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Sleep in remitted bipolar disorder: a naturalistic case-control study using actigraphy
Pierre Alexis Geoffroy1, Carole Boudebesse2, Frank Bellivier3
1INSERM, U955, Psychiatrie génétique, Créteil 94000, France; AP-HP, Hôpital H. Mondor - A. Chenevier, Pôle de Psychiatrie, Créteil 94000, France; Pôle de psychiatrie, Université Lille Nord de France, CHRU de Lille, F-59000 Lille, France; Fondation FondaMental, Créteil 94000, France.
This study found that specific sleep patterns and variability in sleep measures can accurately distinguish individuals with bipolar disorder (BD) from healthy controls, even when accounting for other factors. These findings highlight the importance of objective and subjective sleep assessments in understanding BD.
Area of Science:
- Neuroscience
- Psychiatry
- Sleep Medicine
Background:
- Previous actigraphy studies suggest sleep and circadian rhythm disruptions in bipolar disorder (BD).
- Methodological limitations and unaddressed confounders have previously undermined these findings.
- This study aims to provide a more robust analysis by controlling for key variables.
Purpose of the Study:
- To compare subjective and objective sleep measures between euthymic bipolar disorder patients and healthy controls.
- To identify specific sleep parameters that can differentiate between these two groups.
- To assess the diagnostic utility of sleep measures in bipolar disorder.
Main Methods:
- Compared 26 euthymic BD cases and 29 healthy controls (HC) using the Pittsburgh Sleep Questionnaire Inventory (PSQI) and actigraphy over 21 days.
- Utilized multivariate generalized linear modeling (GLM) to analyze differences in sleep measures.
- Employed backward stepwise linear regression (BSLR) to identify key differentiating variables and classification accuracy.
Main Results:
- Significant differences were found between BD cases and HC in five PSQI items, four actigraphy mean scores, and five actigraphy variability measures.
- A combination of four variables (mean sleep duration, mean sleep latency, variability of fragmentation index, and PSQI daytime dysfunction score) correctly classified 89% of participants.
- These results indicate distinct sleep profiles in euthymic BD patients.
Conclusions:
- Adequately controlling for confounders like age, gender, daytime sleepiness, mood symptoms, BMI, and sleep apnea risk is crucial.
- Quantitative (mean scores) and qualitative (variability) sleep features can effectively differentiate euthymic BD cases from HC.
- These findings support the utility of detailed sleep assessments in the context of bipolar disorder.
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