Longitudinal resting-state electroencephalography in patients with chronic pain undergoing interdisciplinary multimodal pain therapy

Henrik Heitmann, Cristina Gil Ávila, Moritz M Nickel, Son Ta Dinh, Elisabeth S May, Laura Tiemann, Vanessa D Hohn, Thomas R Tölle, Markus Ploner, Henrik Heitmann, Cristina Gil Ávila, Moritz M Nickel, Son Ta Dinh, Elisabeth S May, Laura Tiemann, Vanessa D Hohn, Thomas R Tölle, Markus Ploner

Abstract

Chronic pain is a major healthcare issue posing a large burden on individuals and society. Converging lines of evidence indicate that chronic pain is associated with substantial changes of brain structure and function. However, it remains unclear which neuronal measures relate to changes of clinical parameters over time and could thus monitor chronic pain and treatment responses. We therefore performed a longitudinal study in which we assessed clinical characteristics and resting-state electroencephalography data of 41 patients with chronic pain before and 6 months after interdisciplinary multimodal pain therapy. We specifically assessed electroencephalography measures that have previously been shown to differ between patients with chronic pain and healthy people. These included the dominant peak frequency; the amplitudes of neuronal oscillations at theta, alpha, beta, and gamma frequencies; as well as graph theory-based measures of brain network organization. The results show that pain intensity, pain-related disability, and depression were significantly improved after interdisciplinary multimodal pain therapy. Bayesian hypothesis testing indicated that these clinical changes were not related to changes of the dominant peak frequency or amplitudes of oscillations at any frequency band. Clinical changes were, however, associated with an increase in global network efficiency at theta frequencies. Thus, changes in chronic pain might be reflected by global network changes in the theta band. These longitudinal insights further the understanding of the brain mechanisms of chronic pain. Beyond, they might help to identify biomarkers for the monitoring of chronic pain.

Trial registration: ClinicalTrials.gov NCT03634670.

Conflict of interest statement

T.R Tölle received consulting fees from Almirall Hermal, AOP Orphan, Benkitt Rekinser, Bionest Partners, Grünenthal, Hexal, Indivior, Kaia Health, Lilly, Medscape Mundipharma, MSD, Novartis, Pfizer, Recordati Pharma, Sanofi-Aventis, and TAD Pharma; all not related to the present work. The remaining authors have no conflicts of interest to declare.

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.

Figures

Figure 1.
Figure 1.
Timeline of procedures. Patients underwent 2 identical assessments, including evaluation of clinical characteristics using questionnaires and resting-state EEG. The baseline assessment was performed in the week before or within the first 3 days of the interdisciplinary multimodal pain therapy program. The follow-up assessment was performed 6 to 9 months later. Interdisciplinary multimodal pain therapy was provided on 20 days over a period of either 4 weeks (5 days per week) or 7 weeks (3 days per week). EEG, electroencephalography.
Figure 2.
Figure 2.
Clinical measures at baseline and follow-up. Measures of average pain intensity on the Numerical Rating Scale (NRS) as well as scores for pain-related disability (Pain Disability Index [PDI]) and depression (Beck Depression Inventory II [BDI]) at baseline and follow-up are depicted. Raincloud plots show unmirrored violin plots displaying the probability density function of the data, boxplots, and individual data points. Boxplots depict the sample median as well as first (Q1) and third quartiles (Q3). Whiskers extend from Q1 to the smallest value within Q1 −1.5* interquartile range (IQR) and from Q3 to the largest values within Q3 +1.5* IQR.
Figure 3.
Figure 3.
Correlations of changes in theta band global efficiency with changes in clinical measures. Bivariate correlations of changes in the graph theory-based measure global efficiency (gEff) in the theta band with changes in average pain intensity, pain-related disability (Pain Disability Index [PDI]), and depression (Beck Depression Inventory II [BDI]) are depicted. Δ = change = follow-up values—baseline values.

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