Abstract 16409: Gender Disparities Among Patients Receiving Bystander Cardiopulmonary Resuscitation in the United States
Bibliographic record
Abstract
Introduction: Bystander cardiopulmonary resuscitation (B-CPR) increases survival from out of hospital cardiac arrest (OHCA), but B-CPR rates remain low in the US. It is unknown whether disparities of B-CPR delivery exist based on the gender of OHCA victims. Objectives: We sought to assess whether there is variation in B-CPR rates by gender in the home and the public environment. We hypothesized that females would be less likely than males to receive B-CPR in the public, and assessed the impact on survival. Methods: We conducted a retrospective cohort study, using adult, non-traumatic OHCA events from US sites of the Resuscitation Outcomes Consortium (ROC). We modeled the likelihood of receiving B-CPR by gender and stratified by arrest location. Patient and neighborhood-level variables were assessed in a univariate analysis with admission into a multivariate model (p Results: From 2011-2015, the ROC registry contained 27,481 SCA events. Excluding pediatric, EMS witnessed, and healthcare facility arrests, 19,331 were analyzed. Mean age was 64±17; 63% were male. B-CPR was administered in 37% events and varied by location. Overall, 35% females and 36% males received B-CPR in the home (p=ns), and 39% females and 45% males received B-CPR in public (p Conclusion: Males had an increased likelihood of receiving B-CPR compared to females in public locations. B-CPR improved survival, and survival was greater among males compared to females. These findings identify an important gap in B-CPR delivery that can inform future messaging to lay responders, health care providers and dispatchers.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".