Prediction of preterm birth at St. Mary’s Hospital Lacor, Northern Uganda: a prospective cohort study

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dc.contributor.authorSilvia Awor
dc.contributor.authorRosemary Byanyima
dc.contributor.authorBenard Abola
dc.contributor.authorAnnettee Nakimuli
dc.contributor.authorChristopher Orach
dc.contributor.authorPaul Kiondo
dc.contributor.authorJasper Ogwal Okeng
dc.contributor.authorDan Kaye
dc.date.accessioned2025-09-01T10:14:16Z
dc.date.available2025-09-01T10:14:16Z
dc.date.issued2024-06
dc.descriptionThe models can be used for routine screening for preterm birth in prenatal clinics, to collect more data for its validation. Future research should be undertaken to validate the above models in prenatal clinics in other regions, to ensure generalizability. Policy makers could also interest the funders in incorporating screening for preterm birth in prenatal clinics. © 2024 Awor S et al. Licensee African Health Sciences. This is an Open Access article distributed under the terms of the Creative commons Attribution License (https://creativecommons.org/licenses/BY/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.description.abstractBackground: Preterm birth causes over 2% of perinatal mortality in Africa. Screening in prenatal clinics, may be used to identify women at risk. This study developed and validated second-trimester prediction models of preterm birth, using maternal socio-demographic characteristics, sonographic findings, and laboratory parameters in Northern Uganda. Methods: This prospective cohort study recruited 1,000 pregnant mothers at 16 - 24 weeks, and assessed their socio-demographic and clinical characteristics. Preterm birth (delivery after 28 and before 37 weeks) was the primary study outcome. Multi-variable analyses were performed, built models in RStudio, and cross-vaidated them using K (10)-fold cross-validation. Results: The Incidence of preterm birth was 11.9% (90 out of 774). The predictors of preterm birth were multiple pregnancies, personal history of preeclampsia, history of previous preterm birth, diastolic hypertension, serum ALP<98IU, white blood cell count >11000 cells/µl, platelet lymphocyte ratio >71.38, serum urea of 11-45 IU. These predicted preterm birth by 69.5% AUC, with 62.4% accuracy, 77.2% sensitivity, and 47.1% specificity. Conclusion: Despite low specificity, these models predict up to 77.2% of those destined to have a preterm birth, and may be used for second-trimester preterm birth screening in low-resource clinics
dc.identifier.citationAwor S, Byanyima R, Abola B, Nakimuli A, Orach C, Kiondo P, et al. Prediction of preterm birth at St. Mary’s Hospital Lacor, Northern Uganda: a prospective cohort study. Afri Health Sci. 2024;24(2). 283-292. https://dx.doi.org/10.4314/ahs.v24i2.31
dc.identifier.otherhttps://dx.doi.org/10.4314/ahs.v24i2.31
dc.identifier.urihttp://hdl.handle.net/20.500.14270/615
dc.language.isoen
dc.publisherAfrican Health Sciences,
dc.subjectPrediction
dc.subjectsecond-trimester
dc.subjectpreterm-birth
dc.subjectUganda
dc.subjectAfrica.
dc.titlePrediction of preterm birth at St. Mary’s Hospital Lacor, Northern Uganda: a prospective cohort study
dc.typeArticle

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