Symptom Severity Mixity in Older-Age Bipolar Disorder: Analyses From the Global Aging and Geriatric Experiments in Bipolar Disorder Database (GAGE-BD)
Bibliographic record
Abstract
OBJECTIVE: Some individuals with bipolar disorder (BD) experience manic and depressive symptoms concurrently, but data are limited on symptom mixity in older age bipolar disorder (OABD). Using the Global Aging & Geriatric Experiments in Bipolar Disorder Database, we characterized mixity in OABD and associations with everyday function. METHODS: The sample (n = 805), from 12 international studies, included cases with both mania and depression severity ratings at a single timepoint. Four mixity groups were created: asymptomatic (A), mixed (Mix), depressed only (Dep), and manic only (Man). Generalized linear mixed models used mixity group as the predictor variable; cohort was included as a random intercept. Everyday function was assessed with the Global Assessment of Functioning score. RESULTS: Group proportions were Mix (69.6%; n = 560), followed by Dep (18.4%; n = 148), then A (7.8%; n = 63), then Man (4.2%; n= 34); levels of depression and mania were similar in Mix compared to Dep and Man, respectively. Everyday function was lowest in Mix, highest in A, and intermediate in Man and Dep. Within Mix, severity of depression was the main driver of worse functioning. Groups differed in years of education, with A higher than all others, but did not differ by age, gender, employment status, BD subtype, or age of onset. CONCLUSIONS: Mixed features predominate in a cross-sectional, global OABD sample and are associated with worse everyday function. Among those with mixed symptoms, functional status relates strongly to current depression severity. Future studies should include cognitive and other biological variables as well as longitudinal designs to allow for evaluation of causal effects.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".