Survival After Coronary Revascularization in the Elderly
Bibliographic record
Abstract
BACKGROUND: Elderly patients with ischemic heart disease are increasingly referred for coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI). However, reports of poor outcomes in the elderly have led to questions about the benefit of these strategies. We studied survival by prescribed treatment (CABG, PCI, or medical therapy) for patients in 3 age categories: <70 years, 70 to 79 years, and > or =80 years of age. METHODS AND RESULTS: The Alberta Provincial Project for Outcomes Assessment in Coronary Heart Disease (APPROACH) is a clinical data collection and outcome monitoring initiative capturing all patients undergoing cardiac catheterization and revascularization in the province of Alberta, Canada, since 1995. Characteristics and long-term outcomes of a cohort of >6000 elderly patients with ischemic heart disease were compared with younger patients. In 15 392 patients >70 years of age, 4-year adjusted actuarial survival rates for CABG, PCI, and medical therapy were 95.0%, 93.8%, and 90.5%, respectively. In 5198 patients 70 to 79 years of age, survival rates were 87.3%, 83.9%, and 79.1%, respectively. In 983 patients > or = 80 years of age, survival was 77.4% for CABG, 71.6% for PCI, and 60.3% for medical therapy. Absolute risk differences in comparison to medical therapy for CABG (17.0%) and PCI (11.3%) were greater for patients > or =80 years of age than for younger patients. CONCLUSIONS: Elderly patients paradoxically have greater absolute risk reductions associated with surgical or percutaneous revascularization than do younger patients. The combination of these results with a recent randomized trial suggests that the benefits of aggressive revascularization therapies may extend to subsets of patients in older age groups.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".