Clinical outcomes and quality of life after contemporary isolated coronary bypass grafting: a prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: The objective of the European Multicenter Registry to Assess Outcomes in coronary artery bypass grafting (CABG) patients (DuraGraft Registry) was to determine clinical outcomes and quality of life (QoL) after contemporary CABG that included isolated CABG and combined CABG/valve procedures, using an endothelial damage inhibitor (DuraGraft) intraoperatively for conduit preservation. Here, we report outcomes in the patient cohort undergoing isolated CABG. METHODS: The primary outcome was the composite of all-cause death, myocardial infarction (MI), or repeat revascularization (RR) [major adverse cardiac events (MACE)] at 1 year. Secondary outcomes included the composite of all-cause death, MI, RR, or stroke [major adverse cardiac and cerebrovascular events (MACCE)], and QoL. QoL was assessed with the EuroQol-5 Dimension questionnaire. Independent risk factors for MACE at 1 year were determined using Cox regression analysis. RESULTS: A total of 2532 patients (mean age, 67.4±9.2 years; 82.5% male) underwent isolated CABG. The median EuroScore II was 1.4 [interquartile range (IQR), 0.9-2.3]. MACE and MACCE rates at 1 year were 6.6% and 7.8%, respectively. The rates of all-cause death, MI, RR, and stroke were 4.4, 2.0, 2.2, and 1.9%, respectively. The 30-day mortality rate was 2.3%. Age, extracardiac arteriopathy, left ventricular ejection fraction less than 50%, critical operative state, and left main disease were independent risk factors for MACE. QoL index values improved from 0.84 [IQR, 0.72-0.92] at baseline to 0.92 [IQR, 0.82-1.00] at 1 year ( P <0.0001). CONCLUSION: Contemporary European patients undergoing isolated CABG have a low 1-year clinical event rate and an improved QoL.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".