Browsing College of Health Sciences (CHS) by Author "Abola, Benard"

Now showing items 1-4 of 4

    • Incidence of preeclampsia and retention to prenatal care in Northern Uganda. 

      Awor, Silvia; Byanyima, Rosemary; Abola, Benard; Nakimuli, Annettee; Orach Garimoi, Christopher; Kiondo, Paul; Ogwal-Okeng, Jasper; Kaye Kabonge, Dan (East African Medical Journal, 2022-08-23)
      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 ...

    • Prediction of low birth weight at term in low resource setting of Gulu City, Uganda : a prospective cohort study 

      Awor, Silvia; Byanyima, Rosemary; Abola, Benard; Kiondo, Paul; Garimoi-Orach, Christopher; Ogwal-Okeng, Jasper; Nakimuli, Annettee; Kaye, Dan (PAMJ Clinical Medicine, 2022-11-08)
      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 ...

    • Prediction of pre-eclampsia at St. Mary's hospital lacor, a low-resource setting in northern Uganda, a prospective cohort study 

      Awor, Silvia; Abola, Benard; Byanyima, Rosemary; Garimo Orach, Christopher; Kiondo, Paul; Kaye Kabonge, Dan; Ogwal-Okeng, Jasper; Nakimuli, Annettee (BioMed Central (BMC), 2023-02-08)
      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 ...

    • Prediction of stillbirth low resource setting in Northern Uganda 

      Awor, Silvia; Byanyima, Rosemary; Abola, Benard; Kiondo, Paul; Orach, Christopher Garimoi; Ogwal‑Okeng, Jasper; Kaye, Dan; Nakimuli, Annettee (BMC Pregnancy and Childbirth, 2022-11-19)
      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 ...