Regional Variation in Out-of-Hospital Cardiac Arrest Survival in the United States
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Bibliographic record
Abstract
BACKGROUND: Although previous studies have shown marked variation in out-of-hospital cardiac arrest survival across US regions, factors underlying this survival variation remain incompletely explained. METHODS AND RESULTS: Using data from the Cardiac Arrest Registry to Enhance Survival, we identified 96 662 adult patients with out-of-hospital cardiac arrest in 132 US counties. We used hierarchical regression models to examine county-level variation in rates of survival and survival with functional recovery (defined as Cerebral Performance Category score of 1 or 2) and examined the contribution of demographics, cardiac arrest characteristics, bystander cardiopulmonary resuscitation, automated external defibrillator use, and county-level sociodemographic factors in survival variation across counties. A total of 9317 (9.6%) patients survived to discharge, and 7176 (7.4%) achieved functional recovery. At a county level, there was marked variation in rates of survival to discharge (range, 3.4%-22.0%; median odds ratio, 1.40; 95% confidence interval, 1.32-1.46) and survival with functional recovery (range, 0.8%-21.0%; median odds ratio, 1.53; 95% confidence interval, 1.43-1.62). County-level rates of bystander cardiopulmonary resuscitation and automated external defibrillator use were positively correlated with both outcomes (P<0.0001 for all). Patient demographic and cardiac arrest characteristics explained 4.8% and 27.7% of the county-level variation in survival, respectively. Additional adjustment of bystander cardiopulmonary resuscitation and automated external defibrillator explained 41% of the survival variation, and this increased to 50.4% after adjustment of county-level sociodemographic factors. Similar findings were noted in analyses of survival with functional recovery. CONCLUSIONS: Although out-of-hospital cardiac arrest survival varies significantly across US counties, a substantial proportion of the variation is attributable to differences in bystander response across communities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it