Outcomes after surgical revascularization in diabetic patients
Bibliographic record
Abstract
OBJECTIVES: Patients with diabetes mellitus (DM) undergoing coronary artery bypass grafting (CABG) have been repeatedly demonstrated to have worse clinical outcomes compared to patients without DM. The objective of this study was to evaluate the impact of DM on 1-year clinical outcomes after isolated CABG. METHODS: The European DuraGraft registry included 1130 patients (44.6%) with and 1402 (55.4%) patients without DM undergoing isolated CABG. Intra-operatively, all free venous and arterial grafts were treated with an endothelial damage inhibitor. Primary end point in this analysis was the incidence of a major adverse cardiac event (MACE), a composite of all-cause death, repeat revascularization or myocardial infarction at 1 year post-CABG. To balance between differences in baseline characteristics (n = 1072 patients in each group), propensity score matching was used. Multivariable Cox proportional hazards regression was performed to identify independent predictors of MACE. RESULTS: Diabetic patients had a higher cardiovascular risk profile and EuroSCORE II with overall more comorbidities. Patients were comparable in regard to surgical techniques and completeness of revascularization. At 1 year, diabetics had a higher MACE rate {7.9% vs 5.5%, hazard ratio (HR) 1.43 [95% confidence interval (CI) 1.05-1.95], P = 0.02}, driven by increased rates of death [5.6% vs 3.5%, HR 1.61 (95% CI 1.10-2.36), P = 0.01] and myocardial infarction [2.8% vs 1.4%, HR 1.99 (95% CI 1.12-3.53) P = 0.02]. Following propensity matching, no statistically significant difference was found for MACE [7.1% vs 5.7%, HR 1.23 (95% CI 0.87-1.74) P = 0.23] or its components. Age, critical operative state, extracardiac arteriopathy, ejection fraction ≤50% and left main disease but not DM were identified as independent predictors for MACE. CONCLUSIONS: In this study, 1-year outcomes in diabetics undergoing isolated CABG were comparable to patients without DM.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".