Evaluation of circadian rhythms in depression by using actigraphy: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective·To systematically review the effectiveness of actigraphy on the evaluation of circadian rhythm characteristics in patients with depression.Methods·A systematic literature search was conducted in PubMed, Embase, Web of Science, Cochrane Library, PsycINFO, CNKI, WanFang Data, and Chinese biomedical literature database (CBM), from the inception of each database to May 5th, 2023. Case control studies that used actigraphy to evaluate circadian rhythms in patients with depression and compared them with healthy controls were collected. Literature was screened according to the inclusion and exclusion criteria, and the quality of the included literature was evaluated by using the Newcastle-Ottawa Scale. The meta-analysis was performed by using RevMan 5.4 software.Results·A total of 9 articles were included, including 390 patients with depression and 288 healthy controls. The meta-analysis showed that the MESOR (midline statistic of rhythm) (SMD=-0.29, 95% CI -0.51 ‒ -0.07, P=0.009) of the circadian cosine function in patients with depression was lower than that in healthy controls; sleep onset (MD=33.06, 95% CI 14.90 ‒ 51.23, P=0.000) and sleep offset (MD=53.80, 95% CI 22.38 ‒ 85.23, P=0.000) were later in patients with depression than those in healthy controls; no statistical difference was found in the activity level of the most active 10 hours (SMD=-0.26, 95% CI -0.52 ‒ 0.01, P=0.060) between patients with depression and healthy controls, although there was a trend for lower activity in patients with depression; no statistical difference was found in the acrophase (MD=25.33, 95% CI -12.41 ‒ 63.06, P=0.190) of the circadian cosine function between patients with depression and healthy controls; no clear statistical significance of the difference was found in the amplitude (SMD=-0.14, 95% CI -0.42 ‒ 0.14, P=0.340) and the activity level of the least active 5 hours (SMD=0.31, 95% CI -0.10 ‒ 0.71, P=0.140) between patients with depression and healthy controls.Conclusion·Actigraphy can reflect circadian rhythm disruption in patients with depression to some extent, but the limited number of included studies and inconsistencies in the study populations and methodologies have affected the quality and results of the analyses. More high-quality clinical trials are needed to provide evidence.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.026 |
| Bibliometrics | 0.007 | 0.007 |
| 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) | 0.003 | 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".