Prevalence, indications, and complications of caesarean section in health facilities across Nigeria: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Over 80,000 pregnant women died in Nigeria due to pregnancy-related complications in 2020. Evidence shows that if appropriately conducted, caesarean section (CS) reduces the odds of maternal death. In 2015, the World Health Organization (WHO), in a statement, proposed an optimal national prevalence of CS and recommended the use of Robson classification for classifying and determining intra-facility CS rates. We conducted this systematic review and meta-analysis to synthesise evidence on prevalence, indications, and complications of intra-facility CS in Nigeria. METHODS: Four databases (African Journals Online, Directory of Open Access Journals, EBSCOhost, and PubMed) were systematically searched for relevant articles published from 2000 to 2022. Articles were screened following the PRISMA guidelines, and those meeting the study's inclusion criteria were retained for review. Quality assessment of included studies was conducted using a modified Joanna Briggs Institute's Critical Appraisal Checklist. Narrative synthesis of CS prevalence, indications, and complications as well as a meta-analysis of CS prevalence using R were conducted. RESULTS: We retrieved 45 articles, with most (33 (64.4%)) being assessed as high quality. The overall prevalence of CS in facilities across Nigeria was 17.6%. We identified a higher prevalence of emergency CS (75.9%) compared to elective CS (24.3%). We also identified a significantly higher CS prevalence in facilities in the south (25.5%) compared to the north (10.6%). Furthermore, we observed a 10.7% increase in intra-facility CS prevalence following the implementation of the WHO statement. However, none of the studies adopted the Robson classification of CS to determine intra-facility CS rates. In addition, neither hierarchy of care (tertiary or secondary) nor type of facility (public or private) significantly influenced intra-facility CS prevalence. The commonest indications for a CS were previous scar/CS (3.5-33.5%) and pregnancy-related hypertensive disorders (5.5-30.0%), while anaemia (6.4-57.1%) was the most reported complication. CONCLUSION: There are disparities in the prevalence, indications, and complications of CS in facilities across the geopolitical zones of Nigeria, suggestive of concurrent overuse and underuse. There is a need for comprehensive solutions to optimise CS provision tailor-made for zones in Nigeria. Furthermore, future research needs to adopt current guidelines to improve comparison of CS rates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".