Sleep-wake profiles and circadian rhythms of core temperature and melatonin in young people with affective disorders
Bibliographic record
Abstract
While disturbances of the sleep-wake cycle are common in people with affective disorders, the characteristics of these disturbances differ greatly between individuals. This heterogeneity is likely to reflect multiple underlying pathophysiologies, with different perturbations in circadian systems contributing to the variation in sleep-wake cycle disturbances. Such disturbances may be particularly relevant in adolescents and young adults with affective disorders as circadian rhythms undergo considerable change during this key developmental period. This study aimed to identify profiles of sleep-wake disturbance in young people with affective disorders and investigate associations with biological circadian rhythms. Fifty young people with affective disorders and 19 control participants (aged 16-31 years) underwent actigraphy monitoring for approximately two weeks to derive sleep-wake cycle parameters, and completed an in-laboratory assessment including evening dim-light saliva collection for melatonin assay and overnight continuous core body temperature measurement. Cluster analysis based on sleep-wake cycle parameters identified three distinct patient groups, characterised by 'delayed sleep-wake', 'disrupted sleep', and 'long sleep' respectively. The 'delayed sleep-wake' group had both delayed melatonin onset and core temperature nadir; whereas the other two cluster groups did not differ from controls on these circadian markers. The three groups did not differ on clinical characteristics. These results provide evidence that only some types of sleep-wake disturbance in young people with affective disorders are associated with fundamental circadian perturbations. Consequently, interventions targeting endogenous circadian rhythms to promote a phase shift may be particularly relevant in youth with affective disorders presenting with delayed sleep-wake cycles.
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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 | 0.001 | 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".