Defining abnormal electrocardiography in adult emergency department syncope patients: the Ottawa Electrocardiographic Criteria.
Bibliographic record
Abstract
BACKGROUND: Previous studies have indicated that the suboptimal performance of the San Francisco Syncope Rule (SFSR) is likely due to the misclassification of the "abnormal electrocardiogram (ECG)" variable. We sought to identify specific emergency department (ED) ECG and cardiac monitor abnormalities that better predict cardiac outcomes within 30 days in adult ED syncope patients. METHODS: This health records review included patients 16 years or older with syncope and excluded patients with ongoing altered mental status, alcohol or illicit drug use, seizure, head injury leading to loss of consciousness, or severe trauma requiring admission. We collected patient characteristics, 22 ECG variables, cardiac monitoring abnormalities, SFSR "abnormal ECG" criteria, and outcome (death, myocardial infarction, arrhythmias, or cardiac procedures) data. Recursive partitioning was used to develop the "Ottawa Electrocardiographic Criteria." RESULTS: Among 505 included patient visits, 27 (5.3%) had serious cardiac outcomes. We found that patients were at risk for cardiac outcomes within 30 days if any of the following were present: second-degree Mobitz type 2 or third-degree atrioventricular (AV) block, bundle branch block with first-degree AV block, right bundle branch with left anterior or posterior fascicular block, new ischemic changes, nonsinus rhythm, left axis deviation, or ED cardiac monitor abnormalities. The sensitivity and specificity of the Ottawa Electrocardiographic Criteria were 96% (95% CI 80-100) and 76% (95% CI 75-76), respectively. CONCLUSION: We successfully identified specific ED ECG and cardiac monitor abnormalities, which we termed the Ottawa Electrocardiographic Criteria, that predict serious cardiac outcomes in adult ED syncope patients. Further studies are required to identify which adult ED syncope patients require cardiac monitoring in the ED and the optimal duration of monitoring and to confirm the accuracy of these criteria.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".