Interventions to optimize dispatcher-assisted CPR instructions: A scoping review
Bibliographic record
Abstract
Aim: To review and summarize existing literature and knowledge gaps regarding interventions that have been tested to optimize dispatcher-assisted CPR (DA-CPR) instruction protocols for out-of-hospital cardiac arrest (OHCA). Methods: This scoping review was undertaken by an International Liaison Committee on Resuscitation (ILCOR) Basic Life Support scoping review team and guided by the ILCOR methodological framework and the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR). Studies were eligible for inclusion if they were published in peer-reviewed journals and evaluated interventions used to improve DA-CPR. The search was carried out in MEDLINE, EMBASE, Education Resources Information Center (ERIC), PsycINFO, the Cochrane Library, Evidence Based Medicine (EBM) Reviews, and the Campbell Library from 2000 to December 18, 2023. Results: = 1). Studies ranged in methodology from registry studies to randomized clinical trials with the majority being observational studies of simulated EMS calls for OHCA. Outcomes were highly variable but included rates of bystander CPR, confidence & willingness to perform CPR, time to initiation of bystander CPR, bystander CPR quality (including CPR metrics: chest compression depth and rate; chest compression fraction; full chest recoil, ventilation rate, overall CPR competency), rates of automated external defibrillator (AED) use, return of spontaneous circulation (ROSC) and survival. Overall, all interventions seem to be associated with potential improvement in bystander CPR and CPR metrics. Conclusion: There appears to be trends towards improvement on key outcomes however more research is needed. This scoping review highlights the lack of high-quality clinical research on any of the tested interventions to improve DA-CPR. There is insufficient evidence to explore the effectiveness of any of these interventions via systematic review.
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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 | 0.029 | 0.115 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".