Relationships between mood and estradiol (E2) levels in Alzheimer'sdisease (AD) patients
Bibliographic record
Abstract
This study investigates the relationship between mood and estradiol (E2) levels and assesses the prevalence of mood symptoms in Alzheimer's disease (AD) patients compared to healthy elderly controls. Fifty-two AD patients (26 men, 23 estrogen non-using women and three estrogen-using women), mean age 76.2 years, were recruited and assessed with the Geriatric Depression Scale (GDS), a test of mood, and a radioimmunoassay measure of E2 levels at the time of testing. The AD patients were compared to a control group of age and gender-matched healthy elderly men and women estrogen-users and non-users. No differences were found between the AD patients and the controls in overall E2 levels, but, as expected, the women estrogen-users in both the AD and control groups had higher E2 levels than the men and the female estrogen non-users. Both groups of men had higher E2 levels than the estrogen non-using women. There was a significant negative correlation between E2 levels and GDS scores in the full sample, which was particularly strong in the estrogen-using women. This indicates that those subjects with higher E2 levels had less mood symptomatology. Overall, mood scores in the AD patients were higher than in the healthy controls, indicating higher levels of depressive symptomatology; the highest depression scores occurred in the AD women who were estrogen non-users. This suggests that depressive symptoms are common in AD patients, and that women with AD who are not taking estrogen replacement may be especially vulnerable to depression.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".