Myocardial injury after noncardiac surgery
Bibliographic record
Abstract
PURPOSE OF REVIEW: Recent investigations have substantially improved our understanding of myocardial injury after noncardiac surgery (MINS). RECENT FINDINGS: MINS is defined as a prognostically relevant myocardial injury due to ischemia that occurs during or within 30 days after noncardiac surgery. MINS occurs in 8% of adults undergoing major noncardiac surgery and is diagnosed with an elevated postoperative troponin measurement. MINS is associated with significant morbidity, and approximately 10% of patients experiencing MINS will die within 30 days. There is a dose-graded response in mortality and time to death with increasing levels of postoperative troponin elevations. Most patients (>80%) suffering from MINS will not experience an ischemic symptom. Without troponin monitoring, the majority of MINS events would go undetected. To avoid missing these prognostically relevant events, guidelines now recommend perioperative troponin monitoring in high-risk patients having noncardiac surgery. In patients who suffer MINS, risk-adjusted observational data suggest that aspirin and a statin can reduce the risk of 30-day mortality. SUMMARY: Among adults, MINS is the most common cardiovascular complication that occurs after noncardiac surgery. Given that worldwide 200 million adult patients undergo major noncardiac surgery each year, at least 8 million of these patients will suffer MINS making this a substantial public health problem.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".