Menopausal hormone therapy and mild cognitive impairment: a randomized, placebo-controlled trial
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to explore the therapeutic potential of menopausal hormone therapy (MHT) in women with mild cognitive impairment (MCI). METHODS: Thirty-seven postmenopausal women (age range: 57-82 y) with multiple-domain, amnestic subtype MCI were randomly assigned to either placebo (n = 18) or MHT (n = 19) for 24 months (percutaneous estradiol [E2] gel [0.1%, 2 mg/d] and oral micronized progesterone [MP4] [100 mg/d]). All participants received donepezil, and apolipoprotein E genotype was determined. The primary endpoint was general cognitive function: Alzheimer's disease Assessment Scale, cognitive subscale, the Korean version of Mini-Mental State Examination (K-MMSE), and the Korean version of the Montreal Cognitive Assessment (MoCA_K) were performed in-person every 6 months. RESULTS: Twenty-one participants (placebo 13, MHT 8) completed the trial (56.8%). Progression rates to dementia were 52.9% (9/17) in the placebo group and 44.4% (8/18) in the MHT group. Within-group analysis showed that all three tests significantly worsened during the trial in the placebo, but not the MHT groups. Analysis adjusted for ε4 allele demonstrated that MHT significantly reduced deterioration of MoCA_K score, a sensitive tool for assessing global cognition in MCI (P = 0.0261). Compared with the control group, both MoCA_K (P = 0.043; mean difference, 3.85; 95% CI, -0.46 to 8.16) and K-MMSE (P = 0.0319; mean difference, 3.26; 95% CI, 0.04-6.48) scores were significantly better at 24 months in the MHT group. CONCLUSIONS: Long-term MHT using percutaneous E2 gel and oral MP4 might attenuate cognitive decline in postmenopausal women with MCI.
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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 | 0.001 | 0.001 |
| 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) | 0.007 | 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".