Use Rate and Outcome in Bilateral Internal Thoracic Artery Grafting: Insights From a Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: This meta-analysis was designed to assess whether center experience affects the short- and long-term results and the relative benefits of bilateral internal thoracic artery grafting (BITA) for coronary artery bypass grafting. METHODS AND RESULTS: MEDLINE and EMBASE were searched to identify all articles reporting the outcome of BITA in patients undergoing coronary artery bypass grafting. The BITA center experience was gauged according to the percentage use of BITA in the institutional overall coronary artery bypass grafting population (%BITA). The primary outcome was long-term all-cause mortality. Secondary outcomes were operative mortality, perioperative myocardial infarction, perioperative stroke, deep sternal wound infections (DSWIs), and major postoperative adverse event. The rates of the primary and secondary outcomes were calculated after adjusting for %BITA. Primary and secondary outcomes were also compared between the BITA and the single internal thoracic artery arms in the adjusted studies. Meta-regression was used to evaluate the effect of %BITA on the primary and secondary outcomes. Thirty-four studies (27 894 patients undergoing BITA) were included. In the pooled analysis, the incidence rate for long-term mortality was 2.83% (95% confidence interval, 2.21%-3.61%). %BITA was significantly and inversely associated with long-term mortality and the rate of DSWI. In the pairwise comparison, %BITA was significantly and inversely associated with the risk of long-term mortality and DSWI in the group undergoing BITA. CONCLUSIONS: BITA series with higher %BITA report significantly lower long-term mortality and DSWI rate as well as higher long-term survival advantage and lower relative risk of DSWI in their BITA cohort. These findings suggest that a specific volume-outcome relationship exists for BITA grafting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".