Efficacy and safety of Yi Shen Fang granules in elderly people with MCI: study protocol for a multicentre, randomized, double-blind, parallel-group, controlled trial
Bibliographic record
Abstract
BACKGROUND: Mild cognitive impairment (MCI) is a transitional state between normal ageing and dementia. Most MCI patients will progress to dementia within 5 years; therefore, early intervention for MCI is important for delaying the occurrence and progression of dementia. Yi Shen Fang (YSF) granules are a promising traditional Chinese medicine (TCM) treatment that shows great neuroprotective potential against cognitive impairment, as evidenced in clinical and basic studies. This trial aims to systematically evaluate the efficacy and safety of YSF granules in elderly people with MCI. METHODS: This study is a multicentre, randomized, double-blind, parallel-group, controlled trial. Based on the results of previous clinical trials, 280 elderly patients with MCI will be randomly divided into a treatment group (n = 140) and control group (n = 140). The study will last 33 weeks, including 1 week of screening, 8 weeks of intervention, and 24 weeks of follow-up. The primary outcomes will be the changes in Montreal Cognitive Assessment (MoCA) and Memory and Executive Screening (MES) scores before and after the intervention. The secondary outcome measures will be homocysteine (HCY) levels, Functional Assessment Questionnaire (FAQ) scores and event-related potential (ERP) detection in typical cases. The TCM symptom scale is a combined measure of syndrome differentiation and treatment. During this study, the classifications and characteristics of adverse events, the times of occurrence and disappearance, the measures of treatment, their impact on the primary disease, and outcomes will be reported truthfully. DISCUSSION: This study will provide valuable clinical evidence that YSF can help to improve the cognitive function of elderly people with MCI, and the results will be disseminated via conferences and publications. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2000036807. Registered on August 25, 2020.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".