Effect of Pushen capsule for treating vascular mild cognitive impairment: a pilot observational study
Bibliographic record
Abstract
Objective Traditional Chinese medicine (TCM) may be beneficial for vascular dementia (VaD). We evaluated the efficacy of Pushen capsule, a compound containing several TCM components, for treating vascular mild cognitive impairment (VaMCI). Methods Seventy outpatients with VaMCI were randomized to Pushen capsule or control treatment with Ginkgo biloba. Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Subjective Memory Loss Rating Scale scores; and lipid, lipoprotein, and haemorheological parameters were collected at baseline, week 4, and week 12 of treatment. Results MMSE score at week 12 was significantly higher in the treatment group compared with baseline ( t = −2.352) but was not significantly different from week 12 in the control group. The MoCA score at week 12 was higher than that at baseline for both the treatment and control groups ( t = −2.619 and −2.582, respectively), as was the “delayed recall” item score. Subjective memory loss score and the cognitive function “forgetting acquaintance's name” were significantly higher in the treatment group at week 12 than at baseline ( t = −2.621 and χ 2 = 4.419, respectively). Lipid, lipoprotein, and haemorheological parameters were significantly different after treatment in both groups. Conclusion The benefits of Pushen capsule on cognitive function in VaMCI were comparable with that of Ginkgo biloba.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".