Cognitive Predictors of Donepezil Therapy Response in Alzheimer Disease
Bibliographic record
Abstract
OBJECTIVES: To examine whether the presence of domain-specific cognitive impairments would predict a response to donepezil medication in patients with mild-to-moderate Alzheimer disease (AD). METHODS: The protocol was an open-label study of 30 AD subjects (mean age 74 years; education 11 years; Mini-Mental State Exam (MMSE) 23 of 30) beginning a 6-month course of treatment with donepezil. Global response to treatment was determined using a combination algorithm based on changes over 6 months in the ADAS-cog, MMSE and CIBIC. In addition, a set of neuropsychological and experimental cognitive tests designed to test five domains of cognition were administered before beginning therapy in order to determine which domain of testing would be predictive to response to treatment. The tests examined attention, short-term and working memory, learning and memory, visuo-spatial motor skills, and lexical-semantic knowledge. RESULTS: Eighteen of the thirty subjects were rated as having responded (stable or improved scores on the combination algorithm) to the therapy. Responders were significantly less impaired prior to treatment on the following tests: the Clock Drawing Test, a Visual-Spatial Motor Tracking Test, and the Boston Picture Naming Test. No significant initial group differences were noted on the other neuropsychological or experimental cognitive measures. CONCLUSION: The tests that most reliably predicted response to donepezil in AD subjects were in the domains of visual-spatial motor abilities and lexical-semantic functioning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".