Time-Varying Association of the Second Internal Thoracic Artery with Long-Term Survival after Coronary Artery Bypass Grafting
Bibliographic record
Abstract
Abstract The survival advantages of bilateral internal thoracic artery (BITA) grafts in coronary artery bypass grafting (CABG) surgery remain unclear. Therefore, this study aims to systematically evaluate the time-dependent influence of BITA on long-term survival in elective CABG patients presenting with stable multivessel coronary artery disease. Data from 3,693 patients undergoing isolated CABG with single internal thoracic artery (SITA) or BITA, with or without additional vein grafts, between 2002 and 2012 were retrospectively analyzed. The entire cohort was divided into BITA and SITA groups (830 vs. 2,863 patients). A 1:3 propensity score matching was performed. Subsequent analysis of a subgroup meeting Randomized comparison of the clinical Outcome of single versus Multiple Arterial grafts (ROMA) trial criteria (n = 1,339) followed a 1:1 matching. Differences in restricted mean survival time (RMST) estimates were used to assess the time-varying association of BITA with long-term survival. In-hospital mortality (SITA 1.8% vs. BITA 1.1%, p = 0.2) and major postoperative complications were similar between the matched groups. However, long-term survival was significantly higher in BITA patients for the matched whole cohort (15-year survival: 64 vs. 51%, respectively; p < 0.001) and the ROMA-like population (76 vs. 60%, respectively; p < 0.001). RMST demonstrated an incremental survival advantage of BITA over SITA grafting over time for both the whole and ROMA-like populations (0.1, 0.5, and 1.1 years, and 0.1, 0.4, and 1.0 years at 5-, 10-, and 15-year follow-up, respectively) BITA grafting is safe and associated with superior long-term survival compared with SITA and vein grafts, with benefits extending beyond 5 years for the entire cohort and beyond 10 years for ROMA criteria patients.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".