Brugada Syndrome 1BrAIDNCT04641585

Brugada Syndrome and Artificial Intelligence Applications to Diagnosis

A study testing Patients affected by Brugada Syndrome 1 in people with Brugada Syndrome 1, run by Istituto di Fisiologia Clinica CNR at 6 sites in Italy.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Official record

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Trial summary

Aim of the project is the development of an integrated platform, based on machine learning and omic techniques, able to support physicians in as much as possible accurate diagnosis of Type 1 Brugada Syndrome (BrS). Read more about this study

Who is it for?: Ages 14 to 65 yearsHealthy volunteers can take part
Conditions the study is for: Brugada Syndrome 1
What is being tested?: Patients affected by Brugada Syndrome 1
Could I receive a placebo?: No, everyone receives an active treatment
How many people: 144 participants
Where: 6 sitesItaly
Study dates: 15 Jan 2021to 15 Sep 2023
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 14 to 65 years
All sexes
Healthy volunteers accepted
Child, Adult, Older adult

Who may be able to join

Brugada patients: patients with Brugada Syndrome 1 spontaneous or induced by the ajmaline test; patients with non-diagnostic electrocardiographic pattern for Brugada Syndrome 1 or negative in the presence of high clinical suspicion (family history for Brugada Syndrome, patients who survived cardiac arrest without organic heart disease)
Control patients: patients with frequent premature ventricular complex and normal left and right ventricular function; patients with suspected Brugada Syndrome 1 not confirmed by ajmaline test

Who cannot join

organic heart disease or diseases interfering with protocol completion
lack of signed informed consent
pregnancy
acute coronary artery disease, heart failure in the previous 3 months
severe renal or liver failure

Trial locations and contacts

6 sites in 1 country.

Giorgio Iervasi, Dr. contact

+390503153302

segreteria.direzione@ifc.cnr.it

City, postcode or hospital

6 sites in 1 country

Italy6 sites

Azienda USL Toscana Sud Est - U.O.C Cardiologia
Arezzo, Tuscany, 52100
Pasquale Giovanni Notarstefano, Dr., +3905752551, pasqualenotarstefano@gmail.com
Azienda Ospedaliera Universitaria Careggi - SOD Aritmologia
Florence, Tuscany, 50134
Paolo Pieragnoli, Dr., +390557946216, paolopieragnoli@virgilio.it
Azienda Ospedaliero Universitaria Pisana - Cardiologia 2
Pisa, Tuscany, 56100
Giulio Zucchelli, Dr., +39050993043, g.zucchelli@ao-pisa.toscana.it
Fondazione Toscana Gabriele Monasterio
Pisa, Tuscany, 56124
Marcello Piacenti, Dr., +390503153443, marcello.piacenti@ftgm.it
Istituto di Fisiologia Clinica IFC-CNR
Pisa, Tuscany, 56124
Federico Vozzi, Ph.D., +390503152672, vozzi@ifc.cnr.it
Maria-Aurora Morales, Dr., +390503153228, morales@ifc.cnr.it
Azienda Usl Toscana Nord Ovest - U.O.C. Cardiologia
Viareggio, Tuscany, 55049
Gianluca Solarino, Dr., +3905846051, gianluca.solarino@uslnordovest.toscana.it

Other trials in Italy

About this study

Read the detailed description

The aim of BrAID project is to integrate classic clinical guidelines for Brugada Syndrome 1 diagnosis evaluation with innovative Information and Communication Technologies and omic approaches, generating new diagnostic strategies in cardiovascular precision medicine of this disease.

Conditions: Brugada Syndrome 1
Being tested: Patients affected by Brugada Syndrome 1
Medical subject headings: Brugada Syndrome

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

Patients affected by Brugada Syndrome 1Diagnostic test
ECG analysis by Machine Learning algorithms and blood collection for the transcriptomic study of markers possibly associated with the disease

Study groups in NCT04641585
Study group	Role	What they receive
Patients affected by Brugada Syndrome 1	Experimental	Patients with spontaneous or drug-induced Brugada Syndrome 1 Receives: Diagnostic Test: Patients affected by Brugada Syndrome 1
Controls	Active comparator	Patients with no condition associated with spontaneous or drug-induced Brugada Syndrome 1 Receives: Diagnostic Test: Patients affected by Brugada Syndrome 1

What is being measured

The primary outcome is the main question the study is designed to answer.

Machine Learning recognition of Brugada Syndrome 1
Identification of Brugada type 1 Syndrome coved ST component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines
Measured: Week 20
Machine Learning recognition of Brugada Syndrome 1
Identification of Brugada type 1 Syndrome QRS fragmentation component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines
Measured: Week 20
Machine Learning recognition of Brugada Syndrome 1
Identification and characterization of Brugada type 1 Syndrome T segment depression component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines
Measured: Week 20
Machine Learning recognition of Brugada Syndrome 1
Identification of Brugada type 1 Syndrome broad P wave with PQ prolongation component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines
Measured: Week 20

Secondary outcomes (2)

Biomarkers associated with Brugada Syndrome 1
Identification of biomarkers associated with Brugada Syndrome 1 by the means of blood transcriptomic profile and exosomes analysis of patients. Transcriptomic and exosome could provide new insight into the pathophysiology of signalling in this pathology, as well as for application in Brugada Syndrome 1 diagnosis and therapeutics.
Transcriptomic will provide a global picture of phenotypical changes associated with the disease, highlighting the potential genes involved in the development of Brugada Syndrome 1 The analysis of exosome coding and noncoding RNAs, participating in a variety of basic cellular functions, could also evidence potentially important pathophysiologic effects both in cardiac cells as well as on the release of electrical stimuli.
The study will be performed in a cohort of 44 patients (prospective study) and results will be validated in a cohort of 100 patients (validation study)
Measured: week 48
Stratification risk
Development of stratification risk system for Brugada type 1 Syndrome by the integration of ECG Machine Learning algorithms and biomarkers. In particular, the module will combine the peculiar ECG patterns associated with BrS (coved ST, QRS fragmentation, T segment depression, broad P wave with PQ prolongation)(outcome 1-4) and omic (genes) and exosome markers (coding and noncoding RNAs)(outcome 5) with the aim to improve patient risk stratification.
Specifically, gene expression modulation (expressed as % respect to control population) of Na+ (e.g., Nav1.5, Nav1.3, Nav2.1), Ca2+ (e.g. Cav3.1, HCN3) and K+ channels (e.g.,TWIK1, Kv4.3) will be evaluated.
The study will be performed in a cohort of 44 patients (prospective study) and results will be validated in a cohort of 100 patients (validation study).
Measured: week 64

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

15 Jan 202115 Sep 2023

First posted24 Nov 2020
Study start15 Jan 2021 (estimated)
Primary completion15 Mar 2023 (estimated)
Study completion15 Sep 2023 (estimated)

Resources

Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
Publications (7)Papers the sponsor has linked to this study.
Other trials for Brugada Syndrome 1Studies 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: Diagnosis
Allocation: Non-randomised
Intervention model: Parallel groups
Masking: None (open label)
Enrolment: 144 participants (estimated)

IDs, dates and publications

ClinicalTrials.gov ID: NCT04641585
Sponsor's protocol ID: BrAID
Acronym: BrAID
Status last verified: Nov 2020
First submitted: 22 Oct 2020
Last updated: 24 Nov 2020
Results posted: No
FDA-regulated drug: No
FDA-regulated device: No
Individual data sharing: No

Publications

Brugada P, Brugada J. Right bundle branch block, persistent ST segment elevation and sudden cardiac death: a distinct clinical and electrocardiographic syndrome. A multicenter report. J Am Coll Cardiol. 1992 Nov 15;20(6):1391-6. doi: 10.1016/0735-1097(92)90253-j.
PubMed 1309182
Quan XQ, Li S, Liu R, Zheng K, Wu XF, Tang Q. A meta-analytic review of prevalence for Brugada ECG patterns and the risk for death. Medicine (Baltimore). 2016 Dec;95(50):e5643. doi: 10.1097/MD.0000000000005643.
PubMed 27977610
Vutthikraivit W, Rattanawong P, Putthapiban P, Sukhumthammarat W, Vathesatogkit P, Ngarmukos T, Thakkinstian A. Worldwide Prevalence of Brugada Syndrome: A Systematic Review and Meta-Analysis. Acta Cardiol Sin. 2018 May;34(3):267-277. doi: 10.6515/ACS.201805_34(3).20180302B.
PubMed 29844648
Antzelevitch C, Brugada P, Borggrefe M, Brugada J, Brugada R, Corrado D, Gussak I, LeMarec H, Nademanee K, Perez Riera AR, Shimizu W, Schulze-Bahr E, Tan H, Wilde A. Brugada syndrome: report of the second consensus conference. Heart Rhythm. 2005 Apr;2(4):429-40. doi: 10.1016/j.hrthm.2005.01.005.
PubMed 15898165
Wilde AA, Antzelevitch C, Borggrefe M, Brugada J, Brugada R, Brugada P, Corrado D, Hauer RN, Kass RS, Nademanee K, Priori SG, Towbin JA; Study Group on the Molecular Basis of Arrhythmias of the European Society of Cardiology. Proposed diagnostic criteria for the Brugada syndrome. Eur Heart J. 2002 Nov;23(21):1648-54. doi: 10.1053/euhj.2002.3382. No abstract available.
PubMed 12448445
Sarquella-Brugada G, Campuzano O, Arbelo E, Brugada J, Brugada R. Brugada syndrome: clinical and genetic findings. Genet Med. 2016 Jan;18(1):3-12. doi: 10.1038/gim.2015.35. Epub 2015 Apr 23.
PubMed 25905440
Morales MA, Piacenti M, Nesti M, Solarino G, Pieragnoli P, Zucchelli G, Del Ry S, Cabiati M, Vozzi F. The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition. BMC Cardiovasc Disord. 2021 Oct 13;21(1):494. doi: 10.1186/s12872-021-02280-3.
PubMed 34645390

Study at a glance

From the registry record, last updated by the sponsor on 24 Nov 2020. Recruitment status is as the sponsor reported it: confirm with the study team.

Official title: Brugada Syndrome and Artificial Intelligence Applications to Diagnosis
ClinicalTrials.gov ID: NCT04641585
Acronym / sponsor ID: BrAID / BrAID
Conditions: Brugada Syndrome 1
Study type: Interventional
Recruitment status: Unknown status
Enrolment: 144 participants (estimated)
Lead sponsor: Istituto di Fisiologia Clinica CNRUniversity, hospital or other
Collaborators: Fondazione Toscana Gabriele Monasterio, Azienda USL Toscana Sud Est, Azienda USL Toscana Nord Ovest, Azienda Ospedaliero-Universitaria Careggi, Azienda Ospedaliero, Universitaria Pisana
Study start: 15 Jan 2021 (estimated)
Primary completion: 15 Mar 2023 (estimated)
Study completion: 15 Sep 2023 (estimated)
First posted: 24 Nov 2020 (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.

Detailed description

Study design

Primary purpose: Diagnosis
Allocation: Non-randomised
Intervention model: Parallel groups
Masking: None (open label)
Number of arms: 2

Arm	Type	Receives
Patients affected by Brugada Syndrome 1	Experimental	Diagnostic Test: Patients affected by Brugada Syndrome 1Patients with spontaneous or drug-induced Brugada Syndrome 1
Controls	Active comparator	Diagnostic Test: Patients affected by Brugada Syndrome 1Patients with no condition associated with spontaneous or drug-induced Brugada Syndrome 1

Who may qualify

Ages: 14 to 65 years
Sex: All
Healthy volunteers: Accepted
Age groups: Child, Adult, Older adult

Key inclusion criteria (2 listed)

Brugada patients: patients with Brugada Syndrome 1 spontaneous or induced by the ajmaline test; patients with non-diagnostic electrocardiographic pattern for Brugada Syndrome 1 or negative in the presence of high clinical suspicion (family history for Brugada Syndrome, patients who survived cardiac arrest without organic heart disease)
Control patients: patients with frequent premature ventricular complex and normal left and right ventricular function; patients with suspected Brugada Syndrome 1 not confirmed by ajmaline test

Key exclusion criteria (5 listed)

organic heart disease or diseases interfering with protocol completion
lack of signed informed consent
pregnancy
acute coronary artery disease, heart failure in the previous 3 months
severe renal or liver failure

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
Patients affected by Brugada Syndrome 1ECG analysis by Machine Learning algorithms and blood collection for the transcriptomic study of markers possibly associated with the disease	Diagnostic test	Controls, Patients affected by Brugada Syndrome 1

Primary outcome

Machine Learning recognition of Brugada Syndrome 1
Time frame: Week 20
Identification of Brugada type 1 Syndrome coved ST component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines
Machine Learning recognition of Brugada Syndrome 1
Time frame: Week 20
Identification of Brugada type 1 Syndrome QRS fragmentation component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines
Machine Learning recognition of Brugada Syndrome 1
Time frame: Week 20
Identification and characterization of Brugada type 1 Syndrome T segment depression component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines
Machine Learning recognition of Brugada Syndrome 1
Time frame: Week 20
Identification of Brugada type 1 Syndrome broad P wave with PQ prolongation component in a cohort of 44 patients (prospective study) and validated in a cohort of 100 patients (validation study) according to the diagnostic patterns related to Brugada Syndrome 1 on 12-leads ECG as already published on current international guidelines

2 secondary outcomes

Biomarkers associated with Brugada Syndrome 1
Time frame: week 48
Stratification risk
Time frame: week 64

Results and safety

Results are not available in the source record.

Research links

Official record on ClinicalTrials.govLast updated by the sponsor 24 Nov 2020.
Background: PubMed 1309182Brugada P, Brugada J. Right bundle branch block, persistent ST segment elevation and sudden cardiac death: a distinct clinical and electrocardiographic syndrome. A multicenter report. J Am Coll Cardiol. 1992 Nov 15;20(6):1391-6. doi: 10.1016/0735-1097(92)90253-j.
Background: PubMed 27977610Quan XQ, Li S, Liu R, Zheng K, Wu XF, Tang Q. A meta-analytic review of prevalence for Brugada ECG patterns and the risk for death. Medicine (Baltimore). 2016 Dec;95(50):e5643. doi: 10.1097/MD.0000000000005643.
Background: PubMed 29844648Vutthikraivit W, Rattanawong P, Putthapiban P, Sukhumthammarat W, Vathesatogkit P, Ngarmukos T, Thakkinstian A. Worldwide Prevalence of Brugada Syndrome: A Systematic Review and Meta-Analysis. Acta Cardiol Sin. 2018 May;34(3):267-277. doi: 10.6515/ACS.201805_34(3).20180302B.
Background: PubMed 15898165Antzelevitch C, Brugada P, Borggrefe M, Brugada J, Brugada R, Corrado D, Gussak I, LeMarec H, Nademanee K, Perez Riera AR, Shimizu W, Schulze-Bahr E, Tan H, Wilde A. Brugada syndrome: report of the second consensus conference. Heart Rhythm. 2005 Apr;2(4):429-40. doi: 10.1016/j.hrthm.2005.01.005.
Background: PubMed 12448445Wilde AA, Antzelevitch C, Borggrefe M, Brugada J, Brugada R, Brugada P, Corrado D, Hauer RN, Kass RS, Nademanee K, Priori SG, Towbin JA; Study Group on the Molecular Basis of Arrhythmias of the European Society of Cardiology. Proposed diagnostic criteria for the Brugada syndrome. Eur Heart J. 2002 Nov;23(21):1648-54. doi: 10.1053/euhj.2002.3382. No abstract available.
Background: PubMed 25905440Sarquella-Brugada G, Campuzano O, Arbelo E, Brugada J, Brugada R. Brugada syndrome: clinical and genetic findings. Genet Med. 2016 Jan;18(1):3-12. doi: 10.1038/gim.2015.35. Epub 2015 Apr 23.
Derived from this study: PubMed 34645390Morales MA, Piacenti M, Nesti M, Solarino G, Pieragnoli P, Zucchelli G, Del Ry S, Cabiati M, Vozzi F. The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition. BMC Cardiovasc Disord. 2021 Oct 13;21(1):494. doi: 10.1186/s12872-021-02280-3.
Individual participant dataSharing planned: No

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.

Giorgio Iervasi, Dr. contact

+390503153302

segreteria.direzione@ifc.cnr.it

Federico Vozzi, Ph.D. principal investigator

Istituto di Fisiologia Clinica

6 sites in 1 country: see every site and its status.

Questions about this trial

What is this clinical trial studying?

A study testing Patients affected by Brugada Syndrome 1 in people with Brugada Syndrome 1, run by Istituto di Fisiologia Clinica CNR at 6 sites in Italy.

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 2 inclusion and 5 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 24 Nov 2020. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 6 sites in Italy. 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 Giorgio Iervasi, Dr. (+390503153302, segreteria.direzione@ifc.cnr.it), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Machine Learning recognition of Brugada Syndrome 1 (time frame: Week 20). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT04641585, which also lists 7 linked publications.

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 24 Nov 2020.