Outcomes with revascularisation versus conservative management of participants with 3-vessel coronary artery disease in the ISCHEMIA trial
Bibliographic record
Abstract
BACKGROUND: Whether revascularisation (REV) improves outcomes in patients with three-vessel coronary artery disease (3V-CAD) is uncertain. AIMS: Our objective was to evaluate outcomes with REV (percutaneous coronary intervention [PCI] or coronary artery bypass graft surgery [CABG]) versus medical therapy in patients with 3V-CAD. METHODS: ISCHEMIA participants with 3V-CAD on coronary computed tomography angiography without prior CABG were included. Outcomes following initial invasive management (INV) with REV (PCI or CABG) versus initial conservative management (CON) with medical therapy alone were evaluated. Regression modelling was used to estimate the outcomes if all participants were to undergo prompt REV versus those assigned to CON. Outcomes were cardiovascular (CV) death/myocardial infarction (MI), death, CV death, and quality of life. Bayesian posterior probability for benefit (Pr [benefit]) for 1 percentage point lower 4-year rates with REV versus CON were evaluated. RESULTS: Among 1,236 participants with 3V-CAD (612 INV/624 CON), REV was associated with lower 4-year CV death/MI (adjusted 4-year difference: -4.4, 95% credible interval [CrI] -8.7 to -0.3 percentage points, Pr [benefit]=94.8%) when compared with CON, with similar results for PCI versus CON (-5.8, 95% CrI: -10.8 to -0.5 percentage points, Pr [benefit]=96.4%) and CABG versus CON (-3.7, 95% CrI: -8.8 to 1.5 percentage points, Pr [benefit]=84.7%). Adjusted 4-year REV versus CON differences were as follows: death -1.2 (95% CrI: -4.7 to 2.2) percentage points, CV death -2.3 (95% CrI: -5.5 to 0.8) percentage points, with similar results for PCI and for CABG. The Pr (benefit) for death with REV (PCI or CABG) versus CON was 49-63%. The adjusted 12-month Seattle Angina Questionnaire-7 summary score differences favoured REV: REV versus CON 4.6 (95% CrI: 2.7-6.4) percentage points; PCI versus CON 3.6 (95% CrI: 1.2-5.8) percentage points and CABG versus CON 4.3 (95% CrI: 1.5-6.9) percentage points with high Pr (benefit). CONCLUSIONS: In participants with 3V-CAD, REV (either PCI or CABG) was associated with a lower 4-year CV death/MI rate and improved quality of life, with similar results for PCI versus CON and CABG versus CON. The differences in all-cause mortality between REV and CON were small with wide confidence intervals. (ClinicalTrials.gov: NCT01471522).
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".