Development and validation of a frailty index based on data routinely collected across multiple domains in NSW hospitals
Bibliographic record
Abstract
OBJECTIVE(S): To develop and validate a frailty index (FI) that covers multiple domains, using routine hospital data. To investigate the FI's validity, after excluding medication-related items (FI-ExMeds), for studies of frailty and polypharmacy. METHODS: A FI was derived from routine NSW hospital data following standard published guidance. In a development cohort (151 inpatients ≥ 70 years), the FI was correlated with the Reported Edmonton Frail Scale (REFS) using Pearson's R. Validity and distribution of FI and FI-ExMeds, and correlation with each other, were evaluated in a validation cohort (999 inpatients ≥ 75 years). RESULTS: The mean FI for the development cohort was 0.27 (SD 0.09). The FI showed moderate linear correlation with the REFS (n = 148, R = 0.52, P < .001). In the validation cohort, mean FI (n = 993) and FI-ExMeds (n = 990) were both 0.28 (SD 0.11). FI-ExMeds showed high linear correlation with the FI (n = 990, R = 0.99, P < .001). CONCLUSION: This multi-domain FI is comparable to REFS, with adequate redundancy to exclude deficits for specific analyses.
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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 | 0.021 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".