Abstract 8: Influence of Receiving Hospital Characteristics on Survival after Cardiac Arrest
Bibliographic record
Abstract
Hospital management of out-of-hospital cardiac arrest (OHCA) patients after return of spontaneous circulation (ROSC) can influence patient survival via interventions such as hypothermia and cardiac catheterization (CATH). This study tested the hypothesis that survival differed between different types of hospitals for subjects with ROSC after OHCA. Methods: Adult (≥ 18 years) subjects with paramedic-documented ROSC or who lived >1 day after OHCA were identified with their receiving hospital in a prospective database from 9 regions in the US and Canada. Hospitals were characterized using the American Hospital Directory or the Guide to Canadian Healthcare Facilities. Hospitals were categorized by bed number (large >400; medium 250 – 400; small <250) and CATH capability. Associations between clinical variables, hospital categories, survival time, and survival to hospital discharge were determined using Cox regression and analysis of variance. Results: Between December 2005 and July 2007, 3644 OHCA subjects were treated in 254 hospitals, with similar numbers in large (1026), medium (1094) and small (1276) hospitals. CATH hospitals treated 2123 (58%) subjects, and patient features (63% male, 42% VF/VT, 67% witnessed collapse, and mean call-arrival interval of 5.7 (SD 2.8) minutes) did not differ between hospital categories. CATH hospitals had higher survival than non-CATH hospitals in large (35.1% vs. 27.7%), medium (34.4% vs. 30.7%) and small (38.6% vs. 26.5%) categories (F=19.55; p<0.001). VF/VT (p < 0.001), age (p < 0.001) and witnessed collapse (p < 0.001) were associated with survival time. When adjusted for initial rhythm, call-arrival interval, witnessed collapse, age, sex, region, teaching institution, and trauma center level, there was no significant effect of CATH. However, the interaction of large hospital and CATH was associated with lower hazard of death (0.71, 95% CI [0.54, 0.93]). Conclusions: Transport to a CATH hospital is associated with increased probability of survival to discharge after OHCA. These data cannot determine whether cardiac catheterization was performed or if CATH hospital is a surrogate for more comprehensive cardiac care. Therefore, further work should examine what aspects of in-hospital care affected outcome.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".