Management of Patients with Myocardial Injury After Noncardiac Surgery: A Retrospective Chart Review
Bibliographic record
Abstract
Background: Myocardial injury after noncardiac surgery (MINS) is associated with an increased incidence of cardiac morbidity and mortality. Little is known about how these patients are managed. Methods: We performed a single-centre retrospective chart review of patients referred to a postoperative clinic with the diagnosis of MINS. Patients were included if they attended the clinic at least once between September 2018 and December 2019. We extracted preoperative, in-hospital, and postdischarge data on cardiac investigations and medication use. Results: Of the 152 patients with MINS who were included, 34% had a history of coronary disease before MINS. The median peak high-sensitivity troponin I (hsTnI) level was 122 ng/L (interquartile range, 51-259), and 78% had no associated ischemic symptoms or electrocardiographic changes. Patients underwent echocardiography and nuclear stress imaging in 87% and 30% of cases, respectively. Of those who had cardiac investigations performed and no prior history of coronary artery disease, 23% (19 of 84) had ≥ 1 regional wall-motion abnormality on echocardiogram, and 39% (13 of 34) had evidence of ischemia on nuclear stress imaging. More patients were prescribed an antithrombotic and lipid-lowering drug at discharge (79%) and at their final clinic visit (86%), compared to the number before surgery (30%). A total of 57% of patients had changes made to ≥ 1 cardiovascular medication during clinic follow-up. Conclusions: Patients with MINS followed in a postoperative clinic frequently had abnormal cardiac investigations and received medical optimization. Our findings suggest that postoperative clinics may represent an opportunity for risk mitigation after MINS, a possibility that deserves further evaluation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".