Persistent depressive symptoms are associated with frontal regional atrophy in patients with Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Depression in individuals with Alzheimer's disease (AD) is common, difficult to treat and inadequately understood. Previous studies have identified possible differences in regional brain atrophy in individuals with AD and depression, but the results have been inconsistent and some studies had less robust definitions of depression. We aimed to examine regional brain atrophy in two large dementia focused cohorts. METHODS: We used data from Alzheimer's disease neuroimaging initiative (ADNI) and the National Alzheimer's Co-ordinating Center (NACC), for those with data from at least one MRI scan. Depression ratings were available using the Geriatric Depression Scale (GDS) and Neuropsychiatric Inventory (NPI). Intermittent depressive symptoms were defined as one episode above threshold (≥8 on GDS, ≥6 on NPI depression subscale and ≥2 on the Neuropsychiatric Inventory version Q depression sub-scale) and persistent as ≥2 episodes. Derived regional volumetric data was available from ADNI and the NACC. RESULTS: Data was available from 698 individuals with AD in NACC and from 666 individuals in ADNI. We found no evidence of between group differences in regional brain volume at baseline, or of differential atrophy in NACC. In ADNI we found evidence of increased brain atrophy in several frontal brain areas. LIMITATIONS: Because this study was limited to those with MRI data, the numbers in some analyses were low. MRI parcellation differed between studies making direct comparison difficult. For some individuals only the NPI was used to rate depression. CONCLUSIONS: We have found mixed evidence of increased regional atrophy in depression in AD, mainly in frontal brain regions. We found no evidence to support a vascular basis for depression in AD.
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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 | 0.001 | 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".