Abstract 195: Survival in Out-of-Hospital Cardiac Arrest Patients Without a Prehospital Return of Spontaneous Circulation
Bibliographic record
Abstract
Background: Survival rates are low in out-of-hospital cardiac arrest (OHCA) patients transported without a prehospital return of spontaneous circulation (ROSC). Few studies have examined the patient characteristics and prehospital factors associated with improved survival in this unique cohort. Objective: This study aims to describe patient and prehospital factors associated with survival to hospital discharge when patients fail to achieve ROSC in the field. Methods: This was a retrospective observational study of consecutive adult (≥18 years) OHCA patients without a prehospital ROSC from December 1, 2005 to March 30, 2012 who were attended to and transported by emergency medical services (EMS) from urban and rural regions employing the current termination of resuscitation (TOR) guidelines. EMS witnessed cardiac arrests, and cardiac arrests of non-cardiac etiology were excluded. Bivariate analyses were used to determine associations of patient characteristics and prehospital variables with survival to hospital discharge. Results: There were 17,488 OHCA treated by EMS, with 4,892 (28.0%) transported to hospital without a prehospital ROSC. Of these patients, only 42 (0.86%) survived to hospital discharge. Survivors were often younger with initial shockable rhythms, had OHCA that were more often witnessed by bystanders and occurred in public locations, compared to non-survivors (table). No differences were noted in the proportion of male gender, bystander CPR rates, EMS response time, advanced airway, or ALS provider level. Three patients (0.06%) did not meet the criteria for transport in accordance with current TOR guidelines however were transported at the discretion of EMS and survived. Conclusion: Less than 1% (the threshold for futility) of OHCA patients without a prehospital ROSC survived to hospital discharge. Survival in this cohort was associated with younger age, shockable initial rhythms, bystander-witnessed arrests, and public location.
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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 | 0.000 | 0.001 |
| 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".