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Published on: January 5, 2024
Transcranial Electric Stimulation in Chronic Pain Patients: Clinical Profile of Treatment Responders
Antonio Gil-Ugidos1, Jorge Alcántara-Espinosa1, Lara Rubal-Otero2
1Brain and Pain Lab, Institute of Psychology (IPsiUS), University of Santiago de Compostela, Santiago de Compostela, Spain.
Purpose:
Pharmacological interventions for chronic pain (CP) show limited evidence and adverse side effects, and thus, the management of CP represents a challenge for the healthcare systems. In the last few years, transcranial Electrical Stimulation (tES) has yielded positive results in relieving pain in patients with CP. However, the evidence has been obtained through group-level analyses without considering patient profiles that may benefit most from this technique.
Design:
In this secondary analysis, we utilized data from a clinical trial involving 96 CP patients who undertook 15 daily consecutive sessions of tES at home of either transcranial Direct Current Stimulation or transcranial Alternate Current Stimulation.
Methods:
With the aim of ascertaining the predictors of treatment efficacy, we carried out a comparison between responders (patients with a pain intensity reduction of 30% or more after the tES treatment) and non-responders and built a multivariable binary logistic regression model.
Results:
Only 24% of the patients reported a clinically significant improvement in pain intensity. Comparison between the clinical characteristics of patients showed that depression and anxiety-related variables appear to be the most closely related to treatment response. Moreover, finding signs that the number of years with depression and the onset of depression could be the variables with the highest (nearly significant) association with treatment response.
Conclusions:
These results provide preliminary clues to profile patients who could benefit more from tES, an important step to personalize neuromodulation treatments.
Clinical Implications:
Identifying CP patients who could benefit most from tES treatments could help clinicians with decision-making and reduce patient suffering through personalized treatments.

