Evaluation of extracorporeal cardiopulmonary resuscitation eligibility criteria for out-of-hospital cardiac arrest patients
Bibliographic record
Abstract
OBJECTIVES: To evaluate the number of out-of-hospital cardiac arrest (OHCA) patients eligible for extracorporeal cardiopulmonary resuscitation (ECPR) in Saskatchewan and their clinical outcomes, including survival and neurological outcomes at discharge. ECPR eligibility was assessed, using clinical criteria from the University of British Columbia (UBC, Canada), University of Michigan (UM, United States), University of California (UC, United States) and a restrictive ECPR criteria. RESULTS: We performed a retrospective cohort study of 200 OHCA patients (August 1, 2017-May 31, 2019) in Regina, Saskatchewan. Sixty-one (30%) were female, the median age was 64 years (interquartile range [IQR], 52-78), the median CPR duration was 30 min (IQR 12-47), and 20% survived to discharge. Two (1%) patients received ECPR but did not meet any ECPR criteria. Nineteen (10%), thirty (15%), twenty-two (11%), and seven (4%) patients were ECPR-eligible, using the UBC, UM, UC, and restrictive criteria. However, none of these patients had received ECPR. Only two (11%), two (7%), two (9%), and one (14%) of these patient(s) survived to discharge, respectively. Neurological outcomes were unfavourable among all ECPR-eligible patients. Future study at our centre will be necessary on how to implement ECPR program to further improve these outcomes.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".