Prospective validity of measuring angina severity with Canadian Cardiovascular Society class: The ACRE study.
Bibliographic record
Abstract
BACKGROUND: Although the prevalence of angina remains high, the importance of grading angina severity is unclear. OBJECTIVES: To determine the extent to which angina severity is associated with angiographic findings, and the rate of revascularization, mortality and nonfatal myocardial infarction. METHODS: Prospective, population-based study with a 2.5-year follow-up of 2849 consecutive patients with angina undergoing coronary angiography at Barts and the London NHS Trust, London, United Kingdom, in the Appropriateness of Coronary Revascularisation (ACRE) study. Angina severity was assessed with the Canadian Cardiovascular Society (CCS) classification, ranging from class I (mild) to IV (severe). Outcome measures were revascularization rates, and all-cause mortality and nonfatal myocardial infarction. RESULTS: In age-adjusted analyses, a higher CCS class was linearly associated (P<0.001) with a higher number of diseased vessels and impaired left ventricular function. When adjusting for age, sex, smoking, history of hypertension, diabetes, number of diseased vessels, left ventricular function, use of acetylsalicylic acid, beta-blockers or statins, and revascularization status (for death and nonfatal myocardial infarction), a higher CCS class was linearly associated with higher coronary angioplasty (P<0.001) and bypass graft (P=0.03) rates, and lower all-cause mortality and nonfatal myocardial infarction (P<0.001; CCS IV versus I: hazard ratio 2.44, 95% CI 1.46 to 4.09). CONCLUSION: CCS class was linearly associated with angiographic findings, revascularization rates, mortality and nonfatal myocardial infarction. These findings support the importance of a four-level grading of symptom severity among angina patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".