Abstract 260: Sociodemographic Analysis of Paediatric Out-of-Hospital Cardiac Arrest in Ontario, Canada: A Province-Wide Case-Control Study
Bibliographic record
Abstract
Background: Paediatric out-of-hospital cardiac arrest (POHCA) is associated with significant mortality and severe neurological sequelae. Previous literature indicates that there are sociodemographic disparities in POHCA survival and in the provision of upstream interventions. However, it’s unclear if the populations impacted by these disparities also have an elevated risk of experiencing POHCA. We sought to describe the relationship between sociodemographic factors and POHCA risk in Ontario, Canada. Methods: We conducted a province-wide case-control study using health administrative data at ICES. The case group included children (1 day to 17 years of age) who experienced an OHCA 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 POHCA and neighbourhood-level marginalization indicators, geographical context, and immigration status. Results: The case and control groups included 1,826 and 7,254 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: 1.23, 95% CI: 1.02, 1.49) 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 neighbourhoods with the lowest levels of ethnic diversity had a higher odds of POHCA (aOR: 1.34, 95% CI: 1.08, 1.67), as compared to children living in neighbourhoods with the highest levels of ethnic diversity. Northern urban (aOR: 1.42, 95% CI: 1.11, 1.82) and southern rural residence (aOR: 1.27, 95% CI: 1.04, 1.55) were associated with a higher odds of POHCA, relative to southern urban residence. The odds of POHCA were lower in child immigrants (aOR: 0.60, 95% CI: 0.42, 0.85) and maternal immigrants (aOR: 0.70, 95% CI: 0.61, 0.81), relative to the general population. The impact of residential instability was not significant in adjusted analyses. Conclusion: Children living in neighbourhoods with high levels of marginalization are likely at an elevated risk of experiencing POHCA. These communities should be prioritized in POHCA 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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".