The validation of a care partner-derived frailty index based upon comprehensive geriatric assessment (CP-FI-CGA) in emergency medical services and geriatric ambulatory care
Bibliographic record
Abstract
BACKGROUND: The derivation of a frailty index (FI) based on deficit accumulation from a Comprehensive Geriatric Assessment (CGA) has been criticised as cumbersome. To improve feasibility, we developed a questionnaire based on a CGA that can be completed by care partners (CP-FI-CGA) and assessed its validity. METHODS: We enrolled a convenience sample of patients aged 70 or older (n=203) presenting to emergency medical services (EMS) or geriatric ambulatory care (GAC). To test construct validity, we evaluated the shape of the CP-FI-CGA distribution, including its maximum value, relationship with age and gender. Criterion validity was evaluated by survival analysis and by the correlation between the CP-FI-CGA and specialist-completed FI-CGA. RESULTS: The mean age was 82.2±5.9 years. Most patients were women (62.1%), unmarried (widowed, divorced and single) (59.6%) and lived in their own home or apartment (78.3%). The mean CP-FI-CGA was 0.41±0.15 and was higher in the EMS group (0.45±0.15) than in GAC (0.37±0.14) (P<0.001). The CP-FI-CGA correlated well with the specialist-completed FI-CGA (0.7; P<0.05). People who died had a higher CP-FI-CGA than did survivors (0.48±0.13 versus 0.38±0.15). Each 0.01 increase in the FI was associated with a higher risk of death (HR 1.04; 95% CI 1.02-1.06). CONCLUSION: The CP-FI-CGA has properties that resemble other published FIs and may be useful in busy clinical practice for grading degrees of frailty. It efficiently integrates information from care partners so that it can help guide decision-making.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".