Prediction of clinical course in patients with diffuse coronary artery disease after coronary bypass surgery
Bibliographic record
Abstract
Aim. To determine the incidence, predictors and develop a model for long-term risk stratification of ischemic events in patients with coronary artery disease after coronary bypass surgery. Material and methods . This retrospective study of the clinical course in patients with diffuse coronary artery disease (CAD) after coronary endarterectomy and bypass grafting surgery. A total of 232 patients were included, while long-term outcomes were assessed in 202 patients. Among them, complete data on clinical status were obtained from survivors (n=191). The median follow-up was 60 (interquartile range, 42; 74) months, while the minimum follow-up — 12 months, the maximum was 96 months. The primary composite endpoint reflecting the unfavorable course of CAD included coronary ischemic events (recurrent angina, myocardial infarction, repeat revascularization), while secondary endpoint — allcause mortality. The factors influencing the development of primary and secondary endpoints were studied. Results. An unfavorable CAD course was diagnosed in 39 patients (20,4%), while 11 deaths were recorded (5,4%). Univariate analysis demonstrated a significant role of prior myocardial infarction in the increase in mortality rate (p=0,029). Among the factors influencing the CAD course, no significant differences were obtained for any of them. A multivariate analysis was performed to identify a high-risk group for an unfavorable course of diffuse CAD. Independent predictors were identified, the most significant contribution of which was made by multifocal atherosclerosis (odds ratio (OR)=1,99, 95% confidence interval (CI), 0,93-4,21, p=0,072), low adherence to secondary prevention measures (OR=2,21, 95% CI, 0,86-6,89, p=0,128) and diabetes (OR=1,73, 95% CI, 0,79-3,72, p=0,162). Using the results obtained, a prognostic model with high specificity (64%) and moderate sensitivity (53%) was created. Conclusion. The highest probability of an unfavorable long-term course of diffuse CAD was noted in patients with diabetes, multifocal atherosclerosis, and low adherence to secondary prevention measures. The obtained results make it possible to identify a high-risk group in this cohort of patients, determine the reserve of secondary prevention measures and a direction of actions to improve outcomes.
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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 | 0.001 |
| 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".