Randomized double‐blind placebo‐controlled multicenter trial of <scp>Y</scp>okukansan for neuropsychiatric symptoms in <scp>A</scp>lzheimer's disease
Bibliographic record
Abstract
AIM: Yokukansan (YKS), a traditional herbal medicine, has been used to treat behavioral and psychological symptoms of dementia (BPSD). The present study is the first double-blind, randomized, placebo-controlled trial to determine the efficacy and safety of YKS for the treatment of BPSD in Alzheimer's disease (AD). METHODS: A total of 22 sites consisting of clinics, hospitals and nursing homes participated. A total of 145 patients with AD were randomized. Active YKS (7.5 g/day) and placebo were supplied to 75 and 70 participants, respectively. The primary outcome measure was the 4-week change in total score of the Neuropsychiatric Inventory Brief Questionnaire Form (NPI-Q), an instrument that evaluates BPSD. Secondary outcome measures included 12-week changes in NPI-Q scores, changes in NPI-Q subcategory scores and total scores of the Mini-Mental-State Examination. RESULTS: Four-week changes in NPI-Q total scores did not differ significantly between the treatment and placebo groups. There were also no significant differences between groups in 12-week changes in total NPI-Q scores, NPI-Q subcategory scores or total Mini-Mental-State Examination scores. However, a subgroup with fewer than 20 points on the Mini-Mental-State Examination at baseline showed a greater decrease in "agitation/aggression" score in the YKS group than in the placebo group (P = 0.007). No serious adverse effects were observed during the study. CONCLUSIONS: Our data did not reach statistical significance regarding the efficacy of YKS against BPSD; however, YKS improves some symptoms including "agitation/aggression" and "hallucinations" with low frequencies of adverse events. Geriatr Gerontol Int 2017; 17: 211-218.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".