The association between biological rhythms, depression, and functioning in bipolar disorder: a large multi‐center study
Bibliographic record
Abstract
Objective We examined the relationship between biological rhythms and severity of depressive symptoms in subjects with bipolar disorder and the effects of biological rhythms alterations on functional impairment. Method Bipolar patients (n = 260) and healthy controls (n = 191) were recruited from mood disorders programs in three sites (Spain, Brazil, and Canada). Parameters of biological rhythms were measured using the Biological Rhythms Assessment in Neuropsychiatry (BRIAN), an interviewer administered questionnaire that assesses disruptions in sleep, eating patterns, social rhythms, and general activity. Results Multivariate analyses of covariance showed significant intergroup differences after controlling for potential confounders (Pillai's F = 49.367; df = 2, P < 0.001). Depressed patients had the greatest biological rhythms disturbance, followed by patients with subsyndromal symptoms, euthymic patients, and healthy controls. Biological rhythms and HAMD scores were independent predictors of poor functioning (F = 12.841, df = 6, P < 0.001, R2 = 0.443). Conclusion Our study shows a dose‐dependent association between the severity of depressive symptoms and degree of biological rhythms disturbance. Biological rhythms disturbance was also an independent predictor of functional impairment. Although the directionality of this relationship remains unknown, our results suggest that stability of biological rhythms should be an important target of acute and long‐term management of bipolar disorder and may aid in the improvement of functioning.
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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 | 0.001 |
| 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 | 0.000 |
| 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".