Predicting Outcomes From tDCS Intervention in Parkinson' Disease Using Electroencephalographic Biomarkers and Machine Learning Approach: the PREDICT Study Protocol

NCT ID: NCT04819061

Last Updated: 2021-03-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

56 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-06-01

Study Completion Date

2021-12-31

Brief Summary

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Parkinson's disease (PD) is a progressive and disabling neurodegenerative disease, clinically characterized by motor and non-motor symptoms. The potential of the "Transcranial direct current stimulation" (tDCS) for symptomatic improvement in these patients has been demonstrated, but the factors associated with the best therapeutic response are not known. The electroencephalogram (EEG) is considered as a diagnostic and prognostic biomarker of PD, and has been used in recent studies associated with machine-learning methods to identify predictors of responses in neurological and psychiatric conditions. Using connectivity-based prediction and machine-learning, the investigators intend to identify and compare characteristics related to baseline resting EEG between PD responders and non-responders to tDCS treatment.

The recruited participants will be randomized to treatment with active tDCS associated with dual-task motor therapy or motor therapy with visual cues. A resting-state electroencephalography (EEG) will be recorded prior to the start of the treatment. The investigators will determine clinical improvement labels used for machine learning classification, in baseline and posttreatment assessments and will use three different methods to categorize the data into two classes (low or high improvement): Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Extreme Learning Machine (ELM). The functional label will be based on the Timed Up and Go Test recorded at baseline and posttreament of tDCS treatment.

Detailed Description

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Conditions

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Parkinson Disease Electroencephalogram Transcranial Direct Current Stimulation

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

This is a sham-controlled, double-blind randomized multicentric clinical trial that will analyze patients with a confirmed diagnosis of Parkinson disease who were subjected to tDCS associated with dual-task motor training. Whe aim to predict response to tDCS treatment using electroencephalographic biomarkers and machine learning approach.
Primary Study Purpose

OTHER

Blinding Strategy

TRIPLE

Participants Caregivers Investigators

Study Groups

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Active group

In the group G1 will be administered: tDCS active + dual-task motor training

Group Type ACTIVE_COMPARATOR

tDCS Active

Intervention Type OTHER

This group will undergo the motor training and active tDCS. Will be performed 12 sessions in three sessions per week for 30 minutes. Participants will undergo an electroencephalogram before starting the clinical trial. The duration between this baseline EEG and entry into the clinical trial that will assess the effectiveness of tDCS will be two weeks. We will determine the clinical improvement labels used for machine learning classification based on data obtained during the clinical trial (baseline and post-treatment assessments), according to procedures conducted in similar studies.

Sham group

In the group G2 will be administered: tDCS sham + dual-task motor training

Group Type SHAM_COMPARATOR

tDCS sham

Intervention Type OTHER

This group will undergo the motor training and tDCS sham. Will be performed 12 sessions in three sessions per week for 30 minutes. Participants will undergo an electroencephalogram before starting the clinical trial. The duration between this baseline EEG and entry into the clinical trial that will assess the effectiveness of tDCS will be two weeks.

We will determine the clinical improvement labels used for machine learning classification based on data obtained during the clinical trial (baseline and post-treatment assessments), according to procedures conducted in similar studies.

Interventions

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tDCS Active

This group will undergo the motor training and active tDCS. Will be performed 12 sessions in three sessions per week for 30 minutes. Participants will undergo an electroencephalogram before starting the clinical trial. The duration between this baseline EEG and entry into the clinical trial that will assess the effectiveness of tDCS will be two weeks. We will determine the clinical improvement labels used for machine learning classification based on data obtained during the clinical trial (baseline and post-treatment assessments), according to procedures conducted in similar studies.

Intervention Type OTHER

tDCS sham

This group will undergo the motor training and tDCS sham. Will be performed 12 sessions in three sessions per week for 30 minutes. Participants will undergo an electroencephalogram before starting the clinical trial. The duration between this baseline EEG and entry into the clinical trial that will assess the effectiveness of tDCS will be two weeks.

We will determine the clinical improvement labels used for machine learning classification based on data obtained during the clinical trial (baseline and post-treatment assessments), according to procedures conducted in similar studies.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Diagnosis of idiopathic Parkinson's disease by a neurologist based on Parkinson's Disease Society Brain Bank (PDSBB) criteria (Hughes et al.,1992)
* Disease staging between 1.5 and 3, according to the modified Hoehn and Yahr scale (Hoehn and Yahr, 1967)
* Regular pharmacological treatment with levodopa (equivalent dose \> 300mg) or taking antiparkinsonian medication such as anticholinergics, selegiline, dopamine agonists (amantadine) and COMT (catechol-O-methyl transferase) inhibitors
* Score of more than 24 points on the Mini-Mental State Examination (Folstein et al., 1975)

Exclusion Criteria

* Associated neurological, musculoskeletal and/or cardiorespiratory diseases that could compromise gait;
* alcohol or substance abuse disorders;
* Deep brain stimulation implant;
* History of brain trauma or neurological disease that would interfere with study procedures.
Minimum Eligible Age

40 Years

Maximum Eligible Age

70 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Universidade Federal do Rio Grande do Norte

OTHER

Sponsor Role collaborator

Federal University of ParaĆ­ba

OTHER

Sponsor Role lead

Responsible Party

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Suellen Marinho Andrade

Principal Investigator and Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Central Contacts

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Suellen Andrade

Role: CONTACT

986046032 ext. 5583

Other Identifiers

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EEGtDCS

Identifier Type: -

Identifier Source: org_study_id

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