Is urgent coronary artery bypass grafting a safe option in octogenarians? A developing country perspective
Bibliographic record
Abstract
Life expectancy has increased during recent decades leading to a growing number of older population. The objective of this study was to evaluate the outcomes of coronary artery bypass grafting (CABG) in octogenarians and to compare the outcomes of the emergent CABG with elective surgery. Prospectively collected data from 31 consecutive octogenarian patients who underwent CABG between 1 January 2006 and 31 December 2008 were analyzed. Main outcomes of interest included mortality, length of ICU stay, length of hospital stay, priority of surgery, postoperative complications and functional status on follow-up. Fifteen patients were operated on an urgent basis. Patients operated on an urgent basis were in NYHA class III or IV preoperatively (P=0.0016). There were no significant differences in operative and postoperative variables. There were three in-hospital deaths and 23 patients (82%) were alive on follow-up and 19 were in functional class I or II. Quality of life assessment was performed using Seattle Angina Questionnaire and patients reported remarkable improvement in quality of life. Overall, 90% patients were not or slightly disabled in their daily activity. Satisfaction with their current quality of life was reported by 95% of patients. CABG may be performed in octogenarians with remarkable outcomes and improvement in quality of life.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".