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However, it is associated with a higher risk of complications, especially when performed without a clear medical indication. Since labour attendants have no standardised clinical method to assist in this decision, statistical tools developed based on multiple labour variables may be an alternative. The objective of this paper was to develop and evaluate the accuracy of models for caesarean section prediction using maternal and foetal characteristics collected at admission and through labour.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Method<\/jats:title>\n<jats:p>This is a secondary analysis of the World Health Organization\u2019s Better Outcomes in Labour Difficulty prospective cohort study in two sub-Saharan African countries. Data were collected from women admitted for labour and childbirth in 13 hospitals in Nigeria as well as Uganda between 2014 and 2015. We applied logistic regression to develop different models to predict caesarean section, based on the time when intrapartum assessment was made. To evaluate discriminatory capacity of the various models, we calculated: area under the curve, diagnostic accuracy, positive predictive value, negative predictive value, sensitivity and specificity.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Results<\/jats:title>\n<jats:p>A total of 8957 pregnant women with 12.67% of caesarean births were used for model development. The model based on labour admission characteristics showed an area under the curve of 78.70%, sensitivity of 63.20%, specificity of 78.68% and accuracy of 76.62%. On the other hand, the models that applied intrapartum assessments performed better, with an area under the curve of 93.66%, sensitivity of 80.12%, specificity of 89.26% and accuracy of 88.03%.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Conclusion<\/jats:title>\n<jats:p>It is possible to predict the likelihood of intrapartum caesarean section with high accuracy based on labour characteristics and events. However, the accuracy of this prediction is considerably higher when based on information obtained throughout the course of labour.<\/jats:p>\n<\/jats:sec>","DOI":"10.1186\/s12978-019-0832-4","type":"journal-article","created":{"date-parts":[[2019,11,14]],"date-time":"2019-11-14T09:02:58Z","timestamp":1573722178000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Development of caesarean section prediction models: secondary analysis of a prospective cohort study in two sub-Saharan African countries"],"prefix":"10.1186","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7970-5403","authenticated-orcid":false,"given":"Hayala C. C.","family":"de Souza","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gleici S. 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Ethical approval was obtained from the World Health Organization Ethical Review Committee (protocol A65879, approval date 25 August 2014), the Makerere University School of Health Sciences Research and Ethics Committee, Uganda (protocol #SHSREC REF 2014\u2013058), University of Ibadan\/University College Hospital Ethics Committee (UI\/EC\/14\/0223), Federal Capital Territory Health Research Ethics Committee, Nigeria (protocol FHREC\/2014\/01\/42\/27\u201308-14), and Ondo State Government Ministry of Health Research Ethics Review Committee, Nigeria (AD 4693\/160). The study was conducted according to the Declaration of Helsinki of the World Medical Association. All study participants provided an informed consent at study enrolment.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests. The manuscript represents the views of the named authors only.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"165"}}