Geographic Differences in Pediatric Surgical Mortality in Canada: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: This study describes differences in postoperative mortality for pediatric patients in rural communities compared to urban communities. BACKGROUND: . There are 18 children's hospitals in Canada offering pediatric surgical services, all in urban centres, yet nearly one-fifth of the population lives in rural or remote communities. Children who live in rural settings may have worse surgical outcomes, including mortality rates, compared with urban populations. METHODS: Pediatric patients, from birth to 18 years old, who had surgery from January 1, 2011, to December 31, 2021, at a single Children's Hospital were included in the study. Data was obtained from the provincial Operating Room Information System (ORIS) database. Postal code, rural and urban status, distance to children's hospital (0-50 km, 51-100 km, 101-150 km, 151-200 km, and >200 km), and procedure urgency were collected. 30-day mortality for all procedures was collected. RESULTS: 85,998 surgical procedures were performed at ACH between 2011 and 2021. 17,773 (20.7%) of patients lived >50 km or more from the hospital - 5,329 (6.2%) 51- 100 km, 4,053 (4.7%) 101-150 km, n=2,323 (2.7%) 151-200 km, and 6,070 (7.1%) >200 km. Rural patients had higher 30-day mortality rates than urban patients, with an odds ratio of mortality (rural vs urban) of 2.30 (95% CI, 0.95 to 5.60). When stratified by distance, patients living closer to the hospital (0-50 km) had lower odds of mortality. CONCLUSIONS: Canadian Rural patients have higher operative mortality risks than urban patients. This study identifies a vulnerable group of patients who do not have equal access to care and may experience worse 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".