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优化房颤易感性和负荷指标,以评估房颤严重程度、风险和结局。

Optimizing indices of atrial fibrillation susceptibility and burden to evaluate atrial fibrillation severity, risk and outcomes.

机构信息

Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, Via del Pozzo, 71, 41124 Modena, Italy.

Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, UK.

出版信息

Cardiovasc Res. 2021 Jun 16;117(7):1-21. doi: 10.1093/cvr/cvab147.

Abstract

Atrial fibrillation (AF) has heterogeneous patterns of presentation concerning symptoms, duration of episodes, AF burden, and the tendency to progress towards the terminal step of permanent AF. AF is associated with a risk of stroke/thromboembolism traditionally considered dependent on patient-level risk factors rather than AF type, AF burden, or other characterizations. However, the time spent in AF appears related to an incremental risk of stroke, as suggested by the higher risk of stroke in patients with clinical AF vs. subclinical episodes and in patients with non-paroxysmal AF vs. paroxysmal AF. In patients with device-detected atrial tachyarrhythmias, AF burden is a dynamic process with potential transitions from a lower to a higher maximum daily arrhythmia burden, thus justifying monitoring its temporal evolution. In clinical terms, the appearance of the first episode of AF, the characterization of the arrhythmia in a specific AF type, the progression of AF, and the response to rhythm control therapies, as well as the clinical outcomes, are all conditioned by underlying heart disease, risk factors, and comorbidities. Improved understanding is needed on how to monitor and modulate the effect of factors that condition AF susceptibility and modulate AF-associated outcomes. The increasing use of wearables and apps in practice and clinical research may be useful to predict and quantify AF burden and assess AF susceptibility at the individual patient level. This may help us reveal why AF stops and starts again, or why AF episodes, or burden, cluster. Additionally, whether the distribution of burden is associated with variations in the propensity to thrombosis or other clinical adverse events. Combining the improved methods for data analysis, clinical and translational science could be the basis for the early identification of the subset of patients at risk of progressing to a longer duration/higher burden of AF and the associated adverse outcomes.

摘要

心房颤动 (AF) 在症状、发作持续时间、AF 负荷和向永久性 AF 终末阶段进展的趋势方面表现出异质性。AF 与中风/血栓栓塞风险相关,传统上认为该风险取决于患者的个体风险因素,而不是 AF 类型、AF 负荷或其他特征。然而,AF 发作时间似乎与中风风险的增加有关,如临床 AF 患者比亚临床发作患者以及非阵发性 AF 患者比阵发性 AF 患者的中风风险更高所表明的那样。在具有设备检测到的房性心律失常的患者中,AF 负荷是一个动态过程,可能从较低的最大每日心律失常负荷向较高的负荷过渡,因此有理由监测其时间演变。从临床角度来看,首次 AF 发作的出现、特定 AF 类型的心律失常特征、AF 的进展以及节律控制治疗的反应以及临床结果,都受到潜在心脏病、风险因素和合并症的影响。需要更好地了解如何监测和调节影响 AF 易感性和调节 AF 相关结果的因素的作用。在实践和临床研究中越来越多地使用可穿戴设备和应用程序可能有助于预测和量化 AF 负荷,并在个体患者水平评估 AF 易感性。这可能有助于我们揭示为什么 AF 会停止和再次开始,或者为什么 AF 发作或负荷会聚集。此外,负荷的分布是否与血栓形成倾向或其他临床不良事件的变化有关。将改进的数据分析方法、临床和转化科学结合起来,可能是早期识别处于进展为 AF 持续时间更长/负荷更高风险的患者亚组以及相关不良结局风险的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e89/8707734/f73aef22ea5d/cvab147f4.jpg

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