Validation of a Claims-Based Frailty Index Against Physical Performance and Adverse Health Outcomes in the Health and Retirement Study
Bibliographic record
Abstract
BACKGROUND: A claims-based frailty index (CFI) was developed based on a deficit-accumulation approach using self-reported health information. This study aimed to independently validate the CFI against physical performance and adverse health outcomes. METHODS: This retrospective cohort study included 3,642 community-dwelling older adults who had at least 1 health care encounter in the year prior to assessments of physical performance in the 2008 Health and Retirement Study wave. A CFI was estimated from Medicare claims data in the past year. Gait speed, grip strength, and the 2-year risk of death, institutionalization, disability, hospitalization, and prolonged (>30 days) skilled nursing facility (SNF) stay were evaluated for CFI categories (robust: <0.15, prefrail: 0.15-0.24, mildly frail: 0.25-0.34, moderate-to-severely frail: ≥0.35). RESULTS: The prevalence of robust, prefrail, mildly frail, and moderate-to-severely frail state was 52.7%, 38.0%, 7.1%, and 2.2%, respectively. Individuals with higher CFI had lower mean gait speed (moderate-to-severely frail vs robust: 0.39 vs 0.78 m/s) and weaker grip strength (19.8 vs 28.5 kg). Higher CFI was associated with death (moderate-to-severely frail vs robust: 46% vs 7%), institutionalization (21% vs 5%), activity of daily living disability (33% vs 9%), instrumental activity of daily living disability (100% vs 22%), hospitalization (79% vs 23%), and prolonged SNF stay (17% vs 2%). The odds ratios per 1-SD (=0.07) difference in CFI were 1.46-2.06 for these outcomes, which remained statistically significant after adjustment for age, sex, and a comorbidity index. CONCLUSION: The CFI is useful to identify individuals with poor physical function and at greater risks of adverse health outcomes in Medicare data.
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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 | 0.000 |
| 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 | 0.001 |
| 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".