Yang Zhao, Zhou Pan, Fan Fangfang, Hao Yiming, Zhao Wenlang, Wang Ziyu, Deng Xuan, Deng Qiuju, Hao Yongchen, Yang Na, Han Lizhen, Jia Pingping, Qi Yue, Zhang Yan, Liu Jing
Center for Clinical and Epidemiologic Research, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, No. 2 Anzhen Road, Chaoyang District, Beijing 100029, China.
Institute of Cardiovascular Disease, Department of Cardiology, Peking University First Hospital, No. 8 Xishiku St, Xicheng District, Beijing 100034, China.
iScience. 2025 May 30;28(7):112780. doi: 10.1016/j.isci.2025.112780. eCollection 2025 Jul 18.
The 2023 American Heart Association (AHA) Health Presidential Advisory recommends risk assessment of cardiovascular disease (CVD) within the context of Cardiovascular-Kidney-Metabolic syndrome (CKMS). However, an intuitive and easy-to-use risk score incorporating CKM health metrics remains needed to prevent CVD in daily practice. We constructed an acronym-based clinical risk score using CKM-related predictors and externally validated its predictive performance for total CVD and its subtypes of atherosclerotic CVD and heart failure, based on two prospective community-based cohorts. We found the Cholesterol, Kidney function, Male [Doubled], Smoker [Doubled]-Blood pressure, Age, and fast blood Glucose (CKMS-BAG) score exhibited good-to-excellent and robust performance regarding discrimination and risk stratification for total CVD and its subtypes in internal and external validation. Using clinical routine data, the CKMS-BAG score accurately discriminates participants at cardiovascular low, intermediate, and high risk. Thus, it might help improve CVD prevention and management in clinical practice without any paper or electronic tools.
2023年美国心脏协会（AHA）健康总统咨询报告建议在心血管-肾脏-代谢综合征（CKMS）背景下对心血管疾病（CVD）进行风险评估。然而，在日常实践中预防CVD仍需要一个直观且易于使用的纳入CKM健康指标的风险评分。我们使用与CKM相关的预测因子构建了一个基于首字母缩写的临床风险评分，并基于两个前瞻性社区队列对外验证了其对总CVD及其动脉粥样硬化性CVD和心力衰竭亚型的预测性能。我们发现，胆固醇、肾功能、男性[翻倍]、吸烟者[翻倍]-血压、年龄和空腹血糖（CKMS-BAG）评分在内部和外部验证中对总CVD及其亚型的鉴别和风险分层表现出良好至优秀且稳健的性能。使用临床常规数据，CKMS-BAG评分能准确区分心血管低、中、高风险的参与者。因此，它可能有助于在无需任何纸质或电子工具的情况下改善临床实践中的CVD预防和管理。
