Off‐Pump Coronary Artery Bypass Grafting: Department of Veteran Affairs’ Use and Outcomes
Bibliographic record
Abstract
Background Coronary artery bypass can be performed off pump (OPCAB) without cardiopulmonary bypass. However, trends over time for OPCAB versus on‐pump (ONCAB) use and long‐term outcome has not been reported, nor has their long‐term outcome been compared. Methods and Results We queried the national Veterans Affairs database (2005–2019) to identify isolated coronary artery bypass procedures. Procedures were classified as OPCAB on ONCAB using the as‐treated basis. Trend analyses were performed to evaluate longitudinal changes in the preference for OPCAB. The median follow‐up period was 6.6 (3.5–10) years. An inverse probability weighted Cox model was used to compare all‐cause mortality between OPCAB and ONCAB. From 47 685 patients, 6759 (age 64±8 years) received OPCAB (14%). OPCAB usage declined from 16% (2005–2009) to 8% (2015–2019). Patients with triple vessel disease who received OPCAB received a lower mean number of grafts (2.8±0.8 versus 3.2±0.8; P <0.01). The ONCAB 5‐, 10‐, and 15‐year survival rates were 82.9% (82.5–83.3), 60.4% (59.8–61.1), and 37.2% (36.1–38.4); correspondingly, OPCAB rates were 80.7% (79.7–81.7), 57.4% (56–58.7), and 34.1% (31.7–36.6) ( P <0.01). OPCAB was associated with increased risk‐adjusted all‐cause mortality (hazard ratio, 1.15 [1.13–1.18]; P <0.01) and myocardial infarction (incident rate ratio, 1.16 [1.05–1.28]; P <0.01). Conclusions Over 15 years, OPCAB use declined considerably in Veterans Affairs medical centers. In Veterans Affairs hospitals, late all‐cause mortality and myocardial infarction rates were higher in the OPCAB cohort.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".