Assessing the Efficacy of Artificial Intelligence in Left Ventricular Function Screening Using Parasternal Long Axis View Cardiac Ultrasound Video Clips
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 923
- 试验地点
- 2
- 主要终点
- efficiency of AI in screening left ventricular cardiac function by use smartphone application
研究概览
简要总结
Assessing the Efficacy of Artificial Intelligence in Left Ventricular Function Screening Using Parasternal Long Axis View Cardiac Ultrasound Video Clips
ABSTRACT BACKGROUND: Echocardiography serves as a fundamental diagnostic procedure for managing heart failure patients. Data from Thailand's Ministry of Public Health reveals that there is a substantial patient population, with over 100,000 admissions annually due to this condition. Nevertheless, the widespread implementation of echocardiography in this patient group remains challenging, primarily due to limitations in specialist resources, particularly in rural community hospitals. Although modern community hospitals are equipped with ultrasound machines capable of basic cardiac assessment (e.g., parasternal long axis view), the demand for expert cardiologists remains a formidable obstacle to achieving comprehensive diagnostic capabilities. Leveraging the capabilities of Artificial Intelligence (AI) technology, proficient in the accurate prediction and processing of diverse healthcare data types, offers a promising for addressing this prevailing issue. This study is designed to assess the effectiveness of AI in evaluating cardiac performance from parasternal long axis view ultrasound video clips obtained via the smartphone application.
OBJECTIVES: To evaluate the effectiveness of artificial intelligence in screening cardiac function from parasternal long axis view cardiac ultrasound video clips obtained through the smartphone application.
详细描述
METHODS: The investigators built the smartphone application to collect parasternal long axis view video clips and used artificial intelligence "Easy EF" to evaluate cardiac function. All samples that were evaluated for LVEF by certified cardiologists, 70% of all clips were used to train AI, while the remaining 30% of clips were used to test if AI could process the results correctly. Artificial intelligence aims to classify cardiac function into three groups: Reduced EF, Mildly Reduced EF, and Preserved LV.
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
- Single (Outcomes Assessor)
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Shot 5 second VDO clip of Parasternal long axis heart ultrasound recorded by smartphone Application "Easy EF" without patient identification with result of Ejection fraction that performed by certify cardiologist approved result
排除标准
- •Incomplete VDO clip (too much shaking, too shot recording)
- •Lighting was inappropriate
- •Inappropriate ultrasound framing
- •arrhythmia (atrial fibrillation)
结局指标
主要结局
efficiency of AI in screening left ventricular cardiac function by use smartphone application
时间窗: 3 month
percentage of correct LV function clip that interpreted by AI in each LV function group(Preserved LV, Mildly reduced LV, Reduced LV function) and overall compare with result from certified cardiologist
次要结局
未报告次要终点
研究者
Sittiluck Wongwantanee
Principal Investigator
Rayong Hospital