Liu JunFei, Qian XiaoPing, Wang TaoXia, Liu XiaoLi, Liu WeiGang, Wang LiJie, Zhang HuiFang, Han Li, Li GuiYing, Yu XiaoJuan
Affiliated Hospital of Hebei University of Engineering, Department of Nephrology, The Key Laboratory of Basic Research on Blood Purification Application in Hebei Province, Handan City, Hebei Province, China.
Affiliated Hospital of Hebei University of Engineering, Department of Nutrition, Handan City, Hebei Province, China.
J Med Biochem. 2025 Jul 4;44(4):801-807. doi: 10.5937/jomb0-56221.
Among individuals with diabetes mellitus, diabetic nephropathy (DN) is a common microvascular complication. As renal dysfunction progresses in DN patients, the risk of cardiovascular disease (CVD) significantly increases. The current effective treatment of DN and CVD demands identifying and managing their risk factors.
Patients diagnosed with DN from October 2022 to October 2023 were selected for cross-sectional study and divided into DN group (n=58) and DN/CVD group (n=40) based on the presence of CVD. Univariate analysis was conducted using clinical data, and statistically significant independent variables were analysed through multivariate Logistic regression to identify independent factors influencing CVD in DN patients. A regression model was developed to examine the non-linear relationship between C1q, UA, CRP, and the risk of CVD. The receiver operating characteristic curve was used to analyse the predictive efficacy of the indicators.
When elevated, UA and C1q were independent factors for CVD. A linear relationship existed between UA and C1q and the risk of CVD in DN patients. C1q showed better predictive performance.
As UA and C1q levels rise, the risk of CVD in DN patients significantly increases. In DN patients, UA and C1q are associated with CVD development and progression, offering some supportive evaluation value for the patient's condition.
在糖尿病患者中，糖尿病肾病（DN）是一种常见的微血管并发症。随着DN患者肾功能障碍的进展，心血管疾病（CVD）的风险显著增加。目前对DN和CVD的有效治疗需要识别和管理其危险因素。
选取2022年10月至2023年10月诊断为DN的患者进行横断面研究，并根据是否存在CVD分为DN组（n = 58）和DN/CVD组（n = 40）。使用临床数据进行单因素分析，并通过多因素Logistic回归分析具有统计学意义的独立变量，以确定影响DN患者CVD的独立因素。建立回归模型以检验C1q、尿酸（UA）、C反应蛋白（CRP）与CVD风险之间的非线性关系。采用受试者工作特征曲线分析各指标的预测效能。
UA和C1q升高时是CVD的独立因素。DN患者中UA和C1q与CVD风险之间存在线性关系。C1q显示出更好的预测性能。
随着UA和C1q水平升高，DN患者发生CVD的风险显著增加。在DN患者中，UA和C1q与CVD的发生和进展相关，对患者病情具有一定的支持性评估价值。
