Myocardial injury after non-cardiac surgery: diagnosis and management
Bibliographic record
Abstract
Myocardial injury after non-cardiac surgery (MINS) is due to myocardial ischaemia (i.e. supply-demand mismatch or thrombus) and is associated with an increased risk of mortality and major vascular complications at 30 days and up to 2 years after non-cardiac surgery. The diagnostic criteria for MINS includes an elevated post-operative troponin measurement judged as resulting from myocardial ischaemia (i.e. no evidence of a non-ischaemic aetiology), during or within 30 days after non-cardiac surgery, and without the requirement of an ischaemic feature (e.g. ischaemic symptom, ischaemic electrocardiography finding). For patients with MINS who are not at high risk of bleeding, physicians should consider initiating dabigatran 110 mg twice daily and low-dose aspirin. Physicians should also consider initiating statin therapy in patients with MINS. Most MINS patients should only be referred to cardiac catheterization if they demonstrate recurrent instability (e.g. cardiac ischaemia, heart failure). Patients ≥65 years of age or with known atherosclerotic disease should have troponin measurements on days 1, 2, and 3 after surgery while the patient is in hospital to avoid missing >90% of MINS and the opportunity to initiate secondary prophylactic measures and follow-up.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".