Myocardial infarct size for predicting improvements in cardiac function in patients with ischemic cardiomyopathy following coronary artery bypass grafting
Bibliographic record
Abstract
Background: This study used late gadolinium enhancement-cardiac magnetic resonance (LGE-CMR) to assess myocardial infarct size, with the data being employed to predict whether patients with ischemic cardiomyopathy (ICM) would experience improvements in left ventricular function at 6 months following coronary artery bypass grafting (CABG). Methods: The data of patients with ICM with left ventricular ejection fraction (LVEF) ≤40% who underwent CABG were retrospectively analyzed. All patients underwent preoperative LGE-CMR imaging. Echocardiography results from 6 months post-CABG were used to assess improvements in LVEF, with improvement being defined as ΔLVEF ≥5%. The value of myocardial infarction segments and infarct size as predictors of improved cardiac function following CABG was analyzed. Results: Of the included patients, 66.7% (52/78) exhibited improved cardiac function at 6 months post-CABG. LGE-CMR imaging data revealed that compared to improved group, the improved group had significantly more myocardial infarct segments [improved group: median 1.0, interquartile range (IQR) 0–3; nonimproved group: median 4.0, IQR 3.0–6.0; P<0.001] and significantly greater myocardial infarct size (improved group: 22.4%±8.2%; nonimproved group: 34.7%±5.9%; P<0.001). The area under the receive operating characteristic curve values for myocardial infarct size in predicting cardiac function improvement were significantly higher than those of myocardial infarct segments (0.88 vs. 0.81; P=0.041). The respective sensitivity and specificity values for using a myocardial infarct size cutoff of 26.4% in differentiating between these 2 patient groups were 92.3% and 71.2%, respectively. According to logistic regression analysis, myocardial infarct size was an independent predictor of nonimprovement in cardiac function [odds ratio (OR) =1.244; 95% confidence interval (CI): 1.114–1.389; P<0.001]. A median 1.6-year follow-up interval (range, 0.5–4.1 years) revealed that the incidences of major adverse cerebrovascular events and cardiovascular events were significantly higher in the nonimproved group (5.8% vs. 26.9%; P<0.001), with these individuals having a higher New York Heart Association grading than patients with improved cardiac function (P=0.019). Conclusions: Myocardial infarct size can be measured to reliably predict improvements in cardiac function in patients with ICM following CABG. These results can guide clinicians in their efforts to identify those patients most likely to achieve positive outcomes following CABG.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".