Department of Cardiology, Rambam Medical Center, Haifa, Israel.
Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
Thromb Haemost. 2018 Sep;118(9):1556-1563. doi: 10.1055/s-0038-1668522. Epub 2018 Aug 13.
We used a large real-world data from community settings to develop and validate a 10-year risk score for new-onset atrial fibrillation (AF) and calculate its net benefit performance.
Multivariable Cox proportional hazards model was used to estimate effects of risk factors in the derivation cohort ( = 96,778) and to derive a risk equation. Measures of calibration and discrimination were calculated in the validation cohort ( = 48,404).
Cumulative AF incidence rates for both the derivation and validation cohorts were 5.8% at 10 years. The final models included the following variables: age, sex, body mass index, history of treated hypertension, systolic blood pressure ≥ 160 mm Hg, chronic lung disease, history of myocardial infarction, history of peripheral arterial disease, heart failure and history of an inflammatory disease. There was a 27-fold difference (1.0% vs. 27.2%) in AF risk between the lowest (-1) and the highest (9) sum score. The -statistic was 0.743 (95% confidence interval [CI], 0.737-0.749) for the derivation cohort and 0.749 (95% CI, 0.741-0.759) in the validation cohort. The risk equation was well calibrated, with predicted risks closely matching observed risks. Decision curve analysis displayed consistent positive net benefit of using the AF risk score for decision thresholds between 1 and 25% 10-year AF risk.
We provide a simple score for the prediction of 10-year risk for AF. The score can be used to select patients at highest risk for treatments of modifiable risk factors, monitoring for sub-clinical AF detection or for clinical trials of primary prevention of AF.
我们利用来自社区环境的大型真实世界数据，开发并验证了一种用于新发心房颤动 (AF) 的 10 年风险评分，并计算了其净获益表现。
多变量 Cox 比例风险模型用于估计推导队列（=96778）中风险因素的影响，并推导出风险方程。在验证队列（=48404）中计算了校准和区分度的度量。
推导和验证队列的累积 AF 发生率均为 10 年时为 5.8%。最终模型包括以下变量：年龄、性别、体重指数、治疗高血压史、收缩压≥160mmHg、慢性肺部疾病、心肌梗死史、外周动脉疾病史、心力衰竭和炎症性疾病史。在最低 (-1) 和最高 (9) 总分之间，AF 风险差异有 27 倍（1.0% vs. 27.2%）。推导队列的 -统计量为 0.743（95%置信区间 [CI]，0.737-0.749），验证队列为 0.749（95% CI，0.741-0.759）。风险方程具有良好的校准度，预测风险与观察到的风险密切匹配。决策曲线分析显示，在 10 年 AF 风险 1%至 25%的决策阈值下，使用 AF 风险评分具有一致的净获益。
我们提供了一种用于预测 10 年 AF 风险的简单评分。该评分可用于选择风险最高的患者，以进行可改变的风险因素治疗、监测亚临床 AF 检测或进行 AF 一级预防的临床试验。
