Gender Disparities Among Adult Recipients of Bystander Cardiopulmonary Resuscitation in the Public
Bibliographic record
Abstract
BACKGROUND: Bystander cardiopulmonary resuscitation (BCPR) improves survival from out-of-hospital cardiac arrest (OHCA), yet BCPR rates remain low. It is unknown whether BCPR delivery disparities exist based on victim gender. We measured BCPR rates by gender in private and public environments, hypothesizing that females would be less likely than males to receive BCPR in public settings, with an associated difference in survival to hospital discharge. METHODS AND RESULTS: We analyzed data from adult, nontraumatic OHCA events within the Resuscitation Outcomes Consortium registry (2011-2015). Using logistic regression, we modeled the likelihood of receiving BCPR by gender, including patient-level variables, stratified by location. A cohort of 19 331 OHCAs was assessed. Mean age was 64±17 years, and 63% (12 225/19 331) were male. Overall, 37% of OHCA victims received bystander CPR. In public locations, 39% (272/694) of females and 45% (1170/2600) of males received BCPR ( P<0.01), whereas in private settings, 35% (2198/6328) of females and 36% (3364/9449) of males received BCPR ( P=NS). Among public OHCAs, males had significantly increased odds of receiving BCPR compared with females (odds ratio, 1.27; 95% CI, 1.05-1.53; P=0.01); this was not the case in the private setting (odds ratio, 0.93; 95% CI, 0.87-1.01; P=NS). Controlling for site, age, and race, BCPR was significantly associated with survival to hospital discharge (odds ratio, 1.69; 95% CI, 1.54-1.85; P<0.01); in this model, males had 29% increased odds of survival compared with females (odds ratio, 1.29; 95% CI, 1.17-1.42; P<0.01). CONCLUSIONS: Males had an increased likelihood of receiving BCPR compared with females in public. BCPR improved survival to discharge, with greater survival among males compared with females.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.003 | 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".