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在 atrial fibrillation 移除后的患者中,来自智能手机应用程序的持续症状集群:来自隔离研究的数据
Emma Sandgren1, Konstanze Betz2, Monika Gawalko3
1Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Centre, Maastricht, the Netherlands; Department of Clinical Sciences, Danderyd University Hospital, Karolinska Institutet, Stockholm, Sweden.
JACC. Clinical electrophysiology
|January 15, 2026
概括
一半的患者经历心房动 (AF) 除后的持续症状. 集群分析确定了五种不同的AF亚现象,有助于个性化管理策略,以改善患者的治疗结果.
科学领域:
- 心脏病学 心脏病学
- 数字健康数字健康
- 数据科学数据科学数据科学
背景情况:
- 心房动 (AF) 呈现异质,虽然切除减轻了症状负担,但持续的症状是常见的术后症状,无论AF复发.
- 识别患有持续症状的不同患者群体对于优化剥离后护理至关重要.
研究的目的:
- 进行集群分析,以根据AF切除后的持续症状定义临床相关的AF亚型.
- 评估这些亚表型与临床特征之间的关联,包括AF复发.
主要方法:
- 经过AF切除术的症状患者使用智能手机应用程序同时监测症状和光多心电图心律.
- 对313名患者 (51%) 的7个类别症状变量进行了两步集群分析,在3个月的随访中报告了症状.
主要成果:
- 确定了五个症状集群:未指明的症状 (17%),有稀有症状的AF (30%),心 (15%),伴随伴发病的疲劳 (20%) 和有严重症状的鼻节律 (19%).
- 在症状频率/模式,AF复发,AF负荷,AF模式,症状与节律相关性,年龄,N终端B型亲尿素水平,CHA2DS2-VA得分和左心房体积指数中观察到群集之间存在显著差异.
结论:
- 一半的患者报告AF移除后持续的症状,形成5个不同的亚型.
- 这些亚型表现出独特的临床特征,生物标志物水平和AF复发模式.
- 数字健康工具赋予症状集群识别的权力,可以促进个性化AF管理切除后.
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