Risk score for predicting death, myocardial infarction, and stroke in patients with stable angina, based on a large randomised trial cohort of patients
Bibliographic record
Abstract
OBJECTIVE: To derive a risk score for the combination of death from all causes, myocardial infarction, and disabling stroke in patients with stable symptomatic angina who require treatment for angina and have preserved left ventricular function. DESIGN: Multivariate Cox regression analysis of data from a large multicentre trial. SETTING: Outpatient cardiology clinics in western Europe, Israel, Canada, Australia, and New Zealand. PARTICIPANTS: 7311 patients with all required data available. MAIN OUTCOME MEASURE: Death from any cause or myocardial infarction or disabling stroke during a mean follow-up of 4.9 years. RESULTS: 1063 patients either died from any cause or sustained myocardial infarction or disabling stroke. The five year risk of this composite ranged from 4% for patients in the lowest tenth of risk to 35% for patients in the highest tenth. The risk score combines 16 routinely available clinical variables (in order of decreasing contribution): age, left ventricular ejection fraction, smoking, white blood cell count, diabetes, casual blood glucose concentration, creatinine concentration, previous stroke, at least one angina attack a week, coronary angiographic findings (if available), lipid lowering treatment, QT interval, systolic blood pressure > or = 155 mm Hg, number of drugs used for angina, previous myocardial infarction, and sex. Fitting the same model separately to all cause death, myocardial infarction, and stroke gave similar results. The risk score did not seem to predict the nature of the event (death in 39%, myocardial infarction in 46%, and disabling stroke in 15%) or the incidence of angiography or revascularisation, which occurred in 29% of patients. CONCLUSION: This risk score is an objective aid in deciding on further management of patients with stable angina with the aim of reducing serious outcome events. The score can also be used in planning future trials.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".