Predictors of outcome after coronary bypass surgery in patients with left ventricular dysfunction.
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine the risk factors affecting the mortality and morbidity after coronary artery bypass grafting (CABG) in patients with LV dysfunction and without any viability assessment. METHODS: The preoperative, perioperative, and postoperative early and mid-term follow-up data of 252 patients with left ventricular ejection fraction (LVEF) of < or = 30% who underwent isolated CABG from 1995 through 2000, were evaluated. No preoperative viability study was performed for patient selection. Preoperative echocardiography and cardiac catheterization, and postoperative control echocardiography were performed in all patients. Follow-up data after the discharge of these patients were obtained via monthly periodical examinations in the first 6 months, and thereafter via telephone interviews. As preoperatively, 229 (90.87%) patients were in NYHA class III or IV, and the mean LVEF was 26.58 +/- 3.66%. RESULTS: Overall mortality and late mortality rates were 16.27% and 5.16%, respectively. Postoperative complications were observed in 61 (24.21%) patients. During 49.06 +/- 15.17 months of follow-up, 185 (93.43%) of 198 (78.57%) survived patients were in NYHA class I or II and the mean LVEF was 39.64% +/- 5.68%. Advanced age, diabetes, hypertension, cross-clamp time > 60 min, bypass time > 120 min, severity of angina and functional classes (class III-IV of NYHA and CCS) were found to be the determinants of mortality. However, by multivariate analysis only older age and class III-IV of NYHA and CCS were detected as predictors of mortality. CONCLUSION: The low mortality and morbidity rates as well as postoperative improvements in functional capacity and in LVEF support the use of CABG without the need of any viability assessment in patients with left ventricular dysfunction. Advanced age, severe angina and functional symptom status seem to be the predictors of poor prognosis in these patients after CABG.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".