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Dynamic time warp analysis of individual symptom trajectories in patients with bipolar disorder

INTRODUCTION: Manic and depressive mood states in bipolar disorder (BD) may emerge from the non-linear relations between constantly changing mood symptoms exhibited as a complex dynamic system. Dynamic Time Warp (DTW) is an algorithm that may capture symptom interactions from panel data with sparse...

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Detalles Bibliográficos
Autores principales: Mesbah, R., Koenders, M., Spijker, A. T., de Leeuw, M., van Hemert, A. M., Giltay, E. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660331/
http://dx.doi.org/10.1192/j.eurpsy.2023.1209
Descripción
Sumario:INTRODUCTION: Manic and depressive mood states in bipolar disorder (BD) may emerge from the non-linear relations between constantly changing mood symptoms exhibited as a complex dynamic system. Dynamic Time Warp (DTW) is an algorithm that may capture symptom interactions from panel data with sparse observations over time. OBJECTIVES: The current study is the first to analyze a time series of depression and manic symptoms using DTW analyses in patients with BD. We studied interactions and relative changes in symptom severity within and between participants. METHODS: The Young Mania Rating Scale and Quick Inventory of Depressive Symptomatology were repeatedly assessed in 141 patients with BD, with on average 5.5 assessments per patient every 3 to 6 months. DTW calculated the distance between each of the 27*27 pairs of standardized symptom scores. The changing profile of standardized symptom scores of BD patients was analyzed in individual patients, yielding symptom dimensions in aggregated group-level analyses. Using an asymmetric time-window, symptom changes that preceded other symptom changes (i.e., Granger causality) yielded a directed network. RESULTS: The mean age of the patients was 40.1 (SD 13.5) years old, and 60% were female. Idiographic symptom networks were highly variable between patients. Yet, nomothetic analyses showed five symptom dimensions: core (hypo)mania (6 items), dysphoric mania (5 items), lethargy (7 items), somatic/suicidality (6 items), and sleep (3 items). Symptoms of the ‘Lethargy’ dimension showed the highest out-strength, and its changes preceded those of ‘somatic/suicidality’, while changes in ‘core (hypo)mania’ preceded those of ‘dysphoric mania’. Image: Image 2: Image 3: CONCLUSIONS: DTW may help to capture meaningful BD symptom interactions from panel data with sparse observations. It may increase insight into the temporal dynamics of symptoms, as those with high out-strength (rather than high in-strength) could be promising targets for intervention. DISCLOSURE OF INTEREST: None Declared