Association of Frailty and Long‐Term Survival in Patients Undergoing Coronary Artery Bypass Grafting
Bibliographic record
Abstract
BACKGROUND: Frailty is increasing in prevalence and poses a formidable challenge for clinicians. The cardiac surgery literature consists primarily of small single-center studies with limited follow-up, and the epidemiological features of frailty remain to be elucidated in long-term follow-up. METHODS AND RESULTS: We conducted a population-based, retrospective, cohort study in Ontario, Canada, between 2008 and 2015. Frailty was defined using the Johns Hopkins Adjusted Clinical Groups frailty indicator (a multidimensional instrument validated for research using administrative data). The primary outcome was mortality. Mortality rates were calculated using the Kaplan-Meier method. The hazard of death was assessed using a multivariable Cox proportional hazard model. Of 40 083 patients, 8803 (22%) were frail. At 4±2 years of follow-up, age- and sex-standardized mortality rate per 1000 person-years was higher in frail (33; 95% confidence interval, 29-36) compared with nonfrail (22; 95% confidence interval, 19-24) patients. Frailty was associated with an increased risk of long-term mortality (adjusted hazard ratio, 1.20; 95% confidence interval, 1.12-1.28) and greater differences in the survival of patients between 40 and 74 years of age than in those who were ≥85 years old. CONCLUSIONS: Frailty was present in a large proportion of patients undergoing coronary artery bypass grafting and was independently associated with long-term mortality. The adjusted risk of frailty-related death was inversely proportional to age. Our findings highlight the need for more comprehensive preoperative risk stratification models to assist with optimal selection of operative candidates. In addition, we identified the <75 years age group as a potential target for comprehensive preoperative optimization programs, such as cardiac prehabilitation, nutritional augmentation, and psychosocial support.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".