Comparison of the long-term prognostic value of different frailty instruments in older inpatients: a 5-year prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Frailty is associated with increased mortality in older adults, but limited studies compare frailty instruments among inpatients with long-term follow-up. AIMS: To evaluate five frailty scales for predicting 5-year all-cause mortality in older inpatients. METHODS: This prospective cohort study enrolled 917 inpatients aged ≥ 65 years. We used five commonly used scales [Clinical Frailty Scale (CFS), FRAIL, Fried, Edmonton, and the comprehensive geriatric assessment-frailty index (CGA-FI)] to screen or assess frailty and then conducted a 5-year telephone follow-up. The primary endpoint was 5-year all-cause mortality. The predictive value of different frailty scales was compared using Kaplan-Meier (K-M) survival analysis, COX regression models, and the receiver operating characteristic (ROC) curves. RESULTS: The prevalence of frailty ranged from 19.5 to 36.5%. Both K-M survival curves and Cox regression confirmed that frailty patients had higher mortality risk across all scales. After multivariate adjustment, the hazard ratios from highest to lowest, were: CGA-FI, FRAIL, Fried, CFS, and Edmonton (all p < 0.05). Frailty demonstrated moderate performance, with area under the curves (AUCs) ranging from 0.70 to 0.75 (all p < 0.001). CGA-FI had the largest AUC of 0.724, revealing the best predictive value, while FRAIL had the smallest AUC of 0.666. The AUCs of Fried, Edmonton, and CFS gradually decreased, with no statistical differences. Furthermore, CFS has the highest sensitivity (77.5%). CONCLUSIONS: Frailty identified by all scales is associated with an increased risk of long-term mortality. CFS is the preferred frailty screening scale, while CGA-FI is the most accurate assessment scale. Trial registration ChiCTR1800017204 (07/18/2018).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".