Long-term survival in patients with refractory angina
Bibliographic record
Abstract
AIMS: An increasing number of patients with severe coronary artery disease (CAD) are not candidates for traditional revascularization and experience angina in spite of excellent medical therapy. Despite limited data regarding the natural history and predictors of adverse outcome, these patients have been considered at high risk for early mortality. METHODS AND RESULTS: The OPtions In Myocardial Ischemic Syndrome Therapy (OPTIMIST) program at the Minneapolis Heart Institute offers traditional and investigational therapies for patients with refractory angina. A prospective clinical database includes detailed baseline and yearly follow-up information. Death status and cause were determined using the Social Security Death Index, clinical data, and death certificates. Time to death was analysed using survival analysis methods. For 1200 patients, the mean age was 63.5 years (77.5% male) with 72.4% having prior coronary artery bypass grafting, 74.4% prior percutaneous coronary intervention, 72.6% prior myocardial infarction, 78.3% 3-vessel CAD, 23.0% moderate-to-severe left-ventricular (LV) dysfunction, and 32.6% congestive heart failure (CHF). Overall, 241 patients died (20.1%: 71.8% cardiovascular) during a median follow-up 5.1 years (range 0-16, 14.7% over 9). By Kaplan-Meier analysis, mortality was 3.9% (95% CI 2.8-5.0) at 1 year and 28.4% (95% CI 24.9-32.0) at 9 years. Multivariate predictors of all-cause mortality were baseline age, diabetes, angina class, chronic kidney disease, LV dysfunction, and CHF. CONCLUSION: Long-term mortality in patients with refractory angina is lower than previously reported. Therapeutic options for this distinct and growing group of patients should focus on angina relief and improved quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".