The longitudinal course of cognition in older adults with bipolar disorder
Bibliographic record
Abstract
OBJECTIVES: Epidemiological studies suggest that elders with bipolar disorder (BD) may be at increased risk for dementia compared to the general population. We sought to investigate whether older adults with BD would present with more cognitive dysfunction than expected for their age and education, and whether they would experience a more rapid cognitive decline over three-year prospective follow-up. METHODS: Thirty-three subjects age > or = 50, mean (SD) age 69.7 (7.9) years, with BD I (n = 28) and II (n = 5) had neuropsychological examination at baseline and longitudinally over three years. All subjects were administered the Dementia Rating Scale (DRS) when euthymic. Thirty-six mentally healthy comparators ('controls'), equated on age and education, were selected from ongoing studies in our research center examining the longitudinal relationship between late-life mood disorders and cognitive function. RESULTS: Compared to mentally healthy comparators, subjects with BD performed significantly worse on the DRS at baseline [mean (SD) 135.2 (4.7); n = 33 versus 139.5 (3.3); n = 36], and over follow-up [131.9 (7.7); n = 14 versus 139.1 (3.4); n = 22]. There was a group-by-time interaction between the subjects with BD and the controls [group x time: F(1,64) = 5.07, p = 0.028]. CONCLUSIONS: In our study, older adults with BD had more cognitive dysfunction and more rapid cognitive decline than expected given their age and education. Cognitive dysfunction and accelerated cognitive decline may lead to decreased independence, with increased reliance on family and community supports, and potential placement in assisted-living facilities.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".