Predictors of outcome after coronary artery bypass grafting in patients older than 75 years of age.
Bibliographic record
Abstract
BACKGROUND: This study was designed to identify risk factors affecting mortality and morbidity in patients older than 75 years who underwent coronary artery bypass grafting (CABG) with cardiopulmonary bypass. MATERIAL/METHODS: The preoperative, perioperative, and postoperative data of 116 patients older than 75 years who underwent isolated CABG from January 1997 through April 2002 were evaluated retrospectively. Preoperatively, 82 patients (70.7%) were in CCS class III-IV and 65 (56%) were in NYHA class III-IV. Besides mortality, morbidity and survival rates, the statistical significance of predictors of outcome were investigated. RESULTS: Overall mortality and hospital mortality rates were 12.9% (15 patients) and 4.3%, (5 patients), respectively. Postoperative complications were observed in 56 patients (48.3%). In 25.1+/-17.6 months of follow-up, 96 (86.5%) and 101 (91%) of the surviving 111 patients (95.7%) were in NYHA class I and CCS class I, respectively. Prolonged cross-clamp time (>50 min) (p=0.018), COPD (p=0.028), and emergency operation (p=0.001) were found to be the determinants of postoperative complications. The cumulative 5-year survival rate was 77.2 +/-0.8%. CONCLUSIONS: Elective CABG in older patients with shorter bypass and cross-clamp times, after the management of comorbid disease, such as COPD, is a safe procedure with low mortality and morbidity rates, showing postoperative improvements in functional capacity and angina class.
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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 | 0.001 |
| 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 | 0.000 |
| 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".