Background:The risk prediction of incident atrial fibrillation (AF) is useful to prevent AF and its complications. The aim of this study is to develop a new risk prediction model for incident AF using the prospective longitudinal data from a general Japanese population.

Methods and Results:A total of 2,442 community-dwelling AF-free residents aged ≥40 years were followed up from 1988 to 2012 (46,422 person-years). The development of AF was confirmed by a standard 12-lead electrocardiogram at repeated health examinations and by medical records at clinics or hospitals. The risk prediction model for incident AF was developed using a Cox proportional hazards model. During the follow up, 230 AF events were confirmed. Age, sex, systolic blood pressure, waist circumference, estimated glomerular filtration rate, abnormal cardiac murmur, high R-wave amplitude, and arrhythmia other than AF were selected for inclusion in the model. This model showed good discrimination (Harrell’s c statistics: 0.785) and calibration (Greenwood-Nam-D’Agostino test: P=0.87) for AF risk at 10 years.

Conclusions:The new risk prediction model showed good performance on the individual risk assessment of the future onset of AF in a general Japanese population. As this model included commonly used clinical parameters, it may be useful for determining the requirements for the careful evaluation of AF, such as frequent electrocardiogram examinations in clinical settings, and subsequent reductions in the risk of AF-related complications.

背景：心房颤动 (AF) 的风险预测有助于预防 AF 及其并发症。本研究的目的是利用来自日本一般人群的前瞻性纵向数据，开发一种新的 AF 事件风险预测模型。

方法和结果：从 1988 年到 2012 年，共对 2,442 名年龄≥40 岁的社区无房颤居民（46,422 人年）进行了随访。AF 的发展通过重复健康检查的标准 12 导联心电图和诊所或医院的医疗记录得到证实。AF 事件的风险预测模型是使用 Cox 比例风险模型开发的。在随访期间，确认了 230 起 AF 事件。选择年龄、性别、收缩压、腰围、估计的肾小球滤过率、异常心脏杂音、高 R 波振幅和除 AF 以外的心律失常纳入模型。该模型对 10 年的 AF 风险显示出良好的辨别力（Harrell's c 统计量：0.785）和校准（Greenwood-Nam-D'Agostino 测试：P=0.87）。

结论：新的风险预测模型在日本普通人群中对未来发生 AF 的个体风险评估显示出良好的性能。由于该模型包括常用的临床参数，因此它可能有助于确定仔细评估 AF 的要求，例如在临床环境中频繁进行心电图检查，以及随后降低 AF 相关并发症的风险。