Are Dexamethasone Suppression Test Nonsuppression and Thyroid Dysfunction Related to a Family History of Dementia in Patients with Major Depression? An Exploratory Study
Bibliographic record
Abstract
OBJECTIVE: Recent data suggest that the low thyroid function syndrome in depression is nonspecific. They also suggest that depression may constitute a risk factor for the development of dementia, especially in atypical patients who have high rates of hypothalamo-pituitary-adrenal axis disorders. This study aimed to search for correlations among Dexamethasone Suppression Test (DST) cortisol levels, thyroid indices, and family history of dementia in patients with depression. METHODS: A sample of 30 patients, aged 21 to 60 years and suffering from major depression according to DSM-IV criteria, took part in the study. Three had a family history of dementia in first-degree relatives. We measured their serum levels of free T3, free T4, thyroid-stimulating hormone, thyroid binding inhibitory immunoglobulines, thyroglobulin antibodies, and thyroid microsomal antibodies (TMAs). We applied the 1-mg DST to all patients. The statistical analysis included 1-way multivariate analysis of covariance using t tests as the post hoc tests. RESULTS: Significantly higher levels of TMAs were found in patients with a family history of dementia, compared with those who did not have this family history. CONCLUSION: The results of this study suggest that a more pronounced autoimmune process may characterize depression patients with a family history of dementia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".