Int Immunopharmacol
December 2022
Background: Renal damage is one of the typical clinical manifestations of systemic lupus erythematosus (SLE) and few effective markers can be used to predict SLE with renal damage. Additionally, the relationship among AhR, B cells and SLE with renal damage is poorly understood.
Method: A case-control study was performed, and the clinical and laboratory data were acquired from medical records.
Fewer biomarkers can be used to predict systemic lupus erythematosus (SLE) related kidney injury. This paper presents an apriori algorithm of association rules to mine the predictive biomarkers for SLE-related kidney injury of negative proteinuria. An apriori algorithm of association rules was employed to identify biomarkers, and logistic regression analysis and spearman correlation analysis were used to evaluate the correlation between triglycerides and SLE-related kidney injury of negative proteinuria.
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