Early longitudinal changes in brain structure and cognitive functioning in remitted patients with recently diagnosed bipolar disorder
Bibliographic record
Abstract
BACKGROUND: Patients with bipolar disorder (BD) who are presenting with cognitive impairment and associated structural brain abnormalities have generally a poorer clinical outcome. This study aims to map the early longitudinal trajectories in brain structure and cognition in patients with recently diagnosed BD. METHODS: Fully or partially remitted patients with a recent diagnosis of BD and matched healthy controls (HC) underwent structural MRI and neuropsychological testing at baseline (BD n = 97; HC n = 66) and again following an average of 16 (range 6-27) months (BD n = 50; HC n = 38). We investigated the differential trajectories in BD vs. HC in cortical gray matter volume and thickness, total cerebral white matter, hippocampal and amygdala volumes, estimated brain age, and cognitive functioning using linear mixed models. Within patients, we further investigated whether brain structural abnormalities detected at baseline were associated with subsequent mood episodes. RESULTS: Compared to HC, patients showed a decline in total white matter volume over time and they had a larger amygdala volume, both at baseline and at follow-up time. Patients further showed lower cognitive performance at both times of investigation with no significant change over time. There were no differences between patients and HC in cortical gray matter volume or thickness, hippocampal volume, or brain-aging patterns. CONCLUSIONS: Cognitive impairment and amygdala enlargement may represent stable markers of BD early in the course of illness, whereas subtle white matter decline may result from illness progression.
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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".