Clinical Utility and Safety of an Ultrasonic Head Stimulator in Dementia With Lewy Bodies
Bibliographic record
Abstract
BACKGROUND: The potential of Ultra-Ma, an ultrasonic head stimulator, for the supplementary treatment of dementia with Lewy bodies (DLB) was evaluated in patients with various symptoms under poor control by drug therapy. METHODS: Patients with DLB treated with choline esterase inhibitor or L-DOPA, either alone or in combination, and who met inclusion criteria were enrolled. Four weeks of placebo stimulation was followed by 8 weeks of active ultrasonic stimulation and a 4-week follow-up. Primary endpoints were the effects of ultrasonic head stimulation on both cognitive dysfunction and behavioral and psychological symptoms of dementia (BPSD). Cognitive dysfunction was evaluated using the Japanese versions of the Mini-Mental State Examination and Montreal Cognitive Assessment, and BPSD was assessed using the Neuropsychiatric Inventory Brief Questionnaire Form. For cognitive fluctuations, the Cognitive Fluctuation Inventory served as an index. Improvements in parkinsonism, activities of daily living, and caregiver burden were examined as secondary endpoints. RESULTS: Twelve patients were enrolled. The primary endpoint was significantly improved during the active stimulation period, as were secondary endpoint ratings for parkinsonism and caregiver burden. No notable adverse events occurred. CONCLUSIONS: The findings suggest that ultrasonic head stimulation has supplementary potential when combined with drug treatment in DLB.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".