Epidemiology of paediatric out-of-hospital cardiac arrest in Ontario, Canada
Bibliographic record
Abstract
There are no Canadian epidemiological studies of Paediatric Out-of-Hospital Cardiac Arrest (POHCA) for ≥20 years. Understanding the epidemiology of POHCA is key to prevention, education, and management strategies. We applied a validated algorithm to hospital administrative databases to describe paediatric (age 1 day to ≤18 years) atraumatic OHCA in Ontario from 2004–2020. The cohort included 1,839 paediatric patients with atraumatic POHCA occurring at a median (IQR) age of 2 (0–12) years with 721 (39.2%) POHCA events in <1-year-olds. Males accounted for 71.1% (n = 1123) of the cohort. Crude incidence of children with POHCA who were transported to an Emergency Department was 4.2/100,000 with an increase annually over the study period (p = 0.0065). Thirty percent (n = 560) lived in a neighbourhood with the lowest income quintile, while 13.6% (n = 251) lived in a neighbourhood with the highest income quintile, 78.6% (n = 1444) presented to a non-academic hospital, and the majority (n = 1533, 83.4%) did not have significant comorbidities. Survival to hospital discharge was achieved in 167 (9.1%). Less than 6 (<3.6%) patients had a repeat POHCA in the year following the index event. This is the largest Canadian POHCA cohort and the first to describe its incidence, comorbidities, and sociodemographic characteristics. We found an increase in annual crude incidence, POHCA mostly occurred in healthy children, and survival was similar to other cohorts. There were more than double the number of POHCA events in children living in the lowest income quintile neighborhoods compared to the highest. Most children presented to non-academic hospitals first.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".