Spatiotemporal Stability of Public Cardiac Arrests
Bibliographic record
Abstract
Background: Public access automated external defibrillator (AED) deployment and community cardiopulmonary resuscitation (CPR) programs should target geographical areas with high risk of out-of-hospital cardiac arrest (OHCA). Although these long-term, location-based interventions implicitly assume that the geographical OHCA risk remains stable over time, there is a paucity of evidence to support this assumption. Objective: To determine whether geographic OHCA risk is stable over time in a Canadian urban setting. Methods: We identified all atraumatic public-location OHCAs in Toronto, Canada from Jan. 2006 – Dec. 2014 and allocated each of them to one of the 140 neighborhoods defined by the City of Toronto. We then calculated the intra-class correlation (ICC) to measure the relative variability of OHCA counts within and between neighbourhoods over time. Results: We identified 2506 atraumatic public OHCAs. The figure shows that the average number of public OHCAs in Toronto was 278.4 (±41.4) per year. The highest-risk neighborhood had an average number of 12.9 OHCAs per year and remained the highest-risk neighborhood during six of the nine years. The four lowest-risk neighborhoods each had a rate of 0.1 OHCA per year. The ICC value was 0.67 [95% CI, 0.61 to 0.73], indicating that there was less year-to-year variation within the same neighborhood (i.e., more temporal stability) and more variation between neighborhoods. Conclusion: The OHCA rate in Toronto is stable at the neighborhood level over time. High-risk neighborhoods tend to remain high-risk, which supports focusing public health resources in those areas to increase the efficiency of these scarce resources and improve long-term impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".