人工智能增强的心电图透功能等级预测了高性心肌病症中隔膜切除后的死亡率
Julia G Debertin1, Hartzell V Schaff1, Tedy Sawma1
1Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minn.
The Journal of thoracic and cardiovascular surgery
|May 30, 2025
概括
人工智能启用心电图 (AI-ECG) 可以评估心肌缩心脏病患者的舒张功能. 较高的AI-ECG透析等级预测更糟糕的结果,包括更长的住院时间和隔膜肌切除术后死亡风险增加.
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:
- 扩张性功能障碍是高性心肌病 (HCM) 的关键特征,通常难以非侵入性评估.
- 接受隔膜肌切除术的阻塞性HCM (oHCM) 患者可能具有具有挑战性的术后结果.
研究的目的:
- 为了研究AI-ECG确定的透缩功能等级和oHCM患者的术后结果之间的关联.
- 为了评估AI-ECG透析等级与心声回声测量和长期死亡率的相关性.
主要方法:
- 分析了1953年接受过门隔膜肌切除术的患者.
- 基于通过经过验证的深度学习人工智能算法在手术前心电图上确定的透气功能等级来分层结果.
- 评估早期术后发病率,住院时间和全因死亡率.
主要成果:
- 较高的AI-ECG透析等级 (2和3) 与增加的并发症和较差的心声学参数相关.
- 具有较高等级的患者面临晚期死亡风险增加 (HR 1.73-2.45) 和手术后心房动 (AF).
- 扩张力3级与更长的住院时间 (+0.87天) 和更高的术后肌肉前膜炎 (OR 1.63) 的可能性有关.
结论:
- 较高的AI-ECG透析度与术后AF风险增加,住院时间延长和长期存活率降低有关.
- 人工智能-心电图 (AI-ECG) 扩张分级显示,它有可能成为接受隔膜肌切除术的oHCM患者风险分层的有价值工具.
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