Automated External Defibrillator Program Does Not Impair Cardiopulmonary Resuscitation Initiation in the Public Access Defibrillation Trial
Bibliographic record
Abstract
OBJECTIVES: To evaluate whether automated external defibrillator (AED) training and AED availability affected the response of volunteer rescuers and performance of cardiopulmonary resuscitation (CPR) in presumed out-of-hospital cardiac arrest (OOH-CA) during the multicenter Public Access Defibrillation Trial. METHODS: The Public Access Defibrillation Trial recruited 1,260 facilities in 24 North American regional sites to participate in a trial addressing survival from OOH-CA when AED training and availability were added to a volunteer-based emergency response team. Volunteers at each facility were trained to perform either CPR alone (CPR) or CPR in conjunction with AED use (CPR+AED) according to randomized assignments. This study reports the frequency of response and initiation of CPR actions (chest compressions and/or ventilations) by volunteers in the CPR and CPR+AED study groups. RESULTS: A total of 314 presumed OOH-CA episodes occurred in CPR facilities, and 308 occurred in CPR+AED facilities. The volunteers were matched well for age, gender, and other features. Overall, ventilations (23.1% vs. 13.1%), chest compressions (24.4% vs. 12.1%), and both actions (19.8% vs. 10.5%; all p < 0.05) were more commonly performed in OOH-CA cases in the CPR+AED group. However, when only OOH-CA cases with volunteers responding were analyzed, the rates of CPR actions were similar. In the subgroup of CPR+AED cases with a responding volunteer, the AED was turned on for only 47% of cases. Volunteers initiated a CPR action more commonly when the AED was turned on (60.7% vs. 39.3%; p = 0.003). CONCLUSIONS: In the Public Access Defibrillation Trial, rates of CPR actions for presumed OOH-CA victims were low but similar for CPR and CPR+AED responding volunteer rescuers. Factors associated with volunteer response, CPR action initiation, and AED activation warrant further investigation.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".