Disagreement Between Randomized and Observational Evidence on the Use of Bilateral Internal Thoracic Artery Grafting: A Meta‐Analytic Approach
Bibliographic record
Abstract
Background The ART (Arterial Revascularization Trial) showed no difference in survival at 10 years between patients assigned to the single versus bilateral internal thoracic artery grafting strategies. This finding is in contrast with the results of most observational studies, where the use of 2 internal thoracic arteries has been associated with improved survival. Methods and Results We selected propensity-matched studies from the most comprehensive observational meta-analysis on the long-term outcomes of patients receiving 1 versus 2 internal thoracic arteries. Individual participant survival data from each study and the ART were reconstructed using an iterative algorithm that was applied to solve the Kaplan-Meier equations. The reconstructed individual participant survival data were aggregated to obtain combined survival curves and Cox regression hazard ratios with 95% CIs. Individual participant survival data were obtained from 14 matched observational studies (24 123 patients) and the ART. The 10-year survival of the control group of ART was significantly higher than that of the matched observational studies (hazard ratio, 0.86; 95% CI, 0.80-0.93). The 10-year survival of the experimental group of ART was significantly lower than that of the bilateral internal thoracic artery group of the observational studies (hazard ratio, 1.11; 95% CI, 1.03-1.20). Conclusions Both the improved outcome of the control arm and the lower beneficial effect of the intervention had played a role in the difference between observational evidence and ART.
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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 | 0.367 | 0.554 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".