Parkinson DiseasePREDICTNCT04819061
Predicting Outcomes From tDCS Intervention in Parkinson' Disease Using Electroencephalographic Biomarkers and Machine Learning Approach: the PREDICT Study Protocol
A study testing tDCS Active in people with Parkinson Disease and Electroencephalogram, run by Federal University of Paraíba.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 40 to 70 years
- Conditions the study is for
- Parkinson Disease, Electroencephalogram, Transcranial Direct Current Stimulation
- What is being tested?
- tDCS Active
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 56 participants
- Where
- No sites listed yet
- Study dates
- 1 Jun 2021to 31 Dec 2021
- Phase
- Interventional
- 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 40 to 70 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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)
Who cannot join
- 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.
Trial locations and contacts
No sites are listed yet.
About this study
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.
- Being tested
- tDCS Active, tDCS sham
- Medical subject headings
- Parkinson Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
tDCS ActiveOther
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.
tDCS shamOther
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.
| Study group | Role | What they receive |
|---|---|---|
| Active group | Active comparator | In the group G1 will be administered: tDCS active + dual-task motor training Receives: Other: tDCS Active |
| Sham group | Sham comparator | In the group G2 will be administered: tDCS sham + dual-task motor training Receives: Other: tDCS sham |
What is being measured
The primary outcome is the main question the study is designed to answer.
Functional Mobility measured using the Timed Up and Go test (Podsiadlo D, Richardson S, 1991)
The functional mobility will be measured using the Timed Up and Go test to stand up from a chair at the command: "Walk 3 meters, walk along a demarcated course, turn around and walk back to the chair, then sit down".
Measured: 4 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Mar 2021
- Study start1 Jun 2021 (estimated)
- Primary completion1 Jun 2021 (estimated)
- Study completion31 Dec 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Parkinson DiseaseStudies 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 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.
- Masking
- Triple blind
- Who is masked
- Participant, Care provider, Investigator
- Enrolment
- 56 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Federal University of Paraíba
- Sponsor type
- University, hospital or other
- Collaborators
- Universidade Federal do Rio Grande do Norte
- Responsible party
- Principal investigator, Suellen Marinho Andrade, Federal University of Paraíba
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04819061
- Sponsor's protocol ID
- EEGtDCS
- Acronym
- PREDICT
- Status last verified
- Mar 2021
- First submitted
- 6 Mar 2021
- Last updated
- 26 Mar 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 26 Mar 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Predicting Outcomes From tDCS Intervention in Parkinson' Disease Using Electroencephalographic Biomarkers and Machine Learning Approach: the PREDICT Study Protocol
- ClinicalTrials.gov ID
- NCT04819061
- Acronym / sponsor ID
- PREDICT / EEGtDCS
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 56 participants (estimated)
- Lead sponsor
- Federal University of ParaíbaUniversity, hospital or other
- Collaborators
- Universidade Federal do Rio Grande do Norte
- Study start
- 1 Jun 2021 (estimated)
- Primary completion
- 1 Jun 2021 (estimated)
- Study completion
- 31 Dec 2021 (estimated)
- First posted
- 26 Mar 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.
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.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind (participant, care provider, investigator)
- Number of arms
- 2
- Model description
- 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.
| Arm | Type | Receives |
|---|---|---|
| Active group | Active comparator | Other: tDCS ActiveIn the group G1 will be administered: tDCS active + dual-task motor training |
| Sham group | Sham comparator | Other: tDCS shamIn the group G2 will be administered: tDCS sham + dual-task motor training |
Who may qualify
- Ages
- 40 to 70 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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)
Key exclusion criteria (4 listed)
- 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.
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 |
|---|---|---|
| tDCS ActiveThis 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. | Other | Active group |
| tDCS shamThis 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. | Other | Sham group |
Primary outcome
Functional Mobility measured using the Timed Up and Go test (Podsiadlo D, Richardson S, 1991)
Time frame: 4 weeks
The functional mobility will be measured using the Timed Up and Go test to stand up from a chair at the command: "Walk 3 meters, walk along a demarcated course, turn around and walk back to the chair, then sit down".
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Mar 2021.
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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.
Questions about this trial
What is this clinical trial studying?
A study testing tDCS Active in people with Parkinson Disease and Electroencephalogram, run by Federal University of Paraíba.
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 4 inclusion and 4 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 26 Mar 2021. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. 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 (986046032 ext. 5583, suellenandrade@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Functional Mobility measured using the Timed Up and Go test (Podsiadlo D, Richardson S, 1991) (time frame: 4 weeks). 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 26 Mar 2021.