Hospital factors associated with maternal and neonatal outcomes of deliveries to patients with a previous cesarean delivery: an ecological study
Bibliographic record
Abstract
BACKGROUND: Recommendations for deliveries of pregnant patients with a previous cesarean delivery and the type of hospitals deemed safe for these deliveries have evolved in recent years, although no studies have examined hospital factors and associated safety. We sought to evaluate maternal and neonatal outcomes among patients with a previous cesarean delivery by hospital tier and volume. METHODS: We carried out an ecological study of singleton live births delivered at term gestation to patients with a previous cesarean delivery in all Canadian hospitals (excluding Quebec), 2013-2019. We obtained data from the Discharge Abstract Database of the Canadian Institute for Health Information. The primary outcomes were severe maternal morbidity or mortality (SMMM), and serious neonatal morbidity or mortality (SNMM). We used regression modelling to examine hospital tier (tier 4 hospitals being those that provide the highest level of care) and volume; we also identified hospitals with high rates of SMMM and SNMM using within-tier comparisons and comparisons with the overall rate. RESULTS: We included 235 442 deliveries to patients with a previous cesarean delivery; SMMM and SNMM rates were 14.6 per 1000 deliveries and 4.6 per 1000 live births, respectively. Among patients with a parity of 1, SMMM rates were lower in tier 1 hospitals (adjusted incidence rate ratio [IRR] 0.68, 95% confidence interval [CI] 0.52-0.89) and higher in tier 4 hospitals (adjusted IRR 1.41, 95% CI 1.05-1.91) than in tier 2 hospitals; SNMM rates did not differ by hospital tier. Rates of SNMM increased with increasing hospital volume (adjusted IRR 1.02, 95% CI 1.00-1.04) and increasing rates of vaginal birth after cesarean delivery (adjusted IRR 1.02, 95% CI 1.01-1.04). Most hospitals had relatively low SMMM and SNMM rates, although a few hospitals in each tier and volume category had significantly higher rates than others. INTERPRETATION: Adverse maternal and neonatal outcomes among patients with a previous cesarean delivery showed no clear pattern of decreasing SMMM and SNMM with increasing tiers of service and hospital volume. All hospitals, irrespective of tier or size, should continually review their rates of adverse maternal and neonatal outcomes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".