Effects of donepezil on activities of daily living: integrated analysis of patient data from studies in mild, moderate and severe Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: We aimed to develop a standardization method to pool data recorded on different activities of daily living (ADL) scales in order to reduce variability of functional outcome data from Alzheimer's disease (AD) clinical trials and to better evaluate the effect of donepezil treatment on function in patients with AD. METHODS: Based on pre-specified criteria, six studies were selected from among all donepezil clinical trials in AD. Individual items from nine ADL scales used in these trials were mapped to a standardized functional scale comprising 12 domains (six basic, six instrumental); scores were transformed to a 0-100 scale. External validation of this scale yielded a concordance rate of 90.8%. For each domain, mean change from baseline to 24 weeks in the placebo and donepezil groups was compared for the total population and for subgroups stratified by baseline disease severity. Study settings included outpatient, assisted living, and skilled nursing facilities. Participants comprised 2183 patients (donepezil, 1261; placebo; 922) with baseline Mini-mental State Examination (MMSE) scores 5-26. RESULTS: Significant treatment differences favoring donepezil were observed for five items (two instrumental and three basic). Patients with moderate AD at baseline (MMSE 10-17) demonstrated the greatest treatment effect. CONCLUSION: Functional data were successfully pooled using standardizing methodology. A beneficial effect of donepezil treatment on function was demonstrated using this standardized functional scale. Similar analyses from studies with other anti-dementia drugs may help to determine the generalizability of these findings and potentially encourage use of functional assessment as a clinical tool.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".