Cognitive impairment with and without depression history: an analysis of white matter microstructure
Bibliographic record
Abstract
BACKGROUND: Mild cognitive impairment (MCI) and late-life depression are clinical syndromes that often co-occur and may represent an early manifestation of neurodegenerative disease. The present study examined white matter microstructure in patients with MCI with and without a history of major depression compared with healthy controls. METHODS: Older adults with MCI and no history of major depression (MCI), adults with MCI and euthymic major depression (MCI-MD) and healthy controls underwent comprehensive medical, psychiatric and neuropsychological assessments. Participants also underwent diffusion tensor imaging, which was analyzed using tract-based spatial statistics. White matter hyperintensity (WMH) burden and medical burden were also quantified. RESULTS: We enrolled 30 participants in the MCI group, 36 in the MCI-MD group and 22 in the control group. Compared with controls, participants in the MCI group had significantly reduced fractional anisotropy (FA) in the corpus callosum, superior longitudinal fasciculus (SLF), corona radiata and posterior thalamic radiation. Participants in the MCI-MD group had significantly reduced FA in the corpus callosum, internal capsule, external capsule, corona radiata, posterior thalamic radiation, sagittal striatum, fornix, SLF, uncinate fasciculus and right cingulum compared with controls. No significant differences in FA were observed between the MCI and MCI-MD groups. Participants in the MCI-MD group had greater medical burden (p = 0.020) and WMH burden than controls (p = 0.013). LIMITATIONS: Study limitations include the cross-sectional design and antidepressant medication use. CONCLUSION: To our knowledge, this study is the first to compare white matter microstructure in patients with MCI with and without a history of major depression and suggests that a common underlying structural white matter change may underpin cognitive impairment in both MCI groups. Further research is needed to delineate the pathophysiological mechanisms underlying these microstructural changes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".