在Takotsubo心肌病患者中,人工智能启用心电图的预测价值
Yoshihisa Kanaji1,2, Ilke Ozcan1, David N Tryon1
1Department of Cardiovascular Medicine Mayo Clinic Rochester MN USA.
Journal of the American Heart Association
|February 23, 2024
概括
人工智能增强的心电图 (AI-ECG) 算法可以预测Takotsubo心肌病 (TC) 患者的主要不良心血管事件. 该工具有助于识别高风险个体,以更好地管理患者.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 塔科苏博心肌病 (TC) 患者面临重大心血管不良事件的高风险.
- 目前,TC中缺乏一个有效的风险分层工具.
- 这项研究调查了AI-ECG算法在TC的预后效用.
研究的目的:
- 评估AI-ECG算法对TC患者不良结果的预测价值.
- 为了确定AI-ECG的发现是否可以改善风险分层超越传统因素.
- 探索AI在识别与TC预后相关的微妙心电图模式方面的潜力.
主要方法:
- 来自梅奥诊所Takotsubo综合征登记册的连续患者的分析.
- 应用验证的AI-ECG算法来估计心电图年龄,低射出分数概率和心房动概率.
- 构建多变量模型,包括考克斯比例危险分析,以评估AI-ECG与重大心脏不良事件 (MACE) 的关联.
主要成果:
- 分析了305名TC患者,平均随访时间为4.8年.
- 高风险的AI-ECG发现与MACE的增加有关.
- 在调整为传统风险因素后,有2或3个高风险AI-ECG发现的存在显著预测了MACE (HR,4.419;P=0.001).
结论:
- 人工智能-ECG算法可以检测与TC中较差的结果相关的微妙的ECG模式.
- 这种AI-ECG方法对分层高风险TC患者有很大的希望.
- 将AI-ECG整合到临床实践中可能会改善TC患者的治疗和治疗结果.
更多相关视频
18:11A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
Published on: December 28, 2012
24.3K
06:16Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
408
相关概念视频
01:29Electrocardiogram
2.3K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
2.3K
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
156
Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
156