NCT07724184招募中不适用
Percutaneous Coronary Intervention of Calcified Lesions and the Use of Artificial Intelligence to Predict Successful Outcome
适应症
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Post-PCI FFR
研究概览
简要总结
The primary aim of this study is to evaluate changes in absolute coronary flow and pressure before and after percutaneous coronary intervention in calcified lesions. The secondary aim is to use a machine learning model to predict the outcome of the intervention.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 90 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age > 18 years
- •Moderate (40-90 %) epicardial disease
- •Vessel suitable for PCI and intracoronary imaging
- •De novo-lesions
排除标准
- •eGFR < 40ml/min
- •ACS < 48 hours
- •Patient without ability to provide informed consent
- •Patient with left main stenosis
- •Indication for coronary artery bypass grafting
结局指标
主要结局
Post-PCI FFR
时间窗: Immediately after the procedure
FFR is measured after PCI is completed.
次要结局
未报告次要终点
研究者
Ashkan Eftekhari
Principal Investigator
Aalborg University Hospital
研究点 (1)
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