Improving access, quality and safety of caesarean section services in underserved rural Tanzania: The impact of knowledge translation strategies
Bibliographic record
Abstract
This research was designed to study different approaches to improve access to, and quality of caesarean section services in underserved Tanzania and translate evidence into practice. In 2016, 42 associate clinicians from five health centers were trained in teams for three months in comprehensive emergency obstetric and neonatal care and anesthesia followed by post-training supportive supervision and mentorship. From 2016-2019, 2,179 caesarean sections were performed in the intervention and 969 in the control health centers. Catchment population-based caesarean section rates increased significantly in all five intervention health centers and were more than 10% in three facilities. The risk of a woman dying from complications of caesarean section in the intervention health centers was 2.3 per 1,000 caesarean sections (95% CI 0.7 - 5.3). This educational program was adopted by the government and can be used to meet the demand for caesarean section services in other underserved areas in Africa. (Afr J Reprod Health 202 1; 25[3s]: 74-83 ).
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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 | 0.013 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".