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. 2022 Apr 14;11(8):2204.
doi: 10.3390/jcm11082204.

Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders?

Lisa Ferrand  1   2 , Vincent Hennion  1   3   4 , Ophelia Godin  5 , Frank Bellivier  1   3   4 , Jan Scott  3   6 , Bruno Etain  1   3   4
Affiliations

Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders?

Lisa Ferrand et al. J Clin Med. .

Abstract

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 (p = 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 (p = 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.

Keywords: actigraphy; bipolar disorder; circadian rhythms; longitudinal; predictors; recurrence; sleep; survival analysis.

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Conflict of interest statement

B.E. has received honoraria for consulting from Sanofi. F.B. is an advisor on mental health to the French government. All other authors have no conflict of interest regarding this work.

Figures

Figure 1
Figure 1
Kaplan–Meier survival curve showing the cumulative rate of recurrence over time (data censored at 60 months).
Figure 2
Figure 2
AUC of early versus later recurrence when classified using key clinical and circadian variables alone and in combination. Clinical variables: age, type of BD, density of mood episodes, mood stabilizers monotherapy and body mass index; IV: intra-daily variability.
See this image and copyright information in PMC

References

    1. Tohen M., Zarate C.A., Jr., Hennen J., Khalsa H.M., Strakowski S.M., Gebre-Medhin P., Salvatore P., Baldessarini R.J. The McLean-Harvard First-Episode Mania Study: Prediction of recovery and first recurrence. Am. J. Psychiatry. 2003;160:2099–2107. doi: 10.1176/appi.ajp.160.12.2099. - DOI - PubMed
    1. Vazquez G.H., Holtzman J.N., Lolich M., Ketter T.A., Baldessarini R.J. Recurrence rates in bipolar disorder: Systematic comparison of long-term prospective, naturalistic studies versus randomized controlled trials. Eur. Neuropsychopharmacol. 2015;25:1501–1512. doi: 10.1016/j.euroneuro.2015.07.013. - DOI - PubMed
    1. Radua J., Grunze H., Amann B.L. Meta-Analysis of the Risk of Subsequent Mood Episodes in Bipolar Disorder. Psychother. Psychosom. 2017;86:90–98. doi: 10.1159/000449417. - DOI - PubMed
    1. Degenhardt E.K., Gatz J.L., Jacob J., Tohen M. Predictors of relapse or recurrence in bipolar I disorder. J. Affect. Disord. 2012;136:733–739. doi: 10.1016/j.jad.2011.09.051. - DOI - PubMed
    1. Etain B., Bellivier F., Olie E., Aouizerate B., Aubin V., Belzeaux R., Courtet P., Dubertret C., Schwan R., Roux P., et al. Clinical predictors of recurrences in bipolar disorders type 1 and 2: A FACE-BD longitudinal study. J. Psychiatr. Res. 2021;134:129–137. doi: 10.1016/j.jpsychires.2020.12.041. - DOI - PubMed

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