-Orach, Christopher ; Ogwal-Okeng, Jasper ; Nakimuli, Annettee ; Kaye, Dan
    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 and 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. Since there were few low birth weight at term, were generated synthetic data using ROSE-package in RStudio by over-sampling low birth weights and undersampling normal birth weights, and evaluated the model performance against the synthetic data using K (10) - fold cross-validation. Results: mean age was 26.3 years with an average parity of 1.5. Their mean body mass index was 24.7 and 7.1% (49 of 687) had lateral placenta. The incidence of low birth weight was 5.7% (39 of 687). Predictors of low birth weight were gravidity, level of education, serum alanine aminotransferase (ALT), serum gamma-glutamyl transferase (GGT), lymphocyte count, placental location, and enddiastolic notch in the uterine arteries. This predicted low birth weight at term by 81.9% area under the curve (AUC), 76.1% accuracy, 72.9% specificity, and 79.1% sensitivity. Conclusion: a combination of gravidity, level of education, serum ALT, serum GGT, lymphocyte count, placental location, and end-diastolic notch in the uterine arteries can be used for screening for low birth weight in prenatal clinics for screening low birth weight at term.
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    Prediction of pre-eclampsia at St. Mary's hospital lacor, a low-resource setting in northern Uganda, a prospective cohort study
    (BioMed Central (BMC), 2023-02-08) Awor, Silvia ; Abola, Benard ; Byanyima, Rosemary ; Garimo Orach, Christopher ; Kiondo, Paul ; Kaye Kabonge, Dan ; Ogwal-Okeng, Jasper ; Nakimuli, Annettee
    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 (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. Results Maternal 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/m2 (aOR = 3.86, 95% CI 1.25—14.15, p = 0.027) were independent risk factors for pre-eclampsia. Maternal age ≥ 35 years (aOR = 3.88, 95% CI 0.94—15.44, p = 0.056), nulliparity (aOR = 4.25, 95% CI 1.08—20.18, p = 0.051) and white blood cell count ≥ 11,000 (aOR = 8.43, 95% CI 0.92—70.62, p = 0.050) may be risk factors for pre-eclampsia, and lymphocyte count of 800 – 4000 cells/microliter (aOR = 0.29, 95% CI 0.08—1.22, p = 0.074) may be protective against pre-eclampsia. A combination of all the above variables predicted pre-eclampsia with 77.0% accuracy, 80.4% sensitivity, 73.6% specificity, and 84.9% area under the curve (AUC). Conclusion The 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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    Prediction of stillbirth low resource setting in Northern Uganda
    (BMC Pregnancy and Childbirth, 2022-11-19) Awor, Silvia ; Byanyima, Rosemary ; Abola, Benard ; Kiondo, Paul ; Orach, Christopher Garimoi ; Ogwal‑Okeng, Jasper ; Kaye, Dan ; Nakimuli, Annettee
    Background: 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 pregnant mothers at 16–24 weeks, excluded those with lethal congenital anomalies diagnosed on ultrasound. Their history, physical findings, blood tests and uterine artery Doppler indices were taken, and the mothers were encouraged to continue with routine prenatal care until the time for delivery. While in the delivery ward, they were followed up in labour until delivery by the research team. The primary outcome was stillbirth 24 + weeks with no signs of life. Built models in RStudio. Since the data was imbalanced with low stillbirth rate, used ROSE package to over‑sample stillbirths and under‑sample live‑births to balance the data. We cross‑validated the models with the ROSE‑derived data using K (10)‑fold cross‑validation and obtained the area under curve (AUC) with accuracy, sensitivity and specificity. Results: The incidence of stillbirth was 2.5%. Predictors of stillbirth were history of abortion (aOR = 3.07, 95% CI 1.11—8.05, p = 0.0243), bilateral end‑diastolic notch (aOR = 3.51, 95% CI 1.13—9.92, p = 0.0209), personal history of preeclampsia (aOR = 5.18, 95% CI 0.60—30.66, p = 0.0916), and haemoglobin 9.5 – 12.1 g/dL (aOR = 0.33, 95% CI 0.11—0.93, p = 0.0375). The models’ AUC was 75.0% with 68.1% accuracy, 69.1% sensitivity and 67.1% specificity. Conclusion: Risk factors for stillbirth include history of abortion and bilateral end‑diastolic notch, while haemoglobin of 9.5—12.1 g/dL is protective.