Unmeasured Confounders in Observational Studies Comparing Bilateral Versus Single Internal Thoracic Artery for Coronary Artery Bypass Grafting: A Meta‐Analysis
Bibliographic record
Abstract
Background Observational studies suggest a survival advantage with bilateral single internal thoracic artery (BITA) versus single internal thoracic artery grafting for coronary surgery, whereas this conclusion is not supported by randomized trials. We hypothesized that this inconsistency is attributed to unmeasured confounders intrinsic to observational studies. To test our hypothesis, we performed a meta‐analysis of the observational literature comparing BITA and single internal thoracic artery, deriving incident rate ratio for mortality at end of follow‐up and at 1 year. We postulated that BITA would not affect 1‐year survival based on the natural history of coronary artery bypass occlusion, so that a difference between groups at 1 year could not be attributed to the intervention. Methods and Results We searched MEDLINE and Pubmed to identify all observational studies comparing the outcome of BITA versus single internal thoracic artery. One‐year and long‐term mortality for BITA and single internal thoracic artery were compared in the propensity‐score–matched (PSM) series, that is, the form of observational evidence less prone to confounders. Thirty‐eight observational studies (174 205 total patients) were selected for final comparison. In the 12 propensity‐score–matched series (34 019 patients), the mortality reduction for BITA was similar at 1 year and at the end of follow‐up (incident rate ratio, 0.70; 95% confidence interval, 0.60–0.82 versus 0.77; 95% confidence interval, 0.70–0.85; P for subgroup difference=0.43). Conclusions Unmeasured confounders, rather than biological superiority, may explain the survival advantage of BITA in observational series.
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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 | 0.029 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.048 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".