High sensitivity troponin-I threshold to predict perioperative myocardial infarction
Bibliographic record
Abstract
BACKGROUND: High-sensitivity Troponin I (hs-cTnI) has largely replaced conventional troponin assays in an effort to improve detection of myocardial infarction. However, the mean displacement of hs-cTnI following coronary artery bypass graft (CABG) and the optimal threshold to detect perioperative myocardial infarction (MI) is unclear. Our objective is to describe mean hs-cTnI values at 6-12 h post-CABG and to determine the highest specificity while maintaining 100% sensitivity hs-cTnI cut-off values for diagnosis of perioperative or type-5 MI. METHODS: Between 2016 and 2018, 374 patients underwent non-emergent, isolated CABG. Pre-operative and 6 h post-operative hs-cTnI values were recorded as well as ECG, echocardiographic and angiographic data. RESULTS: Of 374 patients, 151 (40.3%) had normal and 224 (59.7%) had elevated preoperative hs-cTnI. Patients with normal preoperative hs-cTnI had a mean 6 h hs-cTnI of 9193 ng/l or 270X the upper normal value. Eleven patients (7.3%) presented with post-operative MI with a mean 6 h hs-cTnI of 50,218 ng/l or 1477X the upper normal value. Patients with elevated preoperative hs-cTnI had a mean 6 h hs-cTnI of 9449 ng/l or 292X the upper normal value. Eleven patients (4.9%) who presented with post-operative MI had a mean 6 h hs-cTnI of 26,823 ng/l or 789X the upper normal value. CONCLUSIONS: We suggest hs-cTnI threshold of 80-fold in patients with normal pre-operative hs-cTnI and 2.7-fold in patients with elevated pre-operative hs-cTnI. These results have important implications for perioperative care and for surgical trial reporting.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.000 |
| 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".