首页 | 本学科首页   官方微博 | 高级检索  
检索        


A simple and easily implemented risk model to predict 1-year ischemic stroke and systemic embolism in Chinese patients with atrial fibrillation
Authors:Chao Jiang  Tian-Ge Chen  Xin Du  Xiang Li  Liu He  Yi-Wei Lai  Shi-Jun Xia  Rong Liu  Yi-Ying Hu  Ying-Xue Li  Chen-Xi Jiang  Nian Liu  Ri-Bo Tang  Rong Bai  Cai-Hua Sang  De-Yong Long  Guo-Tong Xie  Jian-Zeng Dong  Chang-Sheng Ma
Institution:1.Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Center for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing 100029, China;2.Ping An Health Technology, Beijing 100035, China;3.Heart Health Research Center, Beijing 100029, China;4.Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
Abstract:Background:Accurate prediction of ischemic stroke is required for deciding anticoagulation use in patients with atrial fibrillation (AF). Even though only 6% to 8% of AF patients die from stroke, about 90% are indicated for anticoagulants according to the current AF management guidelines. Therefore, we aimed to develop an accurate and easy-to-use new risk model for 1-year thromboembolic events (TEs) in Chinese AF patients.Methods:From the prospective China Atrial Fibrillation Registry cohort study, we identified 6601 AF patients who were not treated with anticoagulation or ablation at baseline. We selected the most important variables by the extreme gradient boosting (XGBoost) algorithm and developed a simplified risk model for predicting 1-year TEs. The novel risk score was internally validated using bootstrapping with 1000 replicates and compared with the CHA2DS2-VA score (excluding female sex from the CHA2DS2-VASc score).Results:Up to the follow-up of 1 year, 163 TEs (ischemic stroke or systemic embolism) occurred. Using the XGBoost algorithm, we selected the three most important variables (congestive heart failure or left ventricular dysfunction, age, and prior stroke, abbreviated as CAS model) to predict 1-year TE risk. We trained a multivariate Cox regression model and assigned point scores proportional to model coefficients. The CAS scheme classified 30.8% (2033/6601) of the patients as low risk for TE (CAS score = 0), with a corresponding 1-year TE risk of 0.81% (95% confidence interval CI]: 0.41%–1.19%). In our cohort, the C-statistic of CAS model was 0.69 (95% CI: 0.65–0.73), higher than that of CHA2DS2-VA score (0.66, 95% CI: 0.62–0.70, Z = 2.01, P = 0.045). The overall net reclassification improvement from CHA2DS2-VA categories (low = 0/high ≥1) to CAS categories (low = 0/high ≥1) was 12.2% (95% CI: 8.7%–15.7%).Conclusion:In Chinese AF patients, a novel and simple CAS risk model better predicted 1-year TEs than the widely-used CHA2DS2-VA risk score and identified a large proportion of patients with low risk of TEs, which could potentially improve anticoagulation decision-making.Trial Registration:www.chictr.org.cn (Unique identifier No. ChiCTR-OCH-13003729).
Keywords:Atrial fibrillation  Stroke  Risk prediction  CHA2DS2-VA  CHA2DS2-VASc
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号