Correlates of response to acetylcholinesterase inhibitor therapy in Alzheimer’s disease
Bibliographic record
Abstract
Cholinesterase inhibitors improve cognition and behaviour in some patients with Alzheimer's disease (AD). Studies that have focused on methods to predict response to anticholinesterase therapy and markers for response are reviewed. Among the possible predictors of improvement in cognitive outcomes are apolipoprotein genotype, pretreatment postural blood pressure drop, quantitative electroencephalography (qEEG) and disease progression rate. Of these, qEEG profile after a single dose of an acetylcholinesterase inhibitor was consistently found to be a good predictor of cognitive response. Studies have assessed baseline behavioural profiles and baseline single-photon emission computed tomographic profiles as possible predictors of improvement of behavioural symptoms of AD, but these require further study. Possible markers of response during drug treatment include red blood cell cholinesterase inhibition, cerebrospinal fluid monoamine measurement, pupillary response and platelet amyloid precursor protein analyses. Although they, too, require further study, the analysis of platelet amyloid precursor protein may have value as a correlate of the putative disease-modifying effects of long-term treatment. Studying correlates of response may help to elucidate the mechanism of action of acetylcholinesterase inhibitors.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".