Hekun decoction versus Femoston for women with amnestic mild cognitive impairment in early menopause: a randomized, three-arm, double-blind clinical trial
Bibliographic record
Abstract
Background: Amnestic mild cognitive impairment (aMCI), a prodromal stage of Alzheimer's disease (AD), carries a high risk of progression to dementia. However, few clinical trials have focused on interventions to delay this progression. Hekun Decoction, an herbal-based oral medicine, has shown potential in improving memory loss during early menopause. Here we performed a randomized controlled trial to evaluate the efficacy and safety of Hekun Decoction in women with aMCI. Methods: This prospective, randomized, three-arm, double-blind clinical trial enrolled women aged 40-60 years with aMCI during early menopause. Participants were randomized to Hekun Decoction, Femoston, or placebo for 24 weeks. The primary outcome was the change in the Montreal Cognitive Assessment (MoCA) score at 0 and 24 weeks. The secondary outcomes included the Menopause Rating Scale (MRS), Modified Kupperman Index (KI), and Insomnia Severity Index (ISI), along with adverse events. Results: = 96). After 24 weeks, both Hekun Decoction (MD = 3.18, 95% CI [2.44-3.92]) and Femoston (MD = 3.67, 95% CI [2.93-4.42]) were more effective than placebo in improving MoCA scores. Meanwhile, better outcomes were observed in the Hekun Decoction group and Femoston group compared with the placebo group for MRS (MD = -5.87, 95% CI [-7.02, -4.71], and MD = -6.01, 95% CI [-7.02, -5.01]), KI (MD = -6.74, 95% CI [-8.16, -5.33], and MD = -6.93, 95% CI [-8.27, -5.59]), and ISI (MD = -6.53, 95% CI [-7.66, -5.39], and MD = -6.51, 95% CI [-7.58, -5.43]). As for the adverse events, no cases of abdominal distension, pain, breast pain, or abnormal uterine bleeding were observed in the Hekun Decoction group. Conclusion: In women with aMCI during early menopause, Hekun Decoction demonstrated non-inferior efficacy to Femoston in improving cognitive function over 24 weeks, with a favorable safety profile. Notably, women in the Hekun Decoction group showed fewer adverse events compared with Femoston. However, further trials with longer follow-up periods are needed to confirm the efficacy of Hekun Decoction in women with aMCI. Clinical trial registration: http://chictr.org.cn, ChiCTR2000036772.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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) | 0.006 | 0.001 |
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".