Abstract 286: Chance of Bystander Defibrillation According to Number of Nearby Automated External Defibrillators in Out-Of-Hospital Cardiac Arrests
Bibliographic record
Abstract
Introduction: Use of automated external defibrillators (AEDs) for early defibrillation in out-of-hospital cardiac arrest (OHCA) substantially increases chance of survival. Aim: To examine the relationship between number of nearby accessible AEDs and chance of bystander defibrillation. Methods: All OHCAs (2008-2016), and all publicly available AEDs (2007-2016) in Copenhagen were identified. The route distances between OHCAs and AEDs were calculated to determine the number of accessible AEDs ≤100m of an OHCA (OHCA coverage). Multiple logistic regression was performed to identify the adjusted Odds Ratios (ORs) of OHCA characteristics, including the number of AEDs covering an OHCA, on bystander defibrillation. The regression model was evaluated using receiver operator characteristics (ROC). Multiple logistic regression was also used to determine the predicted probability (through a 2000 iteration bootstrap approach) of bystander defibrillation for public vs. residential OHCAs, according to the number of accessible AEDs covering the OHCA, defined as covered by 0, 1 or >1 AED. Results: There were 1830 AEDs registered in Copenhagen. Of 2500 OHCAs, 75.2% (n=1879) occurred in residential locations of which 98.1% were not covered by an AED, 1.7% were covered by 1 AED only, and 0.2% were covered by >1 AED. The corresponding figures for public OHCAs (n=621, 24.8%) were 87.5%, 9.0%, and 3.5%, respectively. Overall, the number of accessible AEDs covering the OHCA, public location, bystander witnessed arrest and bystander CPR were significantly associated with bystander defibrillation (OR (95%CI): 1.75 (1.24-2.46); 4.25 (2.75-6.57); 3.12 (1.84-5.27); 2.33 (1.44-3.75), respectively. (ROC=82%)). The predicted probability of bystander defibrillation for public OHCAs was 12.2% (95%CI: 9.5-14.9) with no AED covering the OHCA, 24.7% (95%CI: 18.2-31.3) with 1 AED, and 39.8% (95%CI: 23.4-56.7) with >1 AED. The corresponding figures for residential OHCAs were 2.1% (95%CI: 1.5-2.8), 4.3% (95%CI: 2.5-6.8), and 4.0% (95%CI: 0.9-10.8), respectively. Conclusions: Rates of bystander defibrillation significantly improved with increasing number of accessible AEDs covering the OHCA, especially for public OHCAs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".