Current Use, Capacity, and Perceived Barriers to the Use of Extracorporeal Cardiopulmonary Resuscitation for Out-of-Hospital Cardiac Arrest in Canada
Bibliographic record
Abstract
BACKGROUND: Extracorporeal cardiopulmonary resuscitation (ECPR) is a therapeutic option for refractory cardiac arrest. We sought to perform an environmental scan to describe ECPR utilization in Canada and perceived barriers for application to out-of-hospital cardiac arrest (OHCA). METHODS: This was a national cross-sectional study. We identified all cardiovascular surgery- and extracorporeal membrane oxygenation (ECMO)-capable hospitals in Canada and emergency medical services (EMS) agencies delivering patients to those centres. We requested the medical lead from each hospital's ECMO service and each EMS agency to submit data regarding ECMO and ECPR utilization, as well as perceived barriers to ECPR provision for OHCA. RESULTS: We identified and received survey data from 39 of 39 Canadian hospital institutions and 21 of 22 EMS agencies. Of hospitals, 38 (97%) perform ECMO and 27 (69%) perform ECPR (74% of which perform ≤5 cases per year). Of the 18 (46%) sites offering ECPR for OHCA, 8 apply a formal protocol for eligibility and initiation procedures. EMS agencies demonstrate heterogeneity with intra-arrest transport practices. The primary rationale for nontransport of refractory OHCA is that hospital-based care offers no additional therapies. Perceived barriers to the use of ECPR for OHCA were primarily related to limited evidence supporting its use, rather than resources required. CONCLUSION: Many Canadian cardiovascular surgery- or ECMO-equipped hospitals use ECPR; roughly half employ ECPR for OHCAs. Low case volumes and few formal protocols indicate that this is not a standardized therapy option in most centres. Increased application may be dependent on a stronger evidence base including data from randomized clinical trials currently underway.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".