A Longitudinal Study of the Relationship Among Cognition, Mood Symptoms, and Markers of Brain Health in Older Age Bipolar Disorder: Une étude longitudinale de la relation entre la cognition, les symptômes thymiques, et les marqueurs de la santé du cerveau en présence de troubles bipolaires du sujet âgé
Bibliographic record
Abstract
OBJECTIVES: An emerging literature has assessed cognition or imaging markers of brain health in in older age bipolar disorder (OABD). In this context, we conducted the first longitudinal study (to our knowledge) that assessed the relationship among cognition, mood symptoms, and imaging markers of brain health in OABD. METHODS: = 58) completed magnetic resonance imaging (MRI) at one or two time-points, yielding three measures of brain health: gray matter volume, fractional anisotropy (FA), and burden of white matter hyperintensities (WMH). RESULTS: Group-based trajectory modelling (GBTM) of overall cognitive performance revealed two groups: a group with higher cognitive performance (63 of 99, 63.6%) and a group with lower cognitive performance (36 of 99, 36.4%). GBTM also revealed two groups based on each of the three imaging markers of brain health. The higher cognitive performance group was associated with the groups with higher measure of total gray matter or higher FA. We found no relationship between the cognitive groups and level of mood symptoms during longitudinal follow-up or WMH burden. CONCLUSIONS: In this first longitudinal study of cognition, mood symptoms, and markers of brain health in OABD, cognitive performance was related to brain health and not to mood symptoms over a follow-up of up to three years. Almost two-thirds of participants with OABD had cognitive performance comparable to older adults without OABD. Larger future studies will need to replicate and extend these findings.Plain Language Summary TitleA Longitudinal Study of Cognition, Mood, and Brain Health in Older Adults with Bipolar Disorder.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".