关键词:

超重及肥胖, 高尿酸血症, 分类树模型, 列线图模型, 预测模型, ROC 曲线, DCA 曲线, CIC 曲线

Abstract:

Objective To construct and evaluate the hyperuricemia prediction model for overweight and obese people. Methods A retrospective study was conducted to collect 5 098 overweight and obese people as research subjects. Among of them，3 582（70%）were randomly selected to form the modeling group，and the rest 1 516（30%）as the internal validationgroup. The subjects in the modeling group and internal validation group were divided into case group and control group according to the presence or absence of hyperuricemia（serum uric acid ≥ 420 μmol/L）. The case group and control group were compared in terms of clinical metabolic features and classifi⁃ cation tree and nomogram models were constructed. Finally，ROC curve，DCA curve and CIC curve were used to compare the two prediction models and analyze their clinical practicability. Results The classification tree and nomogram models of training set and validation set showed that male，Cr，TG，age，HDL⁃c，LDL⁃c were the influ⁃ encing factors of hyperuricemia among the overweight and obese people. The ROC curve of the two models in the two groups indicated moderate predictive value. The risk probability of DCA curve was in the range of 0.1 ~ 0.7，and the net benefit rate of the two models was higher than 0. The CIC curve indicated that the two models had certain clinical impact value. Conclusion The influencing factors predicted from the classification tree and nomogram models are male，Cr，TG，age，HDL⁃c and LDL⁃c，and both models are ofsome value for prediction and clinical practicability.

Key words:

overweight and obesity, hyperuricemia, classification tree model, nomogram model, prediction model, ROC curve, DCA curve, CIC curve