高尿酸血症的列线图模型建立

Developing the nomogram model for hyperuricemia

目的:探究大样本体检人群的高尿酸血症危险因素列线图模型,为控制心脑血管疾病提供依据。方法:选择2014~2016年安徽省某医院健康体检人群298 955例,收集人口学特征、体格检查和实验室检查结果,分析高尿酸血症的主要危险因素并构建列线图模型。结果:多因素logistic逐步回归模型分析显示,Age、HDL-C、AST、LDL、Smoke为高尿酸血症的保护因素,而Sex、BMI、TC、Cre、BUN、ALT、Tbil、HTN、Drink为危险因素。根据多因素分析结果建立高尿酸血症危险因素列线图模型,Cindex为0.773。结论:建立了本地区高尿酸血症的主要危险因素模型,并以此构建高尿酸血症危险因素列线图模型,风险评估效果较好。

Objective: To develop the nomogram model for risk factors of hyperuricemia in large population samples for evidence to control cardio-cerebrovascular diseases. Methods: A total of 298 955 health subjects undergoing physical examination in a hospital in Anhui province were enrolled from 2014 and 2016.The data on demographic characteristics,general check-up findings and laboratory results were included and analyzed to develop the nomogram model for major risk factors of hyperuricemia. Results: Multivariate logistic regression analysis showed that hyperuricemia was positively correlated with the age,levels of HDL-C,AST and LDL as well as smoke,and the gender,levels of BMI,TC,Cre,BUN,ALT,Tbil and HBP as well as drink were risks for hyperuricemia.A nomogram was established on the basis of the parameters described above,with C-index of 0.773. Conclusion: A nomogram model of risk factors for hyperuricemia was successfully established,leading to better risk assessment of hyperuicemia in population.