Prevention, epidemiology, and prognosis of perioperative myocardial injury
Bibliographic record
Abstract
Annually over 200 million adults undergo noncardiac surgery worldwide.Myocardial ischaemia is a frequent cause of perioperative cardiac morbidity and mortality.Approximately 8 million patients will suffer a myocardial injury after noncardiac surgery (MINS) each year.MINS is defined as a prognostically important myocardial injury due to ischaemia that occurs during, or within 30 days after, noncardiac surgery.The diagnostic criterion for MINS is an elevated troponin measurement resulting from myocardial ischaemia.MINS is a strong, independent predictor of 30-day and 1-year mortality.The majority of patients suffering MINS would go undetected without troponin monitoring since >80% of these patients do not experience ischaemic symptoms.Intensification of pharmacotherapy may reduce 30-day mortality in patients who have experienced MINS.This pape r will review the epidemiology, prevention, prognosis and treatment of MINS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".