Assessing feasibility of proposed extracorporeal cardiopulmonary resuscitation programmes for out-of-hospital cardiac arrest in Scotland via geospatial modelling
Bibliographic record
Abstract
BACKGROUND: Extracorporeal cardiopulmonary resuscitation (ECPR) can improve survival for refractory out-of-hospital cardiac arrest (OHCA). We sought to assess the feasibility of a proposed ECPR programme in Scotland, considering both in-hospital and pre-hospital implementation scenarios. METHODS: We included treated OHCAs in Scotland aged 16-70 between August 2018 and March 2022. We defined those clinically eligible for ECPR as patients where the initial rhythm was ventricular fibrillation, ventricular tachycardia, or pulseless electrical activity, and where pre-hospital return of spontaneous circulation was not achieved. We computed the call-to-ECPR access time interval as the amount of time from emergency medical service (EMS) call reception to either arrival at an ECPR-ready hospital or arrival of a pre-hospital ECPR crew. We determined the number of patients that had access to ECPR within 45 min, and estimated the number of additional survivors as a result. RESULTS: A total of 6,639 OHCAs were included in the geospatial modelling, 1,406 of which were eligible for ECPR. Depending on the implementation scenario, 52.9-112.6 (13.8-29.4%) OHCAs per year had a call-to-ECPR access time within 45 min, with pre-hospital implementation scenarios having greater and earlier access to ECPR for OHCA patients. We further estimated that an ECPR programme in Scotland would yield 11.8-28.2 additional survivors per year, with the pre-hospital implementation scenarios yielding higher numbers. CONCLUSION: An ECPR programme for OHCA in Scotland could provide access to ECPR to a modest number of eligible OHCA patients, with pre-hospital ECPR implementation scenarios yielding higher access to ECPR and higher numbers of additional survivors.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".