Development of a Frailty Index for Patients with Coronary Artery Disease
Bibliographic record
Abstract
OBJECTIVES: To construct a brief frailty index for older patients with coronary artery disease (CAD) undergoing coronary angiography that includes physical, cognitive, and psychosocial criteria and accurately predicts future disability and decline in health-related quality of life (HRQL). DESIGN: Prospective cohort. SETTING: An urban tertiary care hospital in Alberta, Canada. PARTICIPANTS: Three hundred seventy-four patients aged 60 and older (73% male) undergoing cardiac catheterization for CAD between October 2003 and May 2007. MEASUREMENTS: Potential frailty criteria examined at baseline (before the procedure) included measures of balance, gait speed, cognition, self-reported health, body mass index (BMI), depressive symptoms, and living alone. The outcomes assessed over 1 year were dependency in activities of daily living (ADLs) and HRQL. RESULTS: The five best-fitting criteria from regression analyses for ADL decline were poor balance (risk ratio (RR)=2.4, 95% confidence interval (CI)=1.4–4.0), abnormal BMI (RR=1.8, 95% CI=1.1–3.0), impaired Trail-Making Test Part B performance (RR=2.3, 95% CI=1.3–4.2), depressive symptoms (RR=1.8, 95% CI=1.1–3.1), and living alone (RR=2.2, 95% CI=1.3–3.8). Using the five criteria as separate variables or as a summary frailty index yielded identical areas under the receiver operating characteristic curve (0.76, 95% CI=0.66–0.84). Patients with three or more criteria (vs none) were at statistically significant greater risk for increased disability (RR=10.4, 95% CI=4.4–24.2) and decreased HRQL (RR=4.2, 95% CI=2.3–7.4) after 1 year. CONCLUSION: This brief frailty index including physical, cognitive, and psychosocial criteria was predictive of increased disability and decreased HRQL at 1 year in older patients with CAD undergoing angiography. This index may have applications for clinicians and researchers but requires further validation.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".