背景:无症状心房颤动(SAF)很常见,且与不良预后相关。
目的:研究老年(≥65岁)一般人群房颤和SAF的危险因素,建立预测SAF的危险分层模型。
方法:在来自NOMED-AF的队列中,使用基于背心的系统进行长达30天的连续ECG监测,一项基于全国人口样本的横断面研究。采用多因素logistic回归分析房颤和SAF的独立危险因素。ROC分析用于验证开发的风险分层评分。
结果:从3014名受试者的总队列中,在680名个体中诊断出房颤(平均年龄,77.5±7.9;50.1%男性)房颤,and,其中,41%有SAF。房颤风险增加的独立关联是年龄,男性,冠心病,甲状腺疾病,既往缺血性卒中或短暂性脑缺血发作(ICS/TIA),糖尿病,心力衰竭,慢性肾脏病(CKD),肥胖,NT-proBNP>125ng/mL。SAF的危险因素是年龄,男性,ICS/TIA,糖尿病,心力衰竭,CKD,NT-proBNP>125ng/mL。我们开发了临床风险量表(MR-DASH评分),在推导队列(AUC0.726)和验证队列(AUC0.730)中实现了良好的预测水平。
结论:在≥65岁的人群样本中,SAF与各种临床危险因素相关。可以使用MR-DASH评分,根据一般人群的SAF风险对个体进行分层。促进对SAF高风险个体的有针对性的筛查计划。
BACKGROUND: Silent atrial fibrillation (SAF) is common and is associated with poor outcomes.
OBJECTIVE: to study the risk factors for AF and SAF in the elderly (≥65 years) general population and to develop a risk stratification model for predicting SAF.
METHODS: Continuous ECG monitoring was performed for up to 30 days using a vest-based system in a cohort from NOMED-AF, a cross-sectional study based on a nationwide population sample. The independent risk factors for AF and SAF were determined using multiple logistic regression. ROC analysis was applied to validate the developed risk stratification score.
RESULTS: From the total cohort of 3014 subjects, AF was diagnosed in 680 individuals (mean age, 77.5 ± 7.9; 50.1% men) with AF, and, of these, 41% had SAF. Independent associations with an increased risk of AF were age, male gender, coronary heart disease, thyroid diseases, prior ischemic stroke or transient ischemic attack (ICS/TIA), diabetes, heart failure, chronic kidney disease (CKD), obesity, and NT-proBNP >125 ng/mL. The risk factors for SAF were age, male gender, ICS/TIA, diabetes, heart failure, CKD, and NT-proBNP >125 ng/mL. We developed a clinical risk scale (MR-DASH score) that achieved a good level of prediction in the derivation cohort (AUC 0.726) and the validation cohort (AUC 0.730).
CONCLUSIONS: SAF is associated with various clinical risk factors in a population sample of individuals ≥65 years. Stratifying individuals from the general population according to their risk for SAF may be possible using the MR-DASH score, facilitating targeted screening programs of individuals with a high risk of SAF.