Prediction of stillbirth low resource setting in Northern Uganda
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Date
2022-11-19
Journal Title
Journal ISSN
Volume Title
Publisher
BMC
Abstract
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 dur‑
ing 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-vali‑
dated 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.
Description
Acknowledgements:
The authors thank Mr. Ronald Kivumbi and Mr. Ronald Waiswa, the biostatisti
cians, for helping me with part of the preprocessing of the data for analysis.
In a special way, I thank my mentor, Prof. Letseka Moeketsi, for guiding me to
aim higher. The authors would like to acknowledge the support provided for
writing this paper from the British Academy Writing Workshop Programme
2022, ‘Addressing Epistemic Injustice: Supporting Writing about Inclusive and
Life‑long Education in Africa’
Authors’ contributions:
Silvia Awor is a Ph.D. student who wrote the proposal, collected data and
drafted the manuscript. Annettee Nakimuli, Jaspar Ogwal‑Okeng and Dan
Kabonge Kaye are doctoral supervisors who guided the writing of the
manuscript. Rosemary Byanyima, Paul Kiondo and Christopher Garimoi
Orach are doctoral committee members who gave technical advice during
the data collection and manuscript writing. Benard Abola, a mathematician,
helped develop and validate the model and participated in data analysis. The
author(s) read and approved the final manuscript
Keywords
Stillbirth, Risk factors, Prediction models, Uganda, Africa
Citation
Awor, S., Byanyima, R., Abola, B., Kiondo, P., Orach, C. G., Ogwal-Okeng, J., ... & Nakimuli, A. (2022). Prediction of stillbirth low resource setting in Northern Uganda. BMC Pregnancy and Childbirth, 22(1), 855.