Association between Sleep Disturbances and Medial Temporal Lobe Volume in Older Adults with Mild Cognitive Impairment Free of Lifetime History of Depression
Bibliographic record
Abstract
BACKGROUND: Previous studies examining the link between neuropsychiatric symptoms (NPS) and biomarkers of Alzheimer's disease (AD) may be confounded by remitted or past history of psychiatric illness, which in itself is associated with AD biomarkers such as reduced medial temporal lobe (MTL) volume. OBJECTIVE: We examined associations between mood and anxiety-related NPS and MTL in older adults with mild cognitive impairment (MCI) free of lifetime history of depression. We hypothesized an inverse relationship between NPS severity and MTL. METHODS: Forty-two MCI participants without current or past history of depression or other major psychiatric illness were assessed using the Neuropsychiatric Inventory-Questionnaire (NPI-Q). Correlation and regression analyses were performed between selected NPI-Q items and regional MTL volumes from structural magnetic resonance imaging. RESULTS: Sleep disturbances were inversely associated with several regional volumes within the MTL. Sleep disturbances remained significantly correlated with left hippocampal and amygdala volume following correction for multiple comparisons. In contrast, depression and anxiety were not correlated with MTL. CONCLUSIONS: The relationship between reduced MTL and sleep, but not with depressed or anxious states, in MCI free of lifetime history of depression, suggests a potential mechanism for sleep as a risk factor for AD. The current findings highlight the importance of accounting for remitted psychiatric conditions in studies of the link between NPS and AD biomarkers and support the need for further research on sleep as clinical biomarker of AD and target for AD prevention.
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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 | 0.000 | 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".