Abstract 13871: Does Compliance With a Global Cpr Quality Benchmark Predict Survival From Out-Of-Hospital Cardiac Arrest?
Bibliographic record
Abstract
Background: Measures of chest compression fraction (CCF), compression rate, compression depth and pre-shock pause have all been independently associated with improved outcomes from out-of-hospital (OHCA) cardiac arrest. However, it is unknown whether compliance with a global CPR quality benchmark, incorporating the aforementioned metrics, can predict OHCA survival. Methods: We performed a secondary analysis of prospectively collected data from the Resuscitation Outcomes Consortium Cardiac Arrest Epistry database. As per the 2015 American Heart Association (AHA) guidelines, high quality CPR was defined as CCF > 0.8, chest compression rate 100-120/minute, chest compression depth 50-60 mm and pre-shock pause< 10 seconds. To derive a global CPR quality benchmark, we created multiple models employing combinations of CPR metrics to assess relationships between CPR compliance and survival to hospital discharge. Multivariable logistic regression models controlling for age, gender, witnessed status, bystander CPR, location, presenting rhythm and site were used to assess the relationship between compliance with a global CPR quality benchmark, survival to hospital discharge and neurologically intact survival with MRS < 2. Results: We analyzed CPR process data from 35,445 defibrillator records collected over a 4 year time frame ending in June 2015. Of the 35,445 records, 19,568 (55.2%) included compression depth. For the primary model (CCF, rate, depth), there was no improvement in survival from OHCA comparing resuscitations that met no CPR quality benchmarks (reference) to those who met all CPR quality benchmarks (OR 0.89; 95% CI: 0.47, 1.70) and those who met some of the CPR quality benchmarks (OR 0.71; 95% CI: 0.45, 1.13). Models combining CCF, rate, depth and pre-shock pause yielded similar results for both shockable and non- shockable presenting rhythms when controlling for Utstein variables. Conclusions: When modeled in combination and adjusting for other predictors of survival, a global CPR quality benchmark using the current AHA guidelines was not associated with improved survival from OHCA. Unmeasured confounders, unknown combinations of optimal CPR quality metrics or possible interactions may explain our study findings.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".