Sociodemographic Factors and the Risk of Pediatric Out‐of‐Hospital Cardiac Arrest in Ontario, Canada: A Province‐Wide Case–Control Study
Bibliographic record
Abstract
BACKGROUND: Pediatric out-of-hospital cardiac arrest (POHCA) is associated with significant mortality and poor neurological outcomes. We aimed to describe the association between sociodemographic factors and POHCA risk in Ontario, Canada. METHODS AND RESULTS: We conducted a province-wide case-control study at ICES, where patient records are linked across administrative databases. The case group included children (aged 1 day to 17 years) who experienced an out-of-hospital cardiac arrest between 2004 and 2020. Controls were matched up to 1:4 on age, sex, index date, and key comorbidities. We used conditional logistic regression to measure the association between sociodemographic indicators and POHCA risk. The case and control groups included 1826 and 7254 children, respectively. Children living in areas with the highest levels of material deprivation (adjusted odds ratio [aOR], 2.35 [95% CI, 1.94-2.85]) and dependency (aOR, 1.22 [95% CI, 1.01-1.48]) had a higher odds of POHCA, relative to children living in regions with the lowest levels of material deprivation and dependency, respectively. Children living in neighborhoods with the lowest levels of ethnic diversity had a higher odds of POHCA (aOR, 1.62 [95% CI, 1.30-2.01]), relative to children living in neighborhoods with the highest levels of ethnic diversity. The odds of POHCA were lower in immigrants (aOR, 0.67 [95% CI, 0.47-0.95]), relative to the general population. Northern urban residence was associated with a higher odds of POHCA (aOR, 1.45 [95% CI, 1.13-1.87]), relative to southern urban residence. CONCLUSIONS: Children living in neighborhoods with high levels of marginalization may have an elevated risk of experiencing POHCA. These findings highlight the importance of addressing disparities through targeted prevention and intervention efforts.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".