Neuroimaging and neurocognitive abnormalities associated with bipolar disorder in old age
Bibliographic record
Abstract
OBJECTIVES: Cognitive dysfunction is prevalent in older adults with bipolar disorder (BD). High white matter hyperintensity (WMH) burden, a marker of white matter disease, detected on T2/fluid-attenuated inversion recovery brain magnetic resonance imaging (MRI) has been consistently reported in BD across all age ranges, including older adults. Yet, whether high WMH burden is related to the excess cognitive impairment present in older adults with BD is unknown. Therefore, we examine whether higher WMH burden is related to worse cognitive function in older adults with BD. METHODS: This is a cross-sectional study of 27 non-demented BD patients aged ≥50 years and 12 similarly aged mentally healthy comparators (controls). Subjects underwent both brain MRI and comprehensive neurocognitive assessment. We employed correlational analyses to evaluate the burden of WMH and the relationship between WMH and cognitive function. RESULTS: Although BD subjects had worse performance in all cognitive domains, BD subjects had less total WMH burden (t[13.4] = -3.57, p = 0.003). In control subjects, higher WMH was related to lower global cognitive function (ρ = -0.57, n = 12, p = 0.05). However, WMH did not correlate with neuropsychological performance in BD subjects. Further, BD and control subjects did not differ with respect to total gray and hippocampal volumes. CONCLUSIONS: Cognitive dysfunction in late-life BD does not appear to be due primarily to processes related to increased WMH or reduced gray matter volume. Future longitudinal studies should examine other potential neuroprogressive pathways such as inflammation, mitochondrial dysfunction, serum anticholinergic burden, and altered neurogenesis.
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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 | 0.000 |
| 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".