Development and validation of a multidimensional tool for baseline functional phenotyping in cardiac rehabilitation
Bibliographic record
Abstract
BACKGROUND: Functional recovery after cardiac events is heterogeneous, with up to 40% of patients showing limited improvement despite standardized rehabilitation. Current assessment tools demonstrate modest accuracy (~ 61%) and rarely capture the multidimensional aspects of functional status. This study aimed to develop and internally validate a pragmatic bedside functional stratification tool for patients entering cardiac rehabilitation. METHODS: We conducted a cross-sectional study of 80 patients (mean age 72.7 ± 5.2 years, 65% male) at rehabilitation intake. Four routinely available parameters were assessed: age, six-minute walk test (6MWT), Timed Up and Go (TUG), and the Edmonton Frail Scale (EFS). Each was categorized into four levels (0–3 points), yielding a composite score of 0–12. Patients were stratified as Low (0–3), Moderate (4–6), High (7–9), or Very High (10–12) functional impairment. Internal validation employed bootstrap resampling (n = 1000). RESULTS: Functional capacity declined progressively across categories: 6MWT decreased from 364.3 ± 75.7 m (Low Impairment) to 185.2 ± 32.9 m (Very High Impairment), and TUG increased from 6.9 ± 1.0 s to 14.2 ± 2.8 s (all p < 0.001). The composite score correlated strongly with functional performance (r = − 0.75, p < 0.001) and demonstrated excellent discrimination (AUC 0.93, 95% CI 0.87–0.97), outperforming individual measures. Bootstrap validation confirmed stability. CONCLUSIONS: We propose a simple, multidomain bedside score requiring ~ 25 min and no specialized equipment. This tool enables functional stratification at rehabilitation intake, supports personalized care, and facilitates matching rehabilitation pathways to baseline functional status. External validation is warranted.
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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 | 0.002 | 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".