Frailty in older adults with amnestic mild cognitive impairment as a result of Alzheimer's disease: A comparison of two models of frailty characterization
Bibliographic record
Abstract
AIM: To verify the prevalence and presence of frailty markers, and their relationship to cognitive function among older adults with amnestic mild cognitive impairment (aMCI). METHODS: This was an observational study with transversal analyses. Older adults with aMCI as a result of Alzheimer's disease (n = 40) were compared with healthy controls (n = 26) at the Psychogeriatric Outpatient Unit, Institute and Department of Psychiatry, Faculty of Medicine of the University of São Paulo. All participants were submitted to a broad clinical and neuropsychological evaluation. Frailty was evaluated according to the Cardiovascular Health Study (CHS) phenotype and the Edmonton Frail Scale (EFS). MCI was diagnosed by a multidisciplinary consensus according to the Petersen criteria and cerebrospinal fluid analysis for Alzheimer's disease biomarkers. RESULTS: The prevalence of frailty was significantly higher in the aMCI compared with the control group when it was assessed with the EFS (P = 0.047), but not with the CHS (P = 0.255). The prevalence of frailty varied on the criteria used (EFS 7.5%; CHS 30%). The fatigue variable in the CHS (P = 0.036), and the mood (P = 0.019) and functional independence (P = 0.042) variables from the EFS were significantly different between the groups. Visuospatial function (OR 2.405, P = 0.042) was associated with the CHS criteria. CONCLUSION: The identification of frailty features in aMCI appears to depend on the protocol used for evaluation. Visuospatial function showed a higher risk for frailty with the CHS. Geriatr Gerontol Int 2017; 17: 2096-2102.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".