Detection of Hypertrophic Cardiomyopathy Using Electrocardiograms and Echocardiograms Through Federated Learning
试验速览
- 阶段
- 不适用
- 状态
- Enrolling By Invitation
- 入组人数
- 1,000
- 试验地点
- 6
- 主要终点
- Diagnosis of HCM
研究概览
简要总结
HCM FLIP study is a two-phase protocol focusing on the detection of Hypertrophic Cardiomyopathy using Electrocardiograms and Echocardiograms through Federated Learning.
详细描述
HCM FLIP (Hypertrophic Cardiomyopathy Federated Learning Implementation Platform) aim to build and test a model's system impact to detect hypertrophic cardiomyopathy (HCM) by training a machine learning (ML) model with electrocardiograms (ECGs) and echocardiograms (ECHOs). Approximately 10-1000 HCM cases and 30-10,000 age/sex-matched controls per institution, depending on size, will be included in the study. We hypothesize that a federated ML model will discriminate cases of HCM from those without HCM in a real-world setting.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients with maximum left ventricular wall thickness exceeding 15 mm (including the right ventricular component of the septum) without any other explanation for ventricular hypertrophy (e.g., severe hypertension, cardiac amyloidosis, severe AS, as determined by local investigators). The measurement could be made in an ECHO or on magnetic resonance imaging (MRI).
- •Patients must have > one (1) ECG and/or > one (1) ECHO available that meet minimum compatibility requirements. If multiple ECGs and ECHOs are available per patient, then all available data meeting compatibility requirements will be used for model training purposes.
- •HCM-Labeled Case
排除标准
- •Any sign of infiltration found in cardiac MRI, if performed.
- •Control Case (Non-HCM) Inclusion Criteria:
- •No diagnosis of HCM
- •Age/sex are matched to HCM cases (+/- 5 years, if possible; +/- 10 years if numbers do not permit).
- •Patient must have > one (1) ECG and/or > one (1) ECHO available that meet minimum compatibility requirements. If multiple ECGs and ECHOs are available per patient, then all available data meeting compatibility requirements will be used for model training purposes.
- •Control Case (Non-HCM) Exclusion Criteria
- •Suggestion of HCM in a clinically obtained ECHO or cardiac MRI report unless subsequently confirmed no diagnosis of HCM. Any new clinical information discovered during the study will be left to the discretion of the local investigator.
结局指标
主要结局
Diagnosis of HCM
时间窗: Through study completion, an average of 2 years
The number/instances of HCM diagnoses as identified by the ML model as compared to clinical diagnosis confirmation. Due to model training and efficacy goals, HCM diagnosis determined clinically via EKG/ECHO reading will be compared to the ML model's capacity to identify HCM correctly and efficiently.
次要结局
- Diagnosis of different types of HCM(Through study completion, an average of 2 years)