Brugada Syndrome and Artificial Intelligence Applications to Diagnosis
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 144
- 试验地点
- 12
- 主要终点
- Machine Learning recognition of Brugada Syndrome 1
研究概览
简要总结
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).
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 14 Years 至 65 Years（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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
排除标准
- •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
结局指标
主要结局
Machine Learning recognition of Brugada Syndrome 1
时间窗: 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
次要结局
- Stratification risk(week 64)
- Biomarkers associated with Brugada Syndrome 1(week 48)