Outcomes of deliveries by family physicians or obstetricians: a population-based cohort study using an instrumental variable
Bibliographic record
Abstract
BACKGROUND: Previous research has suggested that obstetric outcomes are similar for deliveries by family physicians and obstetricians, but many of these studies were small, and none of them adjusted for unmeasured selection bias. We compared obstetric outcomes between these provider types using an econometric method designed to adjust for unobserved confounding. METHODS: We performed a retrospective population-based cohort study of all Canadian (except Quebec) hospital births with delivery by family physicians and obstetricians at more than 20 weeks gestational age, with birth weight greater than 500 g, between Apr. 1, 2006, and Mar. 31, 2009. The primary outcomes were the relative risks of in-hospital perinatal death and a composite of maternal mortality and major morbidity assessed with multivariable logistic regression and instrumental variable-adjusted multivariable regression. RESULTS: After exclusions, there were 3600 perinatal deaths and 14,394 cases of maternal morbidity among 799,823 infants and 793,053 mothers at 390 hospitals. For deliveries by family physicians v. obstetricians, the relative risk of perinatal mortality was 0.98 (95% confidence interval [CI] 0.85-1.14) and of maternal morbidity was 0.81 (95% CI 0.70-0.94) according to logistic regression. The respective relative risks were 0.97 (95% CI 0.58-1.64) and 1.13 (95% CI 0.65-1.95) according to instrumental variable methods. INTERPRETATION: After adjusting for both observed and unobserved confounders, we found a similar risk of perinatal mortality and adverse maternal outcome for obstetric deliveries by family physicians and obstetricians. Whether there are differences between these groups for other outcomes remains to be seen.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".