Out-of-Hospital Cardiac Arrest Protocol Comparison
Bibliographic record
Abstract
Background Early identification of out-of-hospital cardiac arrest (OHCA) has been proven to increase survival rates. Toward this goal, emergency medical dispatchers commonly use one of two types of emergency medical dispatcher systems, each with a unique OHCA protocol. The criteria-based dispatch (CBD) protocol is a set of guidelines and prompts intended for dispatchers with clinical background and experience, while the medical priority dispatch (MPD) is a scripted caller interrogation protocol intended for non-healthcare dispatchers. The objective of this study was to compare CBD and MPD protocols in terms of accuracy and duration of the identification process. Methods To compare the two protocols we conducted an OHCA simulation of an emergency phone call by a bystander. Two groups participated in the simulation: 1) emergency medical technicians during paramedic vocational training, in the role of CBD dispatchers, and 2) non-healthcare personnel in the role of MPD dispatchers. Dispatchers were asked to identify whether a patient was having a cardiac arrest based on the information they received from the bystander. Results Duration of the OHCA identification process was significantly shorter for participants using MPD (CBD 50 seconds vs. MPD 33 seconds, p=0.003). The OHCA accuracy was 86.49% for the CBD and 82.86% for MPD, but this difference was not statistically significant (p=0.60). Conclusion The advantages of each protocol suggest that some combination of the two protocols may optimise the OHCA identification process, leading to increased accuracy and shorter duration of the identification process.
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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 | 0.026 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".