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
AimTo verify the prevalence and presence of frailty markers, and their relationship to cognitive function among older adults with amnestic mild cognitive impairment (aMCI). MethodsThis 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 SAo 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. ResultsThe 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. ConclusionThe 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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 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".