Abstract 344: The Association Between ALS Response Interval and Out-of Hospital Cardiac Arrest Outcomes
Bibliographic record
Abstract
Objective: There is conflicting data in studies investigating the effectiveness of advanced life support (ALS) for out-of-hospital cardiac arrest (OHCA). Within a tiered BLS-ALS system, we sought to determine if the ALS response interval was associated with patient outcomes. Methods: This secondary analysis examined prospectively identified consecutive non-traumatic adult OHCAs from 2006-2016 in British Columbia. We excluded EMS-witnessed arrests and those not treated by ALS. The primary and secondary outcomes were survival and favorable neurological outcomes (mRS ≤3) at hospital discharge. Using logistic regression we estimated the association of ALS response interval (9-1-1 call to ALS arrival) and outcomes, adjusting for treatment year, response interval of the first EMS unit, and other baseline characteristics. We drew spline curves to illustrate this relationship. Results: Of 12,722 included cases, survival was 12%. The median response interval for the first EMS unit was 6.4 minutes (IQR 5.2 - 8.3) and for ALS was 11.8 minutes (IQR 8.7 - 16.5).The adjusted odds of survival and favourable neurological outcome for each additional minute in ALS response interval were 0.98 (95 % CI 0.96-0.99) and 0.98, (95% CI 0.97-0.99) respectively. The spline curve demonstrated an initial decline in survival probability that moderated at approximately 11 minutes. Conclusion: Among ALS-treated subjects within our tiered EMS system, earlier ALS arrival was associated with improved survival and favorable neurological outcomes. The greatest yield of ALS care may be prior to 11 minutes. This may help inform the optimal deployment configuration of prehospital providers.
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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 | 0.002 | 0.013 |
| 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) | 0.007 | 0.001 |
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".