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Prospective early warning signals to detect transitions to manic and depressive episodes in bipolar disorder

Published online by Cambridge University Press:  13 August 2021

F. Bos ,
M. Schreuder ,
B. Doornbos ,
E. Snippe ,
R. Bruggeman ,
L. Van Der Krieke ,
B. Haarman ,
M. Wichers  and
S. George
F. Bos*
Affiliation:
Department Of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
M. Schreuder
Affiliation:
Psychiatry, University Medical Center Groningen, Groningen, Netherlands
B. Doornbos
Affiliation:
Bipolar Disorders, GGZ Drenthe, Assen, Netherlands
E. Snippe
Affiliation:
Department Of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
R. Bruggeman
Affiliation:
Department Of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
L. Van Der Krieke
Affiliation:
Psychiatry, University Medical Center Groningen, Groningen, Netherlands
B. Haarman
Affiliation:
Psychiatry, University Medical Center Groningen, Groningen, Netherlands
M. Wichers
Affiliation:
Department Of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
S. George
Affiliation:
Department Of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
*
*Corresponding author.

Abstract

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Introduction

For patients with bipolar disorder, early recognition of impending mood episodes is crucial to enable timely intervention. Longitudinal digital mood monitoring using ecological momentary assessment (EMA) enable prospective study of early warning signals (EWS) in momentary affective estates prior to symptom transitions.

Objectives

The present study examined in a unique longitudinal EMA data set whether EWS prospectively signal transitions to manic or depressive episodes.

Methods

Twenty bipolar type I/II patients completed EMA questionnaires five times a day for four months (average 491 observations per person), as well as weekly symptom questionnaires concerning depressive (Quick Inventory for Depressive Symptomatology) and manic (Altman Self-Rating Mania Scale) symptoms. Weekly data was used to determine transitions (i.e., abrupt increase in symptoms). Prior to these transitions, EWS (autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective EMA states. Kendall’s tau was calculated to detect significant rises in the EWS indicator prior to the transition.

Results

Eleven patients reported one or two transitions to a mood episode. All transitions were preceded by at least one EWS. Average sensitivity for detecting EWS was slightly higher for manic episodes (36%) than for depressive episodes (25%). For manic episodes, EWS in thoughts racing, being full of ideas, and feeling agitated showed the highest sensitivity and specificity, whereas for depression, only feeling tired showed high sensitivity and specify.

Conclusions

EWS show promise in anticipating transitions to mood episodes in bipolar disorder. Further investigation is warranted.

Disclosure

No significant relationships.

Keywords

predictionbipolar disorderearly warning signalsexperience sampling methodology
Type
Abstract
Information
European Psychiatry , Volume 64 , Special Issue S1: Abstracts of the 29th European Congress of Psychiatry , April 2021 , pp. S78 - S79
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the European Psychiatric Association
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