Analysis of Influencing Factors of Hyperuricemia in Chronic Heart Failure Patients and Model Construction
Objective To investigate the influencing factors of hyperuricemia in patients with chronic heart failure(CHF),and a establish logistic regression model.Methods A total of 100 CHF patients admitted to Nanyang central Hospital from June 2021 to June 2023 were retrospectively selected as the study objects,and were divided into the combined group(42 cases)and the non-combined group(58 cases)according to whether they were complicated with hyperuricemia.The clinical data of the two groups were compared,and the influencing factors of hyperuricemia were analyzed.Two logistic regression models(model 1 and model 2)were established according to the influencing factors,and the differentiation,fit and clinical practical value of the models were evaluated.Results Atrial fibrillation,high-purine diet,monocyte count,high-density lipoprotein cholesterol ratio(MHR),low-density lipoprotein cholesterol(LDL-C),matrix metalloproteinase-9(MMP-9)and malondialdehyde(MDA)were independent risk factors for the development of hyperuricemia,while superoxide dismutase(SOD)and regular exercise were independent protective factors for the development of hyperuricemia(P＜0.05).Atrial fibrillation,high-purine diet,regular exercise,MHR and LDL-C were includeed in model 1,while atrial fibrillation,high-purine diet,MHR,LDL-C,MMP-9,MDA,SOD and regular exercise were includeed in model 2.The area under the curve(AUC)for the diagnosis of hyperuricemia in models 1 and 2 was 0.793 and 0.908,respectively.Model 2 had a good fit with observed values,and when the high-risk threshold was 0.02 to 0.73,the net benefit rate of model 2 had clinical value.Conclusion Atrial fibrillation,high-purine diet,MHR,LDL-C,MMP-9 and MDA are independent risk factors for CHF patients with hyperuricemia,while SOD and regular exercise are independent protective factors.The regression model established based on the above influencing factors has better diagnostic efficacy for hyperuricemia.Clinicians can screen high-risk populations based on the above model and provide intervention measures to reduce the risk of hyperuricemia.
chronic heart failurehyperuricemiainfluencing factordiagnostic value
万方数据
维普
