Literature DB >> 29766490

Emotional hyper-reactivity and cardiometabolic risk in remitted bipolar patients: a machine learning approach.

A A Dargél1,2, F Roussel3, S Volant4, B Etain5,6, R Grant7, J-M Azorin5,8, K M'Bailara5,9, F Bellivier5,6, T Bougerol5,10, J-P Kahn5,11, P Roux5,12,13, V Aubin5,14, P Courtet5,15, M Leboyer5,16,17, F Kapczinski18, C Henry1,5,16,17.   

Abstract

OBJECTIVE: Remitted bipolar disorder (BD) patients frequently present with chronic mood instability and emotional hyper-reactivity, associated with poor psychosocial functioning and low-grade inflammation. We investigated emotional hyper-reactivity as a dimension for characterization of remitted BD patients, and clinical and biological factors for identifying those with and without emotional hyper-reactivity.
METHOD: A total of 635 adult remitted BD patients, evaluated in the French Network of Bipolar Expert Centers from 2010-2015, were assessed for emotional reactivity using the Multidimensional Assessment of Thymic States. Machine learning algorithms were used on clinical and biological variables to enhance characterization of patients.
RESULTS: After adjustment, patients with emotional hyper-reactivity (n = 306) had significantly higher levels of systolic and diastolic blood pressure (P < 1.0 × 10-8 ), high-sensitivity C-reactive protein (P < 1.0 × 10-8 ), fasting glucose (P < 2.23 × 10-6 ), glycated hemoglobin (P = 0.0008) and suicide attempts (P = 1.4 × 10-8 ). Using models of combined clinical and biological factors for distinguishing BD patients with and without emotional hyper-reactivity, the strongest predictors were: systolic and diastolic blood pressure, fasting glucose, C-reactive protein and number of suicide attempts. This predictive model identified patients with emotional hyper-reactivity with 84.9% accuracy.
CONCLUSION: The assessment of emotional hyper-reactivity in remitted BD patients is clinically relevant, particularly for identifying those at higher risk of cardiometabolic dysfunction, chronic inflammation, and suicide.
© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  C-reactive protein; bipolar disorder; cardiometabolic dysfunction; emotional hyper-reactivity; machine learning

Mesh:

Substances:

Year:  2018        PMID: 29766490     DOI: 10.1111/acps.12901

Source DB:  PubMed          Journal:  Acta Psychiatr Scand        ISSN: 0001-690X            Impact factor:   6.392


  3 in total

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Authors:  Alja Videtič Paska; Katarina Kouter
Journal:  Bosn J Basic Med Sci       Date:  2021-08-01       Impact factor: 3.363

2.  Blood pressure in bipolar disorder: evidence of elevated pulse pressure and associations between mean pressure and mood instability.

Authors:  Niall M McGowan; Molly Nichols; Amy C Bilderbeck; Guy M Goodwin; Kate E A Saunders
Journal:  Int J Bipolar Disord       Date:  2021-02-01

3.  Developing "MinDag" - an app to capture symptom variation and illness mechanisms in bipolar disorder.

Authors:  Thomas D Bjella; Margrethe Collier Høegh; Stine Holmstul Olsen; Sofie R Aminoff; Elizabeth Barrett; Torill Ueland; Romain Icick; Ole A Andreassen; Mari Nerhus; Henrik Myhre Ihler; Marthe Hagen; Cecilie Busch-Christensen; Ingrid Melle; Trine Vik Lagerberg
Journal:  Front Med Technol       Date:  2022-07-22
  3 in total

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