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中华脑血管病杂志(电子版) ›› 2020, Vol. 14 ›› Issue (03) : 133 -139. doi: 10.11817/j.issn.1673-9248.2020.03.003

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专家论坛

新发心房颤动风险评估的研究进展
李延广1, 祖凌云1, 刘书旺1,()   
  1. 1. 100191 北京大学第三医院心内科、血管医学研究所  国家卫生健康委心血管分子生物学与调节肽重点实验室 分子心血管学教育部重点实验室 心血管受体研究北京市重点实验室
  • 收稿日期:2020-03-02 出版日期:2020-06-01
  • 通信作者: 刘书旺

Advances in risk assessment of new-onset atrial fibrillation

Yanguang Li1, Lingyun Zu1, Shuwang Liu1,()   

  1. 1. Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; NHC Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides; Key Laboratory of Molecular Cardiovascular Science, Ministry of Education; Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
  • Received:2020-03-02 Published:2020-06-01
  • Corresponding author: Shuwang Liu
  • About author:
    Corresponding author: Liu Shuwang, Email:
引用本文:

李延广, 祖凌云, 刘书旺. 新发心房颤动风险评估的研究进展[J]. 中华脑血管病杂志(电子版), 2020, 14(03): 133-139.

Yanguang Li, Lingyun Zu, Shuwang Liu. Advances in risk assessment of new-onset atrial fibrillation[J]. Chinese Journal of Cerebrovascular Diseases(Electronic Edition), 2020, 14(03): 133-139.

心房颤动(房颤)导致脑卒中、心力衰竭、全因死亡、认知功能障碍等风险明显增加。识别导致的房颤危险因素对指导制定一级预防及筛查策略、提前检出无症状房颤、改善临床预后具有重要意义。新发房颤常见临床危险因素包括高龄、性别、吸烟、饮酒、肥胖、阻塞性睡眠呼吸暂停、高血压、冠心病、心力衰竭、甲状腺功能亢进、糖尿病、慢性阻塞性肺病、慢性肾功能不全等。HAVOC评分和C2HEST评分有望成为评估个体新发房颤风险的简易临床型工具。

Atrial fibrillation (AF) increases the risk of ischemic stroke, heart failure, all-cause mortality and cognitive dysfunction. Identifying risk factors for incident AF is pivotal for making strategies for primary prevention, silent AF screening or detection, and improving AF-related clinical prognosis. The most common clinical risk factors for AF include age, male gender, smoking, drinking, obesity, obstructive sleep apnea, hypertension, coronary artery disease, heart failure, hyperthyroidism, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, etc. The novel HAVOC and C2HEST score are the promising and simple clinical risk assessment tools for incident AF.

表1 新发房颤预测模型
评分工具 第一作者 来源队列 研究对象数量 C值a 所含变量
Framingham Schnabel RB[39] FHS队列(美国) 4764 0.78(0.76~0.80) 年龄、性别、心脏杂音、心力衰竭、收缩压、高血压、体质量指数、PR间期
CHARGE-AF Alonso A[21] ARIC、CHS、FHS队列(美国) 18 556 0.77(0.75~0.78) 年龄、种族、身高、体质量、血压、吸烟、降压药物、糖尿病、心肌梗死、心力衰竭
ARIC Chamberlain AM[40] ARIC队列(美国) 14 546 0.78(N/A) 年龄、种族、身高、吸烟、收缩压、降压药物、心脏杂音、左心室肥厚、左心房扩张、糖尿病、冠心病、心力衰竭
C2HEST Li YG[43] 云南医保数据库(中国)、韩国医保数据库(韩国) 471 446和451 199 0.75(0.73~0.77) 冠心病、慢性阻塞性肺病、高血压、高龄、心力衰竭、甲状腺功能亢进
HAVOC Kwong C[42] STRIDE数据库(美国) 9689 0.77(N/A) 高血压、年龄、瓣膜性心脏病、外周血管病、肥胖、心力衰竭、冠心病
CHASE-LESS Hsieh CY[44] 台湾数据库 17 076 0.73(0.71~0.75) 冠心病、年龄、心力衰竭、卒中严重程度、高脂血症、既往卒中或短暂性脑缺血发作
EHR Hulme OL[41] 多中心电子病历数据库(美国) 412 085 0.78(0.77~0.78) 性别、年龄、种族、吸烟、身高、体质量、舒张压、高血压、高脂血症、心力衰竭、冠心病、瓣膜病、卒中、外周动脉疾病、慢性肾病、甲状腺功能减低
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