Brugada Syndrome and Artificial Intelligence Applications to Diagnosis

Brugada Syndrome and Artificial Intelligence Applications to Diagnosis

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).

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.

Inclusion Criteria:

• 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

Exclusion Criteria:

• 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