Derivation of a Termination-of-resuscitation Guideline for Emergency Medical Technicians Using Automated External Defibrillators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To determine the association between characteristics of cardiac arrest and survival to hospital discharge following failed resuscitation by defibrillation-trained emergency medical technicians (EMT-Ds), and to propose an out-of-hospital termination-of-resuscitation (TOR) guideline for EMT-Ds. METHODS: A 22-month retrospective review of 700 out-of-hospital primary cardiac arrest patients in a large emergency medical services (EMS) system who received exclusively EMT-D care. RESULTS: Seven hundred primary cardiac arrest patients were identified. Follow-up was obtained in 662 cases (94.6%). Of these, 36 (5.4%) achieved a return of spontaneous circulation (ROSC) prior to transport. Among the 626 patients who failed to achieve ROSC at any time, two (0.3%) survived to discharge. Multivariate analysis showed that ROSC at any time had the strongest association with survival [odds ratio (OR) 45.5; 95% confidence interval (95% CI) = 8.5 to 243.7]. A shock prior to transport (OR 6.9; 95% CI = 1.2 to 40.3) and cardiac arrest witnessed by EMS personnel (OR 4.4; 95% CI = 1.0 to 18.5) were also independently associated with survival. These variables were incorporated into a TOR guideline. The guideline was 100% sensitive (95% CI = 99.1 to 100) in identifying survivors and had 100% negative predictive value (95% CI = 75.3 to 100) for identifying nonsurvivors of out-of-hospital cardiac arrest in the study population. CONCLUSIONS: In this EMS system, cardiac arrest patients may be considered for out-of-hospital TOR following EMT-D resuscitation attempts when there has been no ROSC, no shock has been given, and the arrest was not witnessed by EMS personnel. These guidelines require prospective validation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it