EEG-arousal regulation as predictor of treatment response in patients suffering from obsessive compulsive disorder. Issue 10 (October 2017)

• Record Type: Journal Article
• Authors: Dohrmann, Anna-Lena; Stengler, Katarina; Jahn, Ina; Olbrich, Sebastian
• Is Part Of: Clinical neurophysiology. Volume 128:Issue 10(2017:Oct.)
• Page Start: 1906
• Page End: 1914
• Publication Date: 2017-10
• Subjects: CNS-arousal -- Resting state EEG -- Obsessive compulsive disorder (OCD) -- Individualized treatment -- Selective serotonin reuptake inhibitor (SSRI) -- Cognitive behavioral therapy (CBT); Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2017.07.406
• Languages: English
• ISSNs: 1388-2457

Abstract

Highlights: Resting state CNS-arousal profiles of obsessive compulsive disorder (OCD) patients predict response to treatment. Lower amount of highest CNS-arousal levels indicate response. CNS-arousal markers allow discrimination between responders to different treatment strategies. Abstract: Objectives: Aim of this study was to analyze whether electroencephalogram (EEG)-based CNS-arousal markers differ for patients suffering from obsessive compulsive disorder (OCD) that either respond or do not respond to cognitive behavioral therapy (CBT), selective serotonin reuptake inhibitors (SSRIs) or their combination. Further the study aimed to identify specific response-predictors for the different therapy approaches. Methods: CNS-arousal from 51 unmedicated patients during fifteen-minute resting state was assessed using VIGALL (Vigilance Algorithm Leipzig). Clinical Global Impression (CGI) scores were used to assess response or non-response after three to six months following therapy (CBT, n = 18; SSRI, n = 11 or combination, n = 22). Differences between Responders (R) and Non-Responders (NR) were identified using multivariate analysis of covariance (MANCOVA) models. Results: MANCOVA revealed that Responders spent significant less time at the highest CNS-arousal stage 0. Further, low amounts of the highest CNS-arousal stages were specifically predictive for a response to a combined treatment approach. Conclusions: The fact that CNS-arousal markers allowed discrimination between Responders and Non-Responders and also between Responders of different treatment arms underlines a possible clinical value of EEG-based markers. Significance: These results encourage further research on EEG-arousal regulation for determining pathophysiological subgroups for treatment response.