Myocardial Injury after Noncardiac Surgery
Bibliographic record
Abstract
BACKGROUND: Myocardial injury after noncardiac surgery (MINS) was defined as prognostically relevant myocardial injury due to ischemia that occurs during or within 30 days after noncardiac surgery. The study's four objectives were to determine the diagnostic criteria, characteristics, predictors, and 30-day outcomes of MINS. METHODS: In this international, prospective cohort study of 15,065 patients aged 45 yr or older who underwent in-patient noncardiac surgery, troponin T was measured during the first 3 postoperative days. Patients with a troponin T level of 0.04 ng/ml or greater (elevated "abnormal" laboratory threshold) were assessed for ischemic features (i.e., ischemic symptoms and electrocardiography findings). Patients adjudicated as having a nonischemic troponin elevation (e.g., sepsis) were excluded. To establish diagnostic criteria for MINS, the authors used Cox regression analyses in which the dependent variable was 30-day mortality (260 deaths) and independent variables included preoperative variables, perioperative complications, and potential MINS diagnostic criteria. RESULTS: An elevated troponin after noncardiac surgery, irrespective of the presence of an ischemic feature, independently predicted 30-day mortality. Therefore, the authors' diagnostic criterion for MINS was a peak troponin T level of 0.03 ng/ml or greater judged due to myocardial ischemia. MINS was an independent predictor of 30-day mortality (adjusted hazard ratio, 3.87; 95% CI, 2.96-5.08) and had the highest population-attributable risk (34.0%, 95% CI, 26.6-41.5) of the perioperative complications. Twelve hundred patients (8.0%) suffered MINS, and 58.2% of these patients would not have fulfilled the universal definition of myocardial infarction. Only 15.8% of patients with MINS experienced an ischemic symptom. CONCLUSION: Among adults undergoing noncardiac surgery, MINS is common and associated with substantial mortality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".