Abstract 15: Public Access Defibrillators: Sex-Based Inequities in Access and Application
Bibliographic record
Abstract
Introduction: It is unclear if the benefits of public access defibrillator (PAD) programs are similar between men and women. We investigated the location of out-of-hospital cardiac arrests (OHCA) stratified by sex to determine what proportion was eligible for PAD application. Second, we sought to determine if patient sex was associated with PAD utilization. Methods: We analyzed prospectively collected data from the North American Resuscitation Outcomes Consortium (ROC) Epistry dataset (2011 - 2015), excluding emergency medical services (EMS)-witnessed cases, those not treated by EMS, and children aged less than 10. We compared sex-based differences in public vs private location, and location type (street or highway, public building, place of recreation, industrial place, home residence, farm or ranch, healthcare facility, residential institution, other public property, or other private location). Among public location OHCAs with bystander interventions, we fit an adjusted logistic regression model to estimate the association between sex and PAD application. Results: Among the 61,473 cases, 20,933 (34%) were female, 30,353 had resuscitation attempted by bystander, and 13,597 had initial shockable rhythms. The OHCA incidence in a public location for women and men was 8.8% and 18%, respectively (95% CI for difference 8.7 - 9.7). Women had a significantly lower proportion of OHCAs on the street/highway, in public buildings, places of recreation, and farms, but a significantly higher proportion in the home, healthcare facilities, and residential institutions. Among public location OHCAs with bystander interventions, female sex was associated with a lower odds of bystander PAD application (adjusted OR 0.83, 95% CI 0.70-0.99). Conclusion: Women had fewer OHCAs in public locations eligible for PAD application. Further, among public OHCAs with bystander interventions, women were less likely to have PADs applied.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".