Traumatic Brachial Plexus LesionNCT04852536
Electroencephalographia as Predictor of Effectiveness HD-tDCS in Neuropathic Pain: Machine Learning Approach
An observational study of Traumatic Brachial Plexus Lesion and Chronic Pain, run by Federal University of Paraíba at 1 site in Brazil.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Traumatic Brachial Plexus Lesion, Chronic Pain
- What is being tested?
- Neurostimulation (High Definition - transcranial Direct Current Stimulation) HD-tDCS
- Type of treatment
- Medical device
- How many people
- 30 participants
- Where
- 1 siteBrazil
- Study dates
- 15 Jun 2021to 15 Jun 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Participants in a triple-blind clinical trial, based on free demand by the Laboratory of Neuroscience and aging studies at the UFPB and through access to a database with the information of these patients, linked to the Institute of Neurology and Neurosurgery of Paraíba. Patients diagnosed with neuropathic pain due to brachial plexus injury according to clinical history, physical examination and complementary. The diagnosis will be based on clinical and neurophysiological criteria, according to protocols and recommendations of Guidelines of the American Academy of Neurology. Also, it will be based on clinical evidence of loss of post-traumatic sensitivity and muscle weakness involving the upper limb. And neurophysiological tests showing damage to the nerve trunks of the brachial plexus.
Who may be able to join
- Age over 18 years;
- Moderate to severe pain score according to the Numerical Pain Scale (4-10);
- Persistent pain and refractory to clinical treatment for at least 3 months;
- Appropriate pharmacological treatment for pain for at least 1 month before the start of the study;
- Not presenting contraindications for Non-Invasive Brain Stimulation;
- Absence of concomitant diseases of the Central Nervous Sistem or Peripheral Nervous Sistem.
Who cannot join
- Failure to sign the informed consent form;
- Missing two consecutive or three alternate sessions during treatment;
- Developing a disabling condition that prevents further participation in the study
Trial locations and contacts
1 site in 1 country.
Brazil1 site
Federal University of Paraíba,Department of Psychology
João Pessoa, Paraíba, 58051-900
About this study
Official title: EEG as Predictor of Effectiveness of HD-tDCS in Treatment of Neuropathic Pain After Brachial Plexus Injury: Machine Learning Approach
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.
Read the detailed description
Using connectivity-based prediction and machine learning, the objective is to assess whether characteristics related to baseline EEG predict the response of patients with neuropathic pain after BPI to the effectiveness of HD-tDCS treatment. An observational, retrospective cohort study will be carried out, of predictive response with a quantitative approach, of an applied nature, of an exploratory and open-label type, related to the efficacy of HD-tDCS4x1 in patients with neuropathic pain due to BPI, from an analysis of data obtained from a pilot, placebo-controlled, triple-blind, randomized, crossover type clinical trial, in accordance with the CONSORT guidelines, which will investigate the effectiveness of treatment with HD-tDCS.
- Conditions
- Traumatic Brachial Plexus Lesion, Chronic Pain
- Being tested
- Neurostimulation (High Definition - transcranial Direct Current Stimulation) HD-tDCS
- Keywords
- Transcranial Direct Current Stimulation, Chronic Pain, Electroencephalogram, Machine learning
- Medical subject headings
- Chronic Pain
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Neurostimulation (High Definition - transcranial Direct Current Stimulation) HD-tDCSDevice
5 consecutive sessions lasting 20 minutes of HD-tDCS4x1, based on previous publications (VILLAMAR et al., 2013). A list will be provided current of 2 mA, placing a central electrode (anode) on the M1 contralateral to the painful limb and the four return electrodes within a radius of 7.5 cm around, corresponding approximately to Cz, F3, T7 and P3 if the stimulation is on the side left, and Cz, F4, T8 and P4 if it is on the right, according to the International 10/20 System.
| Study group | Role | What they receive |
|---|---|---|
| HD-tDCS4x1 | All data will be acquired from patients of the triple-blind clinical trial that will investigate the effectiveness of treatment for neuropathic pain after brachial plexus injury with HD-tDCS. There will be collection and analysis of EEG data before the clinical trial protocol, to later assess the prediction of response to the technique employed. At the end, they will be grouped into responders and non-responders to HD-tDCS, according to the numerical scale of pain, with assignments serving as targets for the analyzes with machine learning. The labels for clinical improvement used to classify machine learning will be determined based on the data obtained in the baseline and post-treatment assessments, according to similar studies. Thus, the EEG data of these patients will be retrospectively examined, identifying possible neurophysiological characteristics and biomarkers related to the frequency bands that allow predicting which patients are most likely to improve with this treatment. Receives: Device: Neurostimulation (High Definition - transcranial Direct Current Stimulation) HD-tDCS |
What is being measured
The primary outcome is the main question the study is designed to answer.
Pain intensity measured using Numerical Pain Scale
Identification of responders and non-responders to treatment with HD-tDCS, according to the scores obtained by the patients response on the Numerical Pain Scale recorded immediately after the treatment, thus determining the functional labels for processing machine learning models. This instrument measures the intensity of pain, consisting of 11 points (0-10), 0 being counted for no pain and 10 for the worst possible pain. A reduction of two points or by 30% will be considered a clinically important minimum difference (DWORKIN et al., 2008).
Measured: 1 week (5 sessions)
Neurophysiological characteristics and biomarkers recorded by EEG
The EEG data will be retrospectively examined by comparing the two groups (responders and non-responders), identifying possible neurophysiological characteristics and biomarkers related to frequency bands and connectivity that could be characterized as possible markers of response to treatment, predicting which are most likely to respond. The examination of the cortical electrical activity using the EEG tool (BrainVision actiCHamp, Herrsching, Germany), with 32 silver chloride electrodes fixed according to the International System 10-20, by means of an adjustable cap, containing holes that will allow the contact of the electrode with the scalp. The prefrontal, frontal, parietal, temporal and occipital regions will be monitored bilaterally (Fp1, Fp2, F3, F4), temporal (F7, F8, T3, T4, T5, T6), central (C3, C4, Cz) and parieto-occipital (P3, P4, P7, P8, O1, O2), in the condition of silence, with eyes closed, for five minutes each, totaling 10 minutes of collection for each participant.
Measured: One month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Apr 2021
- Study start15 Jun 2021 (estimated)
- Primary completion15 Dec 2021 (estimated)
- Study completion15 Jun 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Traumatic Brachial Plexus LesionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 30 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Federal University of Paraíba
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Suellen Marinho Andrade, Federal University of Paraíba
- Investigators
- Suellen Andrade, Principal investigator, Federal University of Paraiba
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04852536
- Sponsor's protocol ID
- EEGPain/hd-tDCS
- Status last verified
- Apr 2021
- First submitted
- 5 Apr 2021
- Last updated
- 21 Apr 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Apr 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- EEG as Predictor of Effectiveness of HD-tDCS in Treatment of Neuropathic Pain After Brachial Plexus Injury: Machine Learning Approach
- ClinicalTrials.gov ID
- NCT04852536
- Acronym / sponsor ID
- EEGPain/hd-tDCS
- Conditions
- Traumatic Brachial Plexus Lesion, Chronic Pain
- Keywords
- Transcranial Direct Current Stimulation, Chronic Pain, Electroencephalogram, Machine learning
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 30 participants (estimated)
- Lead sponsor
- Federal University of ParaíbaUniversity, hospital or other
- Study start
- 15 Jun 2021 (estimated)
- Primary completion
- 15 Dec 2021 (estimated)
- Study completion
- 15 Jun 2022 (estimated)
- First posted
- 21 Apr 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Using connectivity-based prediction and machine learning, the objective is to assess whether characteristics related to baseline EEG predict the response of patients with neuropathic pain after BPI to the effectiveness of HD-tDCS treatment. An observational, retrospective cohort study will be carried out, of predictive response with a quantitative approach, of an applied nature, of an exploratory and open-label type, related to the efficacy of HD-tDCS4x1 in patients with neuropathic pain due to BPI, from an analysis of data obtained from a pilot, placebo-controlled, triple-blind, randomized, crossover type clinical trial, in accordance with the CONSORT guidelines, which will investigate the effectiveness of treatment with HD-tDCS.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| HD-tDCS4x1 | – | Device: Neurostimulation (High Definition - transcranial Direct Current Stimulation) HD-tDCSAll data will be acquired from patients of the triple-blind clinical trial that will investigate the effectiveness of treatment for neuropathic pain after brachial plexus injury with HD-tDCS. There will be collection and analysis of EEG data before the clinical trial protocol, to later assess the prediction of response to the technique employed. At the end, they will be grouped into responders and non-responders to HD-tDCS, according to the numerical scale of pain, with assignments serving as targets for the analyzes with machine learning. The labels for clinical improvement used to classify machine learning will be determined based on the data obtained in the baseline and post-treatment assessments, according to similar studies. Thus, the EEG data of these patients will be retrospectively examined, identifying possible neurophysiological characteristics and biomarkers related to the frequency bands that allow predicting which patients are most likely to improve with this treatment. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Participants in a triple-blind clinical trial, based on free demand by the Laboratory of Neuroscience and aging studies at the UFPB and through access to a database with the information of these patients, linked to the Institute of Neurology and Neurosurgery of Paraíba. Patients diagnosed with neuropathic pain due to brachial plexus injury according to clinical history, physical examination and complementary. The diagnosis will be based on clinical and neurophysiological criteria, according to protocols and recommendations of Guidelines of the American Academy of Neurology. Also, it will be based on clinical evidence of loss of post-traumatic sensitivity and muscle weakness involving the upper limb. And neurophysiological tests showing damage to the nerve trunks of the brachial plexus.
Key inclusion criteria (6 listed)
- Age over 18 years;
- Moderate to severe pain score according to the Numerical Pain Scale (4-10);
- Persistent pain and refractory to clinical treatment for at least 3 months;
- Appropriate pharmacological treatment for pain for at least 1 month before the start of the study;
- Not presenting contraindications for Non-Invasive Brain Stimulation;
Key exclusion criteria (3 listed)
- Failure to sign the informed consent form;
- Missing two consecutive or three alternate sessions during treatment;
- Developing a disabling condition that prevents further participation in the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Neurostimulation (High Definition - transcranial Direct Current Stimulation) HD-tDCS5 consecutive sessions lasting 20 minutes of HD-tDCS4x1, based on previous publications (VILLAMAR et al., 2013). A list will be provided current of 2 mA, placing a central electrode (anode) on the M1 contralateral to the painful limb and the four return electrodes within a radius of 7.5 cm around, corresponding approximately to Cz, F3, T7 and P3 if the stimulation is on the side left, and Cz, F4, T8 and P4 if it is on the right, according to the International 10/20 System. | Device | HD-tDCS4x1 |
Primary outcome
Pain intensity measured using Numerical Pain Scale
Time frame: 1 week (5 sessions)
Identification of responders and non-responders to treatment with HD-tDCS, according to the scores obtained by the patients response on the Numerical Pain Scale recorded immediately after the treatment, thus determining the functional labels for processing machine learning models. This instrument measures the intensity of pain, consisting of 11 points (0-10), 0 being counted for no pain and 10 for the worst possible pain. A reduction of two points or by 30% will be considered a clinically important minimum difference (DWORKIN et al., 2008).
Neurophysiological characteristics and biomarkers recorded by EEG
Time frame: One month
The EEG data will be retrospectively examined by comparing the two groups (responders and non-responders), identifying possible neurophysiological characteristics and biomarkers related to frequency bands and connectivity that could be characterized as possible markers of response to treatment, predicting which are most likely to respond. The examination of the cortical electrical activity using the EEG tool (BrainVision actiCHamp, Herrsching, Germany), with 32 silver chloride electrodes fixed according to the International System 10-20, by means of an adjustable cap, containing holes that will allow the contact of the electrode with the scalp. The prefrontal, frontal, parietal, temporal and occipital regions will be monitored bilaterally (Fp1, Fp2, F3, F4), temporal (F7, F8, T3, T4, T5, T6), central (C3, C4, Cz) and parieto-occipital (P3, P4, P7, P8, O1, O2), in the condition of silence, with eyes closed, for five minutes each, totaling 10 minutes of collection for each participant.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Apr 2021.
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Suellen Andrade principal investigator
Federal University of Paraiba
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Traumatic Brachial Plexus Lesion and Chronic Pain, run by Federal University of Paraíba at 1 site in Brazil.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 21 Apr 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Brazil. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Suellen Andrade (+55 83 987772488, suellenandrade@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Pain intensity measured using Numerical Pain Scale (time frame: 1 week (5 sessions)). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Apr 2021; AzTrials last refreshed its copy on 8 Nov 2026.