Predictors of emergency cesarean delivery among international migrant women in Canada
Bibliographic record
Abstract
OBJECTIVE: To determine the predictors of emergency cesarean delivery among international migrant women. METHODS: Between February 2006 and May 2009, 1025 postpartum migrant women were recruited from 12 hospitals in Toronto, Montreal, and Vancouver. Logistic regression was used to model migration, social, health service, and biomedical factors predictive of emergency cesarean. RESULTS: Overall, 14% percent of participants underwent emergency cesarean. The greatest risk was for women having their first delivery (odds ratio [OR], 5.9; 95% confidence interval [CI], 3.1-11.3); newborns weighing 4000g or more (OR, 3.5; 95% CI, 1.9-6.5); no health insurance (OR, 2.8; 95% CI, 1.2-6.4); delivery on a Friday (OR, 2.2; 95% CI, 1.2-3.9); incomes of less than 30 000 Canadian dollars (OR, 1.9; 1.2-3.0); and induced labor (OR, 1.8; 95% CI, 1.1-3.0). Compared with immigrants, asylum seekers (OR, 0.3; 95% CI, 0.2-0.6) and refugees (OR, 0.5; 95% CI, 0.2-1.0) were protected against emergency cesarean. CONCLUSION: Indicators specific to, or more common among, migrants were informative in assessing the likelihood of emergency cesarean. The risk associated with being uninsured, day of delivery, income, and immigration class suggests the importance of considering non-biomedical factors in reducing the need for emergency cesarean among migrants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".