Do sleep variables predict mood in bipolar disorder: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Most people with bipolar disorder (BD) experience sleep disturbances across mood states and many identify sleep changes before both depressive and manic episodes. Nearly half of all patients have multiple relapses of BD and identifying early warning signs of relapse, such as sleep changes, could benefit both patients and clinicians as a preventive strategy. METHODS: A systematic search of the databases Embase, APA PsychINFO, and MEDLINE was performed to identify studies that investigated the relationship between sleep changes and mood in BD. The review was registered with PROSPERO (CRD42023405950) and followed the PRISMA guidelines. Results were categorised based on the identified relationship between sleep changes and mood, e.g. sleep and depression correlation, and these are synthesised narratively. The Newcastle-Ottawa scale was used to assess the risk of bias (RoB). RESULTS: The systematic literature search yielded 7159 records. 17 publications were included, describing 13 studies. Nine categories were identified describing the relationship between sleep and mood (e.g. sleep-mood correlations and comparing BD and HC on sleep duration). Regardless of sleep assessment (e.g. actigraphy), study duration or mood outcome, changes towards longer sleep, earlier onset and later wake-up were mostly followed by depressive mood, and vice versa for mania. 14 papers had a "fair" RoB rating. DISCUSSION: Changes in sleep patterns appear to precede predictable mood changes in BD and could be used as early warning signs for patients and clinicians. The main limitation of the study is the high heterogeneity between study results, preventing the conduction of a meta-analysis.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".