人工智能启用心电图 (AI-ECG) 不能预测心房动在圆孔关闭后
Omar Baqal1,2, Eiad A Habib1,2, Elfatih A Hasabo3,4
1Department of Internal Medicine, Mayo Clinic, Phoenix, AZ, USA.
International journal of cardiology. Heart & vasculature
|February 21, 2024
概括
人工智能支持的心电图 (AI-ECG) 没有预测心房动 (AF) 专利圆孔 (PFO) 关闭后. 需要进一步的研究来评估AI-ECG.
科学领域:
- 心脏病学 心脏病学
- 医疗技术 医疗技术 医学技术
- 人工智能的人工智能
背景情况:
- 前庭动 (AF) 是一种已知的并发症,后专利卵巢 (PFO) 关闭.
- 人工智能支持的心电图 (AI-ECG) 可以识别高风险的AF特征.
- 该研究调查了AI-ECG在预测AF后PFO关闭中的作用.
研究的目的:
- 评估AI-ECG在PFO关闭后对AF发展的预测价值.
- 确定与PFO关闭后相关的临床和程序因素 AF.
主要方法:
- 对93名接受PFO关闭的患者的回顾性分析 (2011年1月至2022年12月).
- 记录了AI-ECG概率 (Mayo Clinic仪表板) 和临床数据.
- 在AI-ECG上,AF被定义为≥11%的值;使用PASCAL分类.
主要成果:
- 22%的患者在手术后出现过敏性AF,大多是在第一个月内.
- AI-ECG并没有显著区分发育AF的患者和没有发育AF的患者 (30%对27%,p=0.8).
- 在"可能"的帕斯卡组中,PFO关闭用于二次中风预防的患者具有更高的AF风险 (p=0.034).
结论:
- 在本研究中,AI-ECG并没有准确地预测AF开发后PFO关闭.
- 它在PFO关闭等程序设置中的实用性需要进一步调查.
- 帕斯卡分类可以提供关于PFO关闭后AF风险分层的见解.
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