Evidence map›Paper›PMID 42564532›Full record

ArticleJournal of the colleges of medicine of South Africa2026

Maternal and foetal factors contributing to caesarean section rates at Chris Hani Baragwanath Academic Hospital, a tertiary care centre in South Africa.

Linda C Taptue Noumsi, Evelyn Ngwa Lumngwena, Poovangela Naidoo

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Article in Journal of the colleges of medicine of South Africa, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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3 authors.

Linda C Taptue NoumsiDepartment of Obstetrics and Gynaecology, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0009-0008-8287-3433
Evelyn Ngwa LumngwenaSchool of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0002-9302-8218
Poovangela NaidooDepartment of Obstetrics and Gynaecology, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0003-1879-7137

Funding

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6 · The paper itself

Abstract

Background: Caesarean section (CS) rates remain high globally, increasing healthcare costs and maternal-neonatal complications. The World Health Organization (WHO) recommends the Robson Ten Group Classification System (RTGCS) to assess and compare CS rates and reduce primary CS, which contributes to repeat procedures and associated risks. This study aimed to analyse indications for CS using RTGCS, maternal outcomes using WHO near-miss criteria, and pre- and post-delivery foetal conditions at a tertiary referral hospital. Methods: A retrospective cross-sectional study was conducted on CS deliveries in an African hospital from 01-30 June 2022. Data were analysed using bivariate and multivariate analysis with Fisher's exact test. Results: Of the 1,306 deliveries during the study period, 695 (53.2%) were CS. Robson Group 5 was the largest contributor (32.2%), followed by Groups 2 (16.4%) and 4 (12.8%). Foetal distress was the leading indication for CS (47.2%), followed by previous CS (declining vaginal birth after caesarean [VBAC]) (8.2%) and previous uterine scar × 2 in labour (5.8%). Mothers with a previous uterine scar accounted for 25.1% of all CSs, with 6.9% of them requiring high care. Maternal near-miss events occurred in 0.6% of cases. Group 5 had the highest maternal morbidity. Maternal risk factors that contributed to poor foetal outcome in this category were previous CS, chronic hypertension, gestational diabetes, poor obstetric history and obesity. Preoperatively, 62.4 % of foetuses had pathological non-stress tests (NSTs); 30.7% of NSTs were normal. Despite this, neonatal outcomes were favourable. Although no umbilical cord pH was done when the Apgar was > 7, those babies were discharged and coped well in the ward. The stillbirth risk was 12 times higher (OR 12.10, CI 4.29-34.14, Conclusion: High CS rates reflect tertiary care burden, with the majority falling within Robson Group 5. This group was the most frequent contributor to CS, and foetal distress was the leading indication for CS. Contribution: This was followed by factors related to previous uterine scars. Women with prior uterine scars frequently had a repeat CS and showed notable care needs. Although most foetuses had abnormal preoperative NSTs, overall neonatal outcomes were favourable. However, maternal near miss events, though rare, were strongly associated with significantly increased risks of stillbirth and poor neonatal outcomes. Strategies are needed to prevent primary CS, thus reducing maternal and perinatal morbidity.

Indexed as

caesarean indicationscaesarean sectionfoetal outcomenear-missRobson classification

Identifiers

PMID42564532
PMCPMC13443384

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.