Coronary Artery Bypass Graft Surgery and Cognitive Performance
Bibliographic record
Abstract
BACKGROUND: Some studies have indicated a decline in patients' cognitive performance after coronary artery bypass graft surgery. OBJECTIVE: To evaluate cognitive performance before and after coronary artery bypass graft surgery. METHODS: Patients' cognitive performance before and after coronary artery bypass graft surgery was evaluated in a prospective observational multicenter study in 5 academic medical centers. A total of 242 men and 123 women were evaluated before surgery; 333 men and 216 women, 5 to 11 months after surgery (197 men and 99 women were evaluated both before and after surgery). Verbal ability, attention/concentration, logical/verbal and visual memory, and facial recognition were measured. Data on demographic, medical, and psychosocial characteristics also were collected. RESULTS: After surgery, patients' overall performance improved (P < .001) for attention/concentration, verbal fluency, and logical/verbal memory. Patients with more education (high school or greater) performed better on each test (P < .001) than did patients with less education. No strong effects of sex or age on cognitive performance were observed before or after surgery, and no important differences in sex, age, or education were associated with changes in scores from before to after surgery. CONCLUSION: On average, cognitive performance improved rather than declined after coronary artery bypass graft surgery. The improvements were consistent across sex, age, and education.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".