Methylphenidate for the Treatment of Apathy in Alzheimer Disease
Bibliographic record
Abstract
Apathy is a common behavioral symptom of Alzheimer's disease (AD), being present in up to 70% of patients. Apathy in AD and non-AD populations has been associated with dysfunction in the dopaminergic brain reward system, suggesting that pharmacotherapeutic targeting of this system may be an effective treatment for apathy in AD. We therefore performed a randomized, double-blind, placebo-controlled crossover trial of methylphenidate in a sample of 13 apathetic AD patients (6 men, 7 women; age mean 77.9 years [SD, 7.8 years]; Mini Mental Status Examination score, 19.9 [SD, 4.7]). Patients were treated with methylphenidate (10 mg PO twice a day) or an identical placebo in two 2-week phases separated by a 1-week placebo washout. All patients participated in a dextroamphetamine challenge test (one 10-mg oral dose) before treatment with methylphenidate to gauge the functional integrity of the dopamine brain reward system. Overall, patients demonstrated greater improvement with methylphenidate compared with placebo according to Apathy Evaluation Scale total change scores (end of treatment - baseline: Wilcoxon Z = -2.00; P = 0.047). However, a significantly greater proportion of patients experienced at least 1 adverse event with methylphenidate compared with placebo (3 vs 1; chi = 4.33, P = 0.038). Two patients experienced serious adverse events with methylphenidate, consisting of delusions, agitation, anger, irritability, and insomnia, which resolved upon discontinuation of the medication. Response to methylphenidate was associated with increases in inattention on a continuous performance task after dextroamphetamine challenge. Psychostimulants may be effective in treating features of apathy in AD, and dopaminergic changes may predict response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".