Validation of the Vancouver Chest Pain Rule: A Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVES: The objective was to validate the Vancouver Chest Pain Rule in an emergency department (ED) setting to identify very-low-risk patients with acute chest pain. METHODS: A prospective cohort study was conducted on consecutive patients 25 years of age and older presenting to the ED with a chief complaint of acute chest pain during January 2009 to July 2009. According to the Vancouver Chest Pain Rule, cardiac history, chest pain characteristics, physical and electrocardiogram (ECG) findings, and cardiac biomarker measurement (creatine kinase-myocardial band isoenzyme [CK-MB]) were used to identify patients with very low risk for developing acute coronary syndrome (ACS) in 30 days. The primary outcome was defined as developing ACS (myocardial infarction or non-ST-elevation myocardial infarction [MI]/unstable angina) within 30 days of ED presentation, and all diagnoses were made using predefined explicit criteria. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. RESULTS: Of 593 patients who were eligible for evaluation, 39 (6.6%) developed MI and 43 (7.3%) developed unstable angina. Among all patients, 292 (49.2%) patients could have been assigned to the very-low-risk group and discharged after a brief ED assessment according to the Vancouver Chest Pain Rule. Among these patients, four (1.4%) developed ACS within 30 days. Sensitivity of the rule was 95.1% (95% confidence interval [CI]=88.0% to 98.7%), specificity was 56.3% (95% CI=52.0% to 60.7%), positive prediction value was 25.9% (95% CI=21.0% to 31.0%), and negative prediction value was 98.6% (95% CI=96.5% to 99.6%). CONCLUSIONS: This study showed a lower sensitivity and higher specificity when applying the Vancouver Chest Pain Rule to this population as compared to the original study.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".