Psychosocial and medical predictors of 14-year mortality and morbidity in male and female coronary artery bypass graft recipients: a prospective observational study
Bibliographic record
Abstract
Abstract Background Psychosocial factors may influence mortality and morbidity after coronary bypass surgery (CABG), but it is unclear when, post-surgery, they best predict the outcome, if they interact, or whether results differ for men and women. Methods This prospective, observational study assessed depression symptoms, social support, marital status, household responsibility, functional impairment, mortality and need for further coronary procedures over 14 years of follow-up. Data were collected in-hospital post-CABG and at home 1-year later. Mortality and subsequent cardiac procedure data were extracted from a Cardiac Registry. Results Of 296 baseline participants, 78% (43% were women) completed data at 1-year post-CABG. Long-term survival was shorter with 1-year depression and lower household responsibility but that was not true for the measures taken at baseline [HR for depression = 1.27; 95% CI 1.02–1.59 v. 0.99 (0.78–1.25), and HR = 0.71; 95% CI 0.52–0.97 v. 0.97 (0.80–1.16)] for household responsibility. An interaction between depression symptoms and social support at year 1 [χ 2 (11) = 111.05, p < 0.001] revealed a greater hazard of mortality d with increased depression only at mean (HR = 1.67; 95% CI 1.21–2.26) and high social support (HR = 2.23; 95% CI 1.46–3.40). Depression also accounted for increased event recurrence. There were no significant interactions of sex with medical long-term outcomes. Conclusions In a sex-balanced sample, depression and household responsibility measured at 1-year post-CABG were associated with significant variance in unadjusted and adjusted predictor models of long-term mortality whereas the same indices determined right after the procedure were not significant predictors.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".