Differences in rates and odds for emergency caesarean section in six Palestinian hospitals: a population-based birth cohort study
Bibliographic record
Abstract
OBJECTIVE: To assess the differences in rates and odds for emergency caesarean section among singleton pregnancies in six governmental Palestinian hospitals. DESIGN: A prospective population-based birth cohort study. SETTING: Obstetric departments in six governmental Palestinian hospitals. PARTICIPANTS: 32 321 women scheduled to deliver vaginally from 1 March 2015 until 29 February 2016. METHODS: test, analysis of variance and Kruskal-Wallis test were applied. Logistic regression was used to estimate differences in odds for emergency caesarean section, and ORs with 95% CIs were assessed. MAIN OUTCOME MEASURES: The primary outcome was the adjusted ORs of emergency caesarean section among singleton pregnancies for five Palestinian hospitals as compared with the reference (Hospital 1). RESULTS: The prevalence of emergency caesarean section varied across hospitals, ranging from 5.8% to 22.6% among primiparous women and between 4.8% and 13.1% among parous women. Compared with the reference hospital, the ORs for emergency caesarean section were increased in all other hospitals, crude ORs ranging from 1.95 (95% CI 1.42 to 2.67) to 4.75 (95% CI 3.49 to 6.46) among primiparous women. For parous women, these differences were less pronounced, crude ORs ranging from 1.37 (95% CI 1.13 to 1.67) to 2.99 (95% CI 2.44 to 3.65). After adjustment for potential confounders, the ORs were reduced but still statistically significant, except for one hospital among parous women. CONCLUSION: Substantial differences in odds for emergency caesarean section between the six Palestinian governmental hospitals were observed. These could not be explained by the studied sociodemographic or antenatal obstetric characteristics.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".