Comparing three different measures of frailty in medical inpatients: Multicenter prospective cohort study examining 30‐day risk of readmission or death
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Bibliographic record
Abstract
BACKGROUND: Multiple tools are used to identify frailty. OBJECTIVE: To compare the global Clinical Frailty Scale (CFS) with more objective phenotypic tools (modified Fried score and the Timed Up and Go Test [TUGT]). DESIGN: Prospective cohort study. SETTING: General medical wards in Edmonton, Canada. PARTICIPANTS: Adults being discharged back to the community. MEASUREMENTS: All frailty assessments were done within 24 hours of discharge. Patients were classified as frail if they scored ≥5 on the CFS and/or ≥3 on the modified Fried score, and/or had reduced mobility (>20 seconds on the TUGT). The main outcome was readmission or death within 30 days. RESULTS: Of 495 patients, 211 (43%) were frail according to at least 1 assessment, 46 (9%) met all 3 frailty definitions, and 17% died or were readmitted to the hospital within 30 days. Although patients classified as frail on the CFS exhibited significantly higher 30-day readmission/death rates (23% vs 14% for not frail, P = 0.005; 28% vs. 12% in the elderly, P < 0.001), even after adjusting for age and sex (adjusted odds ratio [aOR]: 2.02, 95% confidence interval [CI]: 1.19-3.41 for all adults; aOR: 3.20, 95% CI: 1.55-6.60 for the elderly), patients meeting either of the phenotypic definitions for frailty but not the CFS definition were not at higher risk of 30-day readmission/death (aOR: 0.87, 95% CI: 0.34-2.19 for all adults and aOR: 1.41, 95% CI: 0.72-2.78 for the elderly). CONCLUSIONS: Frailty has a significant impact on postdischarge outcomes, and the CFS is the most useful of the frequently used frailty tools for predicting poor outcomes after discharge. Journal of Hospital Medicine 2016;11:556-562. © 2016 Society of Hospital Medicine.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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 it