No add-on effect of tDCS on fatigue and depression in chronic stroke patients: A randomized sham-controlled trial combining tDCS with computerized cognitive training

Abstract

Background: Fatigue and emotional distress rank high among self-reported unmet needs in life after stroke. Transcranial direct current stimulation (tDCS) may have the potential to alleviate these symptoms for some patients, but the acceptability and effects for chronic stroke survivors need to be explored in randomized controlled trials.

Methods: Using a randomized sham-controlled parallel design, we evaluated whether six sessions of 1 mA tDCS (anodal over F3, cathodal over O2) combined with computerized cognitive training reduced self-reported symptoms of fatigue and depression. Among the 74 chronic stroke patients enrolled at baseline, 54 patients completed the intervention. Measures of fatigue and depression were collected at five time points spanning a 2 months period.

Results: While symptoms of fatigue and depression were reduced during the course of the intervention, Bayesian analyses provided evidence for no added beneficial effect of tDCS. Less severe baseline symptoms were associated with higher performance improvement in select cognitive tasks, and study withdrawal was higher in patients with more fatigue and younger age. Time-resolved symptom analyses by a network approach suggested higher centrality of fatigue items (except item 1 and 2) than depression items.

Conclusion: The results reveal no add-on effect of tDCS on fatigue or depression but support the notion of fatigue as a relevant clinical symptom with possible implications for treatment adherence and response.

Keywords: brain stimulation; chronic stroke; poststroke fatigue; rehabilitation; tDCS.

FIGURE 1

Flow diagram of recruitment (left) and study timeline (right). Number of patients with complete FSS scores is provided in blue circles

FIGURE 2

Estimated evidence ratio (left) and posterior distributions of predictors (right). Log(BF) > 0 represent evidence in favor of the null hypothesis and log(BF) < 0 represent evidence in favor of the alternative hypothesis. Posterior distributions of predictors (right) for the fatigue model (red) and depression (green) model

FIGURE 3

Individual FSS and PHQ scores across time. Scores are grouped by experimental condition (active vs. sham)

FIGURE 4

Individual mean scores of FSS (x‐axis) and PHQ sum scores (y‐axis) plotted for all patients (n = 74). Vertical lines (gray and orange) mark commonly used cutoff values for clinical fatigue, while horizontal red line marks cutoff value for depression

FIGURE 5

Associations between baseline FSS and PHQ. Network visualization of Spearman partial correlations with EBICglasso regularization (tuning parameter = 0.15), between FSS sum score and PHQ items for all patients (n = 74) at baseline (left). Network visualization of full Spearman correlations between all FSS and PHQ items at baseline (right). Green edges signify positive correlations, while red edges (none present) represent negative correlations (Epskamp et al., 2012). The thickness of the lines indicates the strength of the association

FIGURE 6

Item strength centrality across time points. Standardized strength node centrality of the 17 FSS/PHQ items across five time points (left), and heatmap table (right) showing the ranked node strength centrality of the five networks, estimated at time point 1–5. Each node is ranked in decreasing order, from 1 (highest centrality) to 17 (lowest centrality). FSS item number 9 (“Fatigue interferes with my work, family, or social life”) demonstrated the highest mean ranked strength centrality across time, followed by FSS item 3 (“I am easily fatigued”)