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Established the first clinical prediction model regarding the risk of hyperuricemia in IgA nephropathy
[post]
2021
unpublished
Objective. To construct a novel nomogram model that predicts the risk of hyperuricemia incidence in IgA nephropathy (IgAN) . Methods. Demographic and clinicopathological characteristics of 1184 IgAN patients in the First Affiliated Hospital of Zhengzhou University Hospital were collected. Univariate analysis and multivariate logistic regression were used to screen out hyperuricemia risk factors. The risk factors were used to establish a predictive nomogram model. The performance of the nomogram
doi:10.21203/rs.3.rs-888732/v1
fatcat:4mfdrvax2ndhjiafvcxkewinry