Infant Emergency Department Use After Midwifery‐ Versus Obstetrician‐Led Perinatal Care: A Population‐Based Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To assess whether infant emergency department (ED) use differs between a midwifery-based and obstetrics-based model of care. DESIGN: Retrospective population-based cohort study. SETTING: Province of Ontario, Canada. POPULATION: Infants born to low-risk primiparous women in a hospital, 2012-2021. METHODS: Modified Poisson regression compared ED use between women with midwifery and obstetrics-model care, weighting by propensity-based overlap weights. MAIN OUTCOME MEASURES: Any unscheduled infant ED visit after the birth hospitalisation discharge date up to 27 days thereafter. RESULTS: Included were 36 949 livebirths to women receiving care by a midwife and 120 463 to women receiving care by an obstetrician. Median gestational age at birth was 39 weeks; 11.8% and 13.3% were admitted to the NICU, and the median newborn hospital length of stay was 1.3 and 1.8 days, respectively. Midwifery-care mother-child pairs received a median of 6.9 postpartum visits by a midwife. An infant ED visit ≤ 27 days occurred among 1789 (4.8%) midwife-led care patients versus 11 886 (9.9%) obstetrician-led care recipients (relative risk [RR] 0.51, 95% CI 0.49 to 0.54; absolute risk difference -4.6%, 95% CI -4.9 to -4.3). The corresponding RR was 0.42 (95% CI 0.39 to 0.46) for infant ED visit ≤ 7 days and 0.87 (95% CI 0.86 to 0.89) for infant ED visit ≤ 365 days. CONCLUSIONS: Among infants born to low-risk primiparous women, midwifery-model care was associated with less ED use after birth than an obstetrics model of care. Among similar populations, enhanced access to midwifery care might reduce postnatal newborn resource use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".