Abstract 265: Perioperative Silent Myocardial Ischemia, the Use of Blood Transfusions and Their Associations With Long-Term Mortality Following Peripheral Vascular Surgery
Bibliographic record
Abstract
Objective Thrombotic and bleeding complications during the perioperative period are a major concern during the postoperative period. However, the relationship between perioperative myocardial necrosis and major bleeding with long-term mortality is uncertain. Methods In a retrospective study, we analyzed data from 289 consecutive patients during a one-year period between 2009-2010 who underwent open major vascular surgery (carotid endarterectomy, above/below knee amputation, open aneurysm repair, extremity bypass, and embolectomy). Myocardial necrosis was defined as any cardiac troponin T value ≥ 0.1 ng/ml and major bleeding was defined as requiring ≥2 units of blood within 24 hours of the operation. Lower threshold cutoffs (troponin >0.04 ng/ml and any transfusion) were also investigated. Odds ratios (OR) and 95% confidence intervals (CI) were estimated by logistic regression. Results During a mean follow-up period of 1.8 years, there were 46 deaths (15.9%). Myocardial necrosis and major bleeding occurred in 25.2% and 14.9% of subjects, respectively. After adjustment for age, sex, smoking, hypertension, diabetes and coronary artery disease, both myocardial necrosis (OR 4.24, 95% CI 1.82-9.87) and major bleeding (OR 2.56, 95% CI 1.28-5.46) were associated with long-term death. Similarly, lower threshold cutoffs of troponin >0.04 ng/ml and any transfusion independently predicted a 6.27-fold and a 6.44-fold increase in long-term mortality (p<0.001 for both). Conclusions Perioperative myocardial necrosis and major bleeding, even at low cutoff levels, are independent and complementary predictors of long-term mortality following major vascular surgery.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".