Bystander administered AED shock improves survival from out of hospital cardiac arrest in US and Canada
Bibliographic record
Abstract
Introduction: The Public Access Defibrillation (PAD) trial showed that training and equipping lay volunteers to use an automated external defibrillator (AED) in community settings doubled the number of survivors after out-of-hospital cardiac arrest (OOHCA) compared to training in cardiopulmonary resuscitation (CPR) alone. The effectiveness of contemporary community-based PAD programs is unknown. Hypotheses: Bystander defibrillation before arrival of emergency medical services (EMS) personnel improves survival. Methods: Design-Population-based cohort study. Setting- 11 US and Canadian urban and rural sites participating in the ROC, a prehospital emergency care trials network. Inclusions- Individuals with non-traumatic OOHCA from 12/1/2005 to 11/30/2006, evaluated by organized EMS personnel who received attempted defibrillation before or after EMS arrival or chest compressions by EMS. Analyses-Multivariate logistic regression assessed the association between PAD and survival to hospital discharge. Results: Of 9897 EMS-treated OOHCA, 2991 (30.4%) received bystander CPR and 249 (2.5%) had AED placed by bystander. Overall survival to hospital discharge was 7%. Survival with bystander CPR but no AED, 8%; with AED applied by a bystander 21%; with bystander AED shock delivered, 33%; with EMS shock only, 15%. AED was applied by Lay Volunteers (32%), Police (24%), Healthcare Workers (42%), or Unknown (2%). The association between AED application and survival to hospital discharge was adjusted for age, gender, bystander CPR, public location, EMS response time and bystander witnessed status using multivariate logistic regression. After controlling for these factors, AED application was significantly associated with survival (O.R. 2.21 95% CI 1.41 – 3.47, P < .001). Conclusions: Survival benefits demonstrated in the PAD trial can translate to improved survival in community-based programs. Extrapolating this greater survival from ROC population base (20 million) to the population of US and Canada (330 million) suggests that currently AED application by bystanders saves 412 lives per year. Contemporary PAD programs have a substantial impact on survival from cardiac arrest but impact may be limited by penetration of PAD into the community.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".