Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders?
Bipolar disorder (BD) is characterized by recurrent mood episodes. It is increasingly suggested that disturbances in sleep–wake cycles and/or circadian rhythms could represent valuable predictors of recurrence, but few studies have addressed this question. Euthymic individuals with BD (n = 69) under...
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| Format: | Article |
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MDPI AG
2022-04-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/11/8/2204 |
| _version_ | 1797434499046309888 |
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| author | Lisa Ferrand Vincent Hennion Ophelia Godin Frank Bellivier Jan Scott Bruno Etain |
| author_facet | Lisa Ferrand Vincent Hennion Ophelia Godin Frank Bellivier Jan Scott Bruno Etain |
| author_sort | Lisa Ferrand |
| collection | DOAJ |
| description | Bipolar disorder (BD) is characterized by recurrent mood episodes. It is increasingly suggested that disturbances in sleep–wake cycles and/or circadian rhythms could represent valuable predictors of recurrence, but few studies have addressed this question. Euthymic individuals with BD (n = 69) undertook 3 weeks of actigraphy recording and were then followed up for a median duration of 3.5 years. Principal component analyses were used to identify core dimensions of sleep quantity/variability and circadian rhythmicity. Associations between clinical variables and actigraphy dimensions and time to first recurrence were explored using survival analyses, and then using area under the curve (AUC) analyses (early vs. late recurrence). Most participants (64%) experienced a recurrence during follow-up (median survival time: 18 months). After adjusting for potential confounding factors, an actigraphy dimension comprising amplitude and variability/stability of circadian rhythms was a significant predictor of time to recurrence (<i>p</i> = 0.009). The AUC for correct classification of early vs. late recurrence subgroups was only 0.64 for clinical predictors, but combining these variables with objectively measured intra-day variability improved the AUC to 0.82 (<i>p</i> = 0.04). Actigraphy estimates of circadian rhythms, particularly variability/stability and amplitude, may represent valid predictive markers of future BD recurrences and could be putative targets for future psychosocial interventions. |
| first_indexed | 2024-03-09T10:33:05Z |
| format | Article |
| id | doaj.art-756857e213564275aac511f1d3cbb65c |
| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-09T10:33:05Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Clinical Medicine |
| spelling | doaj.art-756857e213564275aac511f1d3cbb65c2023-12-01T21:07:06ZengMDPI AGJournal of Clinical Medicine2077-03832022-04-01118220410.3390/jcm11082204Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders?Lisa Ferrand0Vincent Hennion1Ophelia Godin2Frank Bellivier3Jan Scott4Bruno Etain5Optimisation Thérapeutique en Neuropsychopharmacologie, INSERM U1144, Université de Paris, 75006 Paris, FranceOptimisation Thérapeutique en Neuropsychopharmacologie, INSERM U1144, Université de Paris, 75006 Paris, FranceINSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, 94000 Créteil, FranceOptimisation Thérapeutique en Neuropsychopharmacologie, INSERM U1144, Université de Paris, 75006 Paris, FranceUniversité de Paris, 75006 Paris, FranceOptimisation Thérapeutique en Neuropsychopharmacologie, INSERM U1144, Université de Paris, 75006 Paris, FranceBipolar disorder (BD) is characterized by recurrent mood episodes. It is increasingly suggested that disturbances in sleep–wake cycles and/or circadian rhythms could represent valuable predictors of recurrence, but few studies have addressed this question. Euthymic individuals with BD (n = 69) undertook 3 weeks of actigraphy recording and were then followed up for a median duration of 3.5 years. Principal component analyses were used to identify core dimensions of sleep quantity/variability and circadian rhythmicity. Associations between clinical variables and actigraphy dimensions and time to first recurrence were explored using survival analyses, and then using area under the curve (AUC) analyses (early vs. late recurrence). Most participants (64%) experienced a recurrence during follow-up (median survival time: 18 months). After adjusting for potential confounding factors, an actigraphy dimension comprising amplitude and variability/stability of circadian rhythms was a significant predictor of time to recurrence (<i>p</i> = 0.009). The AUC for correct classification of early vs. late recurrence subgroups was only 0.64 for clinical predictors, but combining these variables with objectively measured intra-day variability improved the AUC to 0.82 (<i>p</i> = 0.04). Actigraphy estimates of circadian rhythms, particularly variability/stability and amplitude, may represent valid predictive markers of future BD recurrences and could be putative targets for future psychosocial interventions.https://www.mdpi.com/2077-0383/11/8/2204bipolar disorderrecurrenceactigraphypredictorscircadian rhythmssleep |
| spellingShingle | Lisa Ferrand Vincent Hennion Ophelia Godin Frank Bellivier Jan Scott Bruno Etain Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders? Journal of Clinical Medicine bipolar disorder recurrence actigraphy predictors circadian rhythms sleep |
| title | Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders? |
| title_full | Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders? |
| title_fullStr | Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders? |
| title_full_unstemmed | Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders? |
| title_short | Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders? |
| title_sort | which actigraphy dimensions predict longitudinal outcomes in bipolar disorders |
| topic | bipolar disorder recurrence actigraphy predictors circadian rhythms sleep |
| url | https://www.mdpi.com/2077-0383/11/8/2204 |
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