Xu Xin, Shao Xian, Hou Fan Fan
National Clinical Research Center for Kidney Disease, State Key Laboratory of Multi-organ Injury Prevention and Treatment, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
National Clinical Research Center for Kidney Disease, State Key Laboratory of Multi-organ Injury Prevention and Treatment, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Kidney Int. 2025 Jun;107(6):1002-1010. doi: 10.1016/j.kint.2025.01.041. Epub 2025 Mar 27.
During the last 20 years, the disease burden attributable to metabolic disorders increased by 49.4%. Metabolic disorders are established risk factors for both chronic kidney disease (CKD) and cardiovascular disease (CVD). A concept of cardiovascular-kidney-metabolic (CKM) syndrome has recently been proposed to underscore the pathophysiological interrelatedness of the metabolic risk factors, CKD, and CVD. Two major adverse outcomes of the metabolic disorder-associated kidney disease are cardiovascular disease and, to a less extent, kidney failure. This review aims to briefly summarize the traditional metabolic risk factors for kidney disease; to introduce the concept of CKM health; to present the methods for risk assessment for CKD progression and CVD, with focus on validated and clinically applicable prediction tools; and to discuss the key gaps in the current tools for the risk stratification. In summary, in general clinical settings, the CKM health and associated risk in patients with the metabolic disorder-associated kidney disease can be assessed by combining the CKM staging model, the CKD Prognosis Consortium equations for CKD progression, and the Predicting Risk of CVD Events (PREVENT) equations for CVD. More efficient risk prediction tools, potentially incorporating multimodal data, are needed for more accurate and early identification of individuals at high risk and better personalized management of the disease.
在过去20年中，代谢紊乱所致的疾病负担增加了49.4%。代谢紊乱是慢性肾脏病（CKD）和心血管疾病（CVD）公认的危险因素。最近有人提出了心血管-肾脏-代谢（CKM）综合征的概念，以强调代谢危险因素、CKD和CVD之间的病理生理相关性。代谢紊乱相关肾脏病的两个主要不良后果是心血管疾病，以及程度较轻的肾衰竭。本综述旨在简要总结肾脏病的传统代谢危险因素；介绍CKM健康的概念；介绍CKD进展和CVD风险评估方法，重点关注经过验证且临床适用的预测工具；并讨论当前风险分层工具中的关键差距。总之，在一般临床环境中，代谢紊乱相关肾脏病患者的CKM健康状况及相关风险可通过结合CKM分期模型、CKD进展的CKD预后联盟方程以及CVD的心血管疾病事件预测（PREVENT）方程来评估。为了更准确、早期地识别高危个体并实现更好的疾病个体化管理，需要更有效的风险预测工具，可能需要纳入多模态数据。
