Brugada Syndrome and Artificial Intelligence Applications to Diagnosis

NCT04641585 | Unknown

• 1 other identifier: BrAID
• Study Type: interventional
• Target: 144
• Locations: 1 country
• Sites: 6

Brief 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).

Conditions

Brugada Syndrome 1

Outcome Measures

Primary Outcomes (4)

• 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

  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

  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

  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

  Week 20

Secondary Outcomes (2)

• Biomarkers associated with Brugada Syndrome 1

  week 48

• Stratification risk

  week 64

Study Arms (2)

Patients affected by Brugada Syndrome 1

EXPERIMENTAL

Patients with spontaneous or drug-induced Brugada Syndrome 1

Diagnostic Test: Patients affected by Brugada Syndrome 1

Controls

ACTIVE COMPARATOR

Patients with no condition associated with spontaneous or drug-induced Brugada Syndrome 1

Diagnostic Test: Patients affected by Brugada Syndrome 1

Interventions

Patients affected by Brugada Syndrome 1 DIAGNOSTIC_TEST

ECG analysis by Machine Learning algorithms and blood collection for the transcriptomic study of markers possibly associated with the disease

Controls; Patients affected by Brugada Syndrome 1

Eligibility Criteria

• Age: 14 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• Istituto di Fisiologia Clinica CNR: lead
• Fondazione Toscana Gabriele Monasterio: collaborator
• Azienda USL Toscana Sud Est: collaborator
• Azienda USL Toscana Nord Ovest: collaborator
• Azienda Ospedaliero-Universitaria Careggi: collaborator
• Azienda Ospedaliero, Universitaria Pisana: collaborator

Study Sites (6)

Azienda USL Toscana Sud Est - U.O.C Cardiologia

Arezzo, Tuscany, 52100, Italy

Location

Azienda Ospedaliera Universitaria Careggi - SOD Aritmologia

Florence, Tuscany, 50134, Italy

Location

Azienda Ospedaliero Universitaria Pisana - Cardiologia 2

Pisa, Tuscany, 56100, Italy

Location

Fondazione Toscana Gabriele Monasterio

Pisa, Tuscany, 56124, Italy

Location

Istituto di Fisiologia Clinica IFC-CNR

Pisa, Tuscany, 56124, Italy

Location

Azienda Usl Toscana Nord Ovest - U.O.C. Cardiologia

Viareggio, Tuscany, 55049, Italy

Location

Related Publications (7)

• 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.

  PMID: 1309182 BACKGROUND

• 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.

  PMID: 27977610 BACKGROUND

• 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.

  PMID: 29844648 BACKGROUND

• 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.

  PMID: 15898165 BACKGROUND

• 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.

  PMID: 12448445 BACKGROUND

• 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.

  PMID: 25905440 BACKGROUND

• 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.

  PMID: 34645390 DERIVED

MeSH Terms

Conditions

Brugada Syndrome

Condition Hierarchy (Ancestors)

Arrhythmias, Cardiac; Heart Diseases; Cardiovascular Diseases; Cardiac Conduction System Disease; Genetic Diseases, Inborn; Congenital, Hereditary, and Neonatal Diseases and Abnormalities

Study Officials

• Federico Vozzi, Ph.D.

  Istituto di Fisiologia Clinica

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Giorgio Iervasi, Dr.

CONTACT

+390503153302; segreteria.direzione@ifc.cnr.it

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 22, 2020
• First Posted: November 24, 2020
• Study Start: January 15, 2021
• Primary Completion: March 15, 2023
• Study Completion: September 15, 2023
• Last Updated: November 24, 2020

Record last verified: 2020-11

Data Sharing

• IPD Sharing: Will not share

Locations

IT (6)