Treatment effects of Ginkgo biloba extract EGb 761® on the spectrum of behavioral and psychological symptoms of dementia: meta-analysis of randomized controlled trials
Bibliographic record
Abstract
ABSTRACTBackground:In randomized controlled trials, Ginkgo biloba extract EGb 761® has been found to be effective in the treatment of behavioral and psychological symptoms of dementia (BPSD). METHODS: To assess the effects of EGb 761® on specific BPSD, we analyzed data from all randomized, placebo-controlled, at least 20-week, trials of EGb 761® enrolling patients with dementia (probable Alzheimer's disease (AD), probable vascular dementia or probable AD with cerebrovascular disease) who had clinically significant BPSD (Neuropsychiatric Inventory (NPI) total score at least 6). Data were pooled and joint analyses of NPI single item composite and caregiver distress scores were performed by meta-analysis with a fixed effects model. RESULTS: Four trials involving 1628 patients (EGb 761®, 814; placebo, 814) were identified; treatment duration was 22 or 24 weeks; the daily dose of EGb 761® was 240 mg in all trials. Pooled analyses including data from the full analysis sets of all trials (EGb 761®, 796 patients; placebo, 802 patients) revealed significant superiority of EGb 761® over placebo in total scores and 10 single symptom scores. Regarding caregiver distress scores, EGb 761®-treated patients improved significantly more than those receiving placebo in all symptoms except delusions, hallucinations, and elation/euphoria. The benefit of EGb 761® mainly consists of improvement in symptoms present at baseline, but the incidence of some symptoms was also decreased. CONCLUSIONS: Twenty two- to twenty four-week treatment with Ginkgo biloba extract EGb 761® improved BPSD (except psychotic-like features) and caregiver distress caused by such symptoms.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".