The Effect of Guilingji Capsules on Vascular Mild Cognitive Impairment: A Randomized, Double-Blind, Controlled Trial
Bibliographic record
Abstract
Guilingji capsules (GLJC) have been shown to have antiaging effects and improve cognitive function. The aim of this study was to evaluate the clinical efficacy and safety of GLJC for the treatment of vascular mild cognitive impairment (VaMCI). A total of 96 patients with VaMCI (aged 60–85 years) were enrolled in this 24-week, randomized, double-blind, controlled clinical trial. The patients were randomly assigned to a GLJC group (n = 48) or a Ginkgo group (n = 48). Patients in the GLJC group were treated using GLJC, whereas those in the Ginkgo group received Ginkgo extract tablets. We evaluated the participants at baseline and after a 12- and 24-week treatment period using the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Chinese Medicine Symptom Scale (CM-SS). The serum acetylcholine (Ach), acetylcholinesterase (AchE), homocysteine (Hcy), and high-sensitivity C-reactive protein (hs-CRP) serum levels of the patients were measured before and after 24-week treatment. Analysis of the results of both groups showed that both interventions significantly increased the MoCA and MMSE scores of the patients and decreased their ADAS-Cog and CM-SS scores ( P < 0.05 ). The GLJC group showed greater improvement in MoCA, MMSE, and CM-SS scores than the Ginkgo group ( P < 0.05 ). However, both groups showed a significant increase in serum Ach and a decrease in serum AchE, Hcy, and hs-CRP levels ( P < 0.05 ). Furthermore, serum Ach increased and Hcy decreased more significantly in the GLJC group than in the Ginkgo group ( P < 0.05 ). These findings indicate that GLJC can improve the cognitive function, cholinergic system, and inflammatory cytokine levels of patients with VaMCI. Furthermore, this treatment can improve symptoms of syndromes diagnosed according to traditional Chinese medicine practice in patients with VaMCI.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.005 | 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".