Relationship of Hair Cortisol with History of Psychosis, Neuropsychological Performance and Functioning in Remitted Later-Life Major Depression
Bibliographic record
Abstract
INTRODUCTION: Major depressive disorder (MDD) is associated with hypothalamic-pituitary-adrenal axis dysfunction that may persist into remission. Preliminary evidence suggests that this dysfunction may be associated with impaired neuropsychological performance in remitted MDD. MDD with psychotic features ("psychotic depression") is associated with greater neuropsychological and functional impairment than nonpsychotic depression, including in remission. Therefore, the aim of this exploratory study was to examine the relationships among hair cortisol concentration (HCC) - a marker of longer term endogenous cortisol exposure - and history of psychotic features, neuropsychological performance, and functioning in remitted MDD. METHODS: This cross-sectional study compared the relationship between HCC and (i) history of psychosis, (ii) neuropsychological performance, and (iii) everyday functioning in a group of 60 participants with remitted later-life MDD using Pearson's correlation coefficients. This study also measured HCC in a group of 36 nonpsychiatric volunteers to examine the clinical significance of HCC in the patient group. RESULTS: There were no statistically significant correlations between HCC and history of psychotic features, neuropsychological performance, or functioning. Furthermore, there was no clinically meaningful difference in HCC between patients and nonpsychiatric volunteers. CONCLUSION: This study is the first to examine HCC in psychotic depression. The results do not support the hypothesis that impaired neuropsychological performance, and everyday function in remitted psychotic depression is due to a sustained elevation of cortisol.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".