Out-of-hospital cardiac arrest survival in drug-related versus cardiac causes in Ontario: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Drug overdose causes approximately 183,000 deaths worldwide annually and 50,000 deaths in Canada and the United States combined. Drug-related deaths are concentrated among young people, leading to a substantial burden of disease and loss of potential life years. Understanding the epidemiology, patterns of care, and prognosis of drug-related prehospital emergencies may lead to improved outcomes. METHODS: We conducted a retrospective cohort study of out-of-hospital cardiac arrests with drug-related and presumed cardiac causes between 2007 and 2013 using the Toronto Regional RescuNet Epistry database. The primary outcome was survival to hospital discharge. We computed standardized case fatality rates, and odds ratios of survival to hospital discharge for cardiac arrests with drug-related versus presumed cardiac causes, adjusting for confounders using logistic regression. RESULTS: The analysis involved 21,497 cardiac arrests, including 378 (1.8%) drug-related and 21,119 (98.2%) presumed cardiac. Compared with the presumed cardiac group, drug-related arrest patients were younger and less likely to receive bystander resuscitation, have initial shockable cardiac rhythms, or be transported to hospital. There were no significant differences in emergency medical service response times, return of spontaneous circulation, or survival to discharge. Standardized case fatality rates confirmed that these effects were not due to age or sex differences. Adjusting for known predictors of survival, drug-related cardiac arrest was associated with increased odds of survival to hospital discharge (OR1.44, 95%CI 1.15-1.81). INTERPRETATION: In out-of-hospital cardiac arrest, patients with drug-related causes are less likely than those with presumed cardiac causes to receive bystander resuscitation or have an initial shockable rhythm, but are more likely to survive after accounting for predictors of survival. The demographics and outcomes among drug-related cardiac arrest patients offers unique opportunities for prehospital intervention.
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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) | 0.000 | 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 | 0.000 |
| 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".