Ren Yu, Wei Bin, Song Yanpeng, Guo Heng, Zhang Xianghui, Wang Xinping, Yan Yizhong, Ma Jiaolong, Wang Kui, Keerman Mulatibieke, Zhang Jingyu, Ma Rulin, He Jia, Guo Shuxia
Department of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, People's Republic of China.
Department of Social Work, The First Affiliated Hospital of Shihezi University Medical College, Shihezi, Xinjiang, People's Republic of China.
Int J Gen Med. 2021 Aug 10;14:4317-4325. doi: 10.2147/IJGM.S319605. eCollection 2021.
This cohort study created a risk equation of CVD for the Uyghur and Kazakh ethnic groups with metabolic syndrome (MetS) in Xinjiang and its associated factors, evaluated the model's feasibility, and provided theoretical support for the prevention and early diagnosis of CVD.
A total of 5655 participants from Xinyuan and Jiashi counties in Xinjiang from 2010 to 2012 were selected, including 3770 and 1885 training and validation samples, respectively. A factor analysis was performed on 975 patients with MetS in the training sample, whereas potential factors related to CVD were extracted from 21 MetS biomarkers. Cox regression was used to create and verify a CVD-risk prediction model based on training samples. The receiver operating characteristic curve was drawn to evaluate the model's prediction efficiency.
The cumulative incidence of CVD was 9.20% (training sample, 9.12%; validation sample, 9.36%). Nine potential factors were extracted from the training sample population with MetS to predict the CVD risk: lipid (hazard ratio [HR], 1.205), obesity (HR, 1.047), liver function (HR, 1.042), myocardial enzyme (HR, 1.008), protein (HR, 1.024), blood pressure (HR, 1.027), liver enzyme (HR, 1.012), renal metabolic (HR, 1.015), and blood glucose (HR, 1.010). The area under the curve of the training and validation samples was 0.841 (95% confidence interval [CI], 0.821-0.861) and 0.889 (95% CI, 0.870-0.909), respectively.
The CVD prediction model created with nine potential factors in patients with MetS in Kazakh and Uyghur has a good predictive power.
本队列研究构建了新疆维吾尔族和哈萨克族代谢综合征（MetS）患者心血管疾病（CVD）的风险方程及其相关因素，评估了该模型的可行性，为CVD的预防和早期诊断提供理论支持。
选取2010年至2012年来自新疆新源县和伽师县的5655名参与者，其中分别有3770名和1885名作为训练样本和验证样本。对训练样本中的975名MetS患者进行因子分析，从21种MetS生物标志物中提取与CVD相关的潜在因素。采用Cox回归基于训练样本创建并验证CVD风险预测模型。绘制受试者工作特征曲线以评估模型的预测效率。
CVD的累积发病率为9.
