Olanzapine does not enhance cognition in non-agitated and non-psychotic patients with mild to moderate Alzheimer's dementia
Bibliographic record
Abstract
OBJECTIVE: This was an exploratory study of olanzapine as potential treatment for improvement in cognition in patients with Alzheimer's disease without prominent psychobehavioral symptoms. METHODS: Non-psychotic/non-agitated patients (n = 268) with Alzheimer's disease, who had baseline Mini-Mental State Examination (MMSE) scores of 14-26 were randomized to treatment with olanzapine (2.5 to 7.5 mg/d) or placebo for 26 weeks. The primary objectives were to determine if treatment with olanzapine improved cognition as indexed by the Alzheimer's disease Assessment Scale for Cognition (ADAS-Cog) and the Clinician's Interview-Based Impression of Change (CIBIC) after 26 weeks of therapy. RESULTS: Patients treated with olanzapine vs placebo experienced significant worsening ADAS-Cog scores at weeks 12 (p = 0.03) and 26 (p = 0.004). Changes in CIBIC scores were not significantly different between treatment groups at either assessment. A post hoc analysis revealed that olanzapine-treated patients with more cognitive impairment at baseline (MMSE scores of 14-18) (n = 35) experienced significantly greater deterioration in ADAS-Cog performance than patients in the placebo group (n = 24; p < 0.001); whereas in patients with less cognitive impairment (n = 78, baseline MMSE scores of 23-26) between-group ADAS-Cog changes were not significant. CONCLUSIONS: In this 26-week study non-psychotic/non-agitated patients with Alzheimer's disease treated with olanzapine experienced significant worsening of cognition as compared to placebo.
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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) | 0.000 | 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 | 0.000 | 0.001 |
| 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".