The effect of treatment timing on repeat revascularization in patients with stable ischemic heart disease
Bibliographic record
Abstract
Objectives: In patients with stable ischemic heart disease, there is no evidence for the effect of revascularization treatment timing on the need for repeat procedures. We aimed to determine if repeat revascularizations differed among patients who received coronary artery bypass graft surgery after the time recommended by physicians compared with those who had timely percutaneous coronary intervention. Methods: We identified 25,520 British Columbia residents 60 years or older who underwent first-time nonemergency revascularization for angiographically proven, stable left main or multivessel ischemic heart disease between January 1, 2001, and December 31, 2016. We estimated unadjusted and adjusted cumulative incidence functions for repeat revascularization, in the presence of death as a competing risk, after index revascularization or last staged percutaneous coronary intervention for patients undergoing delayed coronary artery bypass grafting compared with timely percutaneous coronary intervention. Results: After adjustment with inverse probability of treatment weights, at 3 years, patients who underwent delayed coronary artery bypass grafting had a statistically significant lower cumulative incidence of a repeat revascularization compared with patients who received timely percutaneous coronary intervention (4.84% delayed coronary artery bypass grafting, 12.32% timely percutaneous coronary intervention; subdistribution hazard ratio, 0.16, 95% CI, 0.04-0.65). Conclusions: Patients who undergo delayed coronary artery bypass grafting have a lower cumulative incidence of repeat revascularization than patients who undergo timely percutaneous coronary intervention. Patients who want to wait to receive coronary artery bypass grafting will see the benefit of lower repeat revascularization over percutaneous coronary intervention unaffected by a delay in treatment.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".