P2749Is relying on ST depression to help predict coronary artery disease after an out-of-hospital cardiac arrest harming patients?
Bibliographic record
Abstract
Background: Following an out-of-hospital cardiac arrest (OHCA), guidelines support immediate coronary angiography (CA) for patients with acute ST-elevation (STE), although no such recommendations exist for ST-depression (STD). Purpose: To examine the relationship between the documented arrest rhythm and immediate post-arrest ECG on CA findings in a large cohort of OHCA patients. Methods: We performed a retrospective analysis of consecutive patients with OHCA in the Metro Vancouver region from 2009–2015, using the Resuscitation Outcomes Consortium Cardiac Arrest Registry. Patients that did not survive to admission, or with known non-cardiac cause for OHCA were excluded. ST-segment change of >0.1mV in 2 contiguous leads was considered significant. Coronary artery disease was defined as stenosis (any artery ≥70% or left main ≥50%) or occlusion (any artery 99–100%). Results: A total of n=604 OHCA met all inclusion criteria. The median age was 64-y (range 20–101 y) with 75% males. Most cardiac arrests were witnessed (67%) with 60% receiving bystander CPR. The documented arrest rhythm was ventricular tachycardia/fibrillation (VT/VF; 50%), pulseless electrical activity (18%), asystole (19%), and unspecified (12%). After exclusion of LBBB (n=22) and uninterpretable ECGs (n=36), the immediate post-arrest ECG demonstrated STE (35%), STD (30%), and no ST abnormality (35%). The overall rate of CA was 45% with most undergoing CA within 0–1 days of admission (median 0 days, IQR 0–1 days).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".