Pharmaco-EEG test dose response predicts cholinesterase inhibitortreatment outcome in Alzheimer's disease
Bibliographic record
Abstract
Previous investigations have indicated that a single dose pharmaco-EEG may predict the outcome of 4-7 weeks of tetrahydroaminoacridine (THA) treatment in dementia of the Alzheimer type (DAT). This open trial study further examined the relationship of quantitative EEG in relation to treatment response by assessing 24 probable DAT patients at baseline, 2 h after their first oral dose (30 mg), and after 12 weeks of THA treatment. Compared to EEG norms, patients, in general, evidenced EEG slowing, as shown by excessive slow (theta) and diminished fast (alpha and beta) wave power as well as reduced mean frequencies which were present prior to treatment as well as at the end of treatment. The EEG of patients exhibiting stable or improved scores on the Mini-Mental State examination (MMSE) at 12 weeks showed a significantly faster baseline mean alpha frequency as well as a significant reduction in relative theta power following the single THA test dose compared to deteriorated patients. A discriminant analysis using test dose response EEG variables correctly classified 75-79% of these two patient groups, suggesting that this procedure may be a useful approach for optimizing patient selection for antidementia treatments.
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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 | 0.000 | 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".