Coronary Artery Bypass Grafting After Recent or Remote Percutaneous Coronary Intervention in the Commonwealth of Massachusetts
Bibliographic record
Abstract
BACKGROUND: In this study, we sought to characterize the outcomes after isolated coronary artery bypass grafting (CABG) in patients with a history of remote (≥14 days), and recent (<14 days), percutaneous coronary intervention (PCI). METHODS AND RESULTS: Patients with PCI within 5 years of CABG were identified among 12 591 primary isolated CABG reported in the mandatory Massachusetts Adult Cardiac Surgery Database. Patients were excluded if they were out-of-state (n=1043, 8%), had undergone primary PCI for acute myocardial infarction (n=401, 3%), had a PCI-CABG interval >5 years or unknown (n=136 and n=673, 1% and 5%). Patients with a history of remote and recent PCI were analyzed separately. Each CABG patient with PCI was matched to 3 patients without PCI using a propensity score. Outcomes were analyzed using generalized estimating equations and stratified proportional hazards models, with a mean follow-up of 4.1±1.2 years. There were 1117 CABG patients (9%) with prior PCI (n(remote)=823; n(recent)=294). In matched CABG patients with remote prior PCI, no differences were found in 30-day mortality (1.1% versus 1.5%; P=0.432), hospital morbidity (41% versus 40%; P=0.385) and overall survival (hazard ratio, [95% confidence interval] for death for prior PCI, 0.93 [0.74 to 1.18]; P=0.555). In matched CABG patients with recent prior PCI, hospital morbidity was higher (59% versus 45%; P<0.001), but no differences were found in 30-day mortality (3.5% versus 3.1%; P=0.754) and overall survival (HR, 1.18 [0.83 to 1.69]; P=0.353). CONCLUSIONS: In patients undergoing CABG, remote prior PCI (≥14 days) was not associated with adverse outcomes at 30 days or during long-term follow-up.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".