Postmenopausal Hormone Therapy and Its Association With Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is a common and potentially debilitating medical problem in older women. Postmenopausal hormone therapy (HT) has been associated with better cognitive function, but the literature is conflicting. Results of recent trials suggest that HT is inappropriate for prevention of heart disease, and we sought to determine the role of HT in the risk of cognitive impairment. METHODS: We measured HT use and cognitive function in a population-based cohort of 1462 postmenopausal women participating in the 5-year follow-up examination for the Epidemiology of Hearing Loss Study in 1998-2000. The cohort was defined in 1987-1988 by residency in Beaver Dam, Wis, and an age of 43 to 84 years. Women had also participated in the Beaver Dam Eye Study baseline examination in 1988-1990. Use of HT was assessed at the Beaver Dam Eye Study baseline (1988-1990), 5-year follow-up (1993-1995), and 10-year follow-up (1998-2000) visits. Cognitive impairment was defined as a low Mini-Mental State Examination score or a reported diagnosis of Alzheimer disease. RESULTS: Six percent of participants (n = 94) were impaired; these women were significantly older and less educated than those who were unimpaired. In age- and education-adjusted analysis, current HT use was not significantly associated with cognitive impairment (odds ratio, 0.6; 95% confidence interval, 0.2-1.3). Similarly, cognitive impairment was not associated with past HT use or duration of HT use. CONCLUSION: In this large population-based study, postmenopausal hormone therapy was not significantly associated with better cognitive function.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".