Increased early postoperative morbidity with off-pump coronary artery bypass grafting surgery in patients with diabetes.
Bibliographic record
Abstract
BACKGROUND: Patients with diabetes constitute a high-risk population for myocardial revascularization due to extensive coronary disease. OBJECTIVE: To compare the early postoperative outcomes of patients with diabetes undergoing off-pump or on-pump coronary artery bypass surgery. METHODS AND RESULTS: Over a four-year period (1995 to 1998), 885 diabetics were operated for primary isolated coronary bypass; 156 patients had off-pump and 729 had on-pump coronary artery bypass surgery. Patients in the off-pump group were significantly older, had a higher incidence of hypertension and renal failure, and received fewer distal anastomoses (2.7 versus 2.9, P=0.004). Postoperative myocardial infarction, reintubation and postoperative use of intra-aortic balloon pump occurred significantly more frequently in the off-pump group (10.3% versus 5.5%, P=0.04; 8.3% versus 3.6%, P=0.03; 7.7% versus 1.5%, P=0.0001, respectively). Multivariate analysis revealed that type of surgery was an independent predictor of these complications, which occurred 1.9, 2.7 and 7.9 times more often, respectively, in the off-pump group. The 30-day mortality rate was not significantly different between the groups. CONCLUSIONS: Off-pump coronary artery bypass surgery is associated with an increased early postoperative morbidity in patients with diabetes and, thus, should be used with caution.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".