Do Lesions Involving the Cortical Cholinergic Pathways Help or Hinder Efficacy of Donepezil in Patients with Alzheimer’s Disease?
Bibliographic record
Abstract
AIMS: To investigate the influences of vascular lesions detected by MRI, lesions involving the cortical cholinergic pathways and hippocampal thickness on therapeutic responsiveness to donepezil in patients with Alzheimer's disease (AD). METHODS: The study cohort contained 67 patients with probable AD. We used the revised Hasegawa Dementia Rating (HDS-R) and the Clock Drawing Test (CDT) to evaluate drug efficacy for 24 months. The Cholinergic Pathways Hyperintensities Scale (CHIPS), a newly developed visual scale, was used to semiquantify lesions on the cholinergic pathways. RESULTS: Over the 24-month period, the results of the CDT showed more apparent and constant association with white matter hyperintensities (WMH) and lesions on the cholinergic pathways than the HDS-R. WMH may enhance, while lesions on the cholinergic pathways may attenuate sensitivity to donepezil treatment when judged by the CDT. No apparent association between the thicknesses of hippocampi with baseline cognition or therapeutic responsiveness to donepezil was found. CONCLUSION: Donepezil may be more efficacious when further executive dysfunction caused by WMH is added to AD dementia and less so when cholinergic reserves are further impinged upon by lesions involving the cortical cholinergic pathways.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".