Abstract 12684: Cpr Quality During Out- Of- Hospital Cardiac Arrest Transport
Bibliographic record
Abstract
Background: Previous studies have demonstrated significant associations between cardiopulmonary resuscitation (CPR) quality metrics and survival to hospital discharge following out-of- hospital cardiac arrest (OHCA). No large study has explored the relationship between location of resuscitation (scene vs. transport) and CPR quality. Objective: We sought to determine the impact of CPR location on CPR quality metrics during OHCA. Methods: We performed a retrospective cohort study of prospectively collected data from the Toronto RescuNET Epistry- cardiac arrest database. We analyzed CPR quality data from all treated adult OHCA occurring over a 39 month period beginning January 1, 2013. We included OHCA patients who underwent resuscitation by emergency medical services and had CPR quality metric data for both scene and transport phases of the resuscitation. Based on 2010 American Heart Association guidelines, high quality CPR was defined as chest compression fraction (CCF)> 0.70, compression rate >100/min and compression depth > 5.0 cm. Scene and transport CPR quality metrics were compared for each patient using a Wilcoxon rank-sum paired-samples test . The proportion of patients who received high quality CPR (defined as meeting all 3 CPR quality benchmarks) was compared between resuscitation locations using a chi-square statistic. Results: Amongst 842 included patients (69.5% male, mean (SD) age 66.8±17.0), median compression rate was statistically higher on scene compared to transport (105.8 vs. 102.0 ; Δ 3.8; 95% CI: 2.5, 4.0), while median compression depth (5.56 vs. 5.33; Δ 0.23; 95% CI: 0.12, 0.26) and median CCF (0.95 vs. 0.87; Δ 0.08; 95% CI: 0.07, 0.08) were statistically higher during the transport phase. The proportion of patients with high quality CPR was similar on scene compared to during transport (45.8% vs. 42.5%; Δ 3.3; 95% CI: -1.4, 8.1). Conclusions: High quality CPR metrics were identified in both (scene and transport) locations of resuscitation and exceeded current CPR quality benchmarks. These results suggest that high quality, manual compressions can be performed by well-trained EMS systems regardless of location. Further study is required to determine whether these metrics can be replicated in other EMS jurisdictions.
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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 | 0.005 |
| 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 | 0.001 | 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".