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Traumatic Brachial Plexus Lesion clinical trials

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NCT ID: NCT04852536 Not yet recruiting - Chronic Pain Clinical Trials

Electroencephalographia as Predictor of Effectiveness HD-tDCS in Neuropathic Pain: Machine Learning Approach

Start date: June 15, 2021
Phase:
Study type: Observational

Contextualization: Neuropathic pain is a complication present in the clinical picture of patients with traumatic Brachial Plexus injury (BPI). It is characterized by high intensity, severity and refractoriness to clinical treatments, resulting in high disability and loss of quality of life. Due to loss of afferent entry, it causes cortical and subcortical alterations and changes in somatotopic representation, from inadequate plastic adaptations in the Central and Peripheral Nervous System, one of the therapies with potential benefit in this population is the Transcranial High Definition Continuous Current Stimulation (HD-tDCS). Thus, by using connectivity-based response prediction and machine learning, it will allow greater assurance of efficiency and optimization of the application of this therapy, being directed to patients with greater potential to benefit from the application of this approach. Objective: Using connectivity-based prediction and machine learning, this study aims to assess whether baseline EEG related characteristics predict the response of patients with neuropathic pain after BPI to the effectiveness of HD-tDCS treatment. Materials and methods: A quantitative, applied, exploratory, open-label response prediction study will be conducted from data acquired from a pilot, triple-blind, cross-over, placebo-controlled, randomized clinical trial investigating the efficacy of applying HD-tDCS to patients with neuropathic brachial plexus trauma pain. Participants will be evaluated for eligibility and then randomly allocated into two groups to receive the active HD-tDCS or simulated HD-tDCS. The primary outcome will be pain intensity as measured by the numerical pain scale. Participants will be invited to participate in an EEG study before starting treatment. Clinical improvement labels used for machine learning classification will be determined based on data obtained from the clinical trial (baseline and post-treatment evaluations). The hypothesis adopted in this study is that the response prediction model constructed from EEG frequency band pattern data collected at baseline will be able to identify responders and non-responders to HD-tDCS treatment.

NCT ID: NCT04649749 Completed - Clinical trials for Brachial Plexus Neuropathies

Central Programming in Patients With a Bionic Hand After Traumatic Brachial Plexus Injury

Start date: October 1, 2020
Phase:
Study type: Observational

Traumatic brachial plexus lesions may lead to permanent impairment of hand function despite brachial plexus surgery. In selected cases the affected forearm can be amputated and replaced by a bionic hand. It is unclear how cortical activation patterns change after the injury and after acquisition of the hand prosthesis considering the complex changes in sensory and motor feedback. The aim of the study is to measure cortical activity with fMRI during actual and imagery movements with the affected and healthy arm in a group of patients after traumatic brachial plexus injury and a group in whom this was followed by replacement with a bionic hand. In this prospective study three groups of patients will participate: 1) 3 adult patients with a traumatic brachial plexus lesion eligible for a bionic arm but prior to its acquisition, 2) 3 patients with a traumatic brachial plexus lesion who have acquired the bionic arm already, and 3) 10 healthy subjects. The investigators will measure cortical activity using fMRI BOLD tasks of closing the hand and motor imagery of this movement. Cortical activity will be compared between the three groups. Additionally, regional gray matter volume, resting-state, and DTI networks will be studied. Written informed consent will be provided prior to the investigation. The complete examination has a duration of approximately 45 minutes.