[P2–474]: TOWARD DEVELOPING AND VALIDATING A NOVEL COGNITIVE FRAILTY INDEX
Bibliographic record
Abstract
Frailty is an important geriatric syndrome; so many efforts were done to measure and describe its properties, such as Frailty Index (FI), clinical frailty and phenotype frailty. However, the majority of them were developed based on physical components. A novel cognitive frailty index (CFI) was developed by modifying FI and adding several cognitive domains toward developing a more comprehensive assessment of frailty in elderly. Secondary analysis of the baseline cohort and five-year follow-up of the Canadian Study of Health and Aging (CSHA), a longitudinal observational cohort. Of 10263 participants who underwent a comprehensive intake assessment followed by 5-year; Clinical and neuropsychological assessment measures were available on 1105 people. CFI was defined as a combined score of 42 physical and mental components (in 8 cognitive domains) as they were available in the dataset. CFI was compared to FI that previously reported in this dataset. Cognitive score (measure by 3MS) at follow-up, dementia (Dementia defined with DSM-IV criteria), and survival were outcome. In multivariate logistic regression (Dementia as a binary outcome), linear regression (3MS as continuous variable) and Cox regression (5-year survival), CFI was independent and significant factor for three outcomes (P < 0.05). When both CFI and FI were included in the 3 multivariate analysis, only CFI was significant (P < 0.05); all models were adjusted for age and gender. CFI is strongly associated with cognitive changes over a five-year period. Participants with higher CFI score at baseline are at greater risk to develop dementia and higher probability of die within five years than their less impaired group. In contrast to previous approach (frailty index), CFI provide more robust and higher accuracy rate to predict outcomes.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".