Objective To investigate the influencing factors of renal anemia in non-dialysis chronic kidney disease (CKD) patients, and to establish a risk model of renal anemia in non-dialysis CKD patients and verify its validity.

Methods The clinical data of non-dialysis CKD patients admitted from January 2017 to December 2021 were retrospectively analyzed. The patients were randomly divided into training set (n=388) and validation set (n=165) at a ratio of 7∶3. Univariate and multivariate Logistic regression analysis was used to screen out the influencing factors for renal anemia. Based on the minimum Akaike Information Criterion (AIC) criterion, the final predictors were selected to construct the nomogram, and the efficiency of the model was verified.

Results Multivariate Logistic regression analysis showed that 17 variables including white blood cell, percentage of neutrophil granulocyte, erythrocyte distribution width (RDW), thrombocytocrit, alkaline phosphatase, serum albumin (ALB), cystatin C, urea, CKD stage, bicarbonate, potassium, calcium, phosphorus, C-reactive protein (CRP), triglyceride, urinary albumin, occult urine were associated with anemia(P < 0.05). Multiple Logistic regression analysis showed that white blood cell count, CRP, RDW, ALB, cystatin C, urea, CKD stage, bicarbonate and blood calcium were independent influencing factors for anemia (P < 0.05). Using risk factors to construct a nomogram, the validation model had good discrimination the area under ROC curve (AUC) of the training set was 0.915(95%CI, 0.870 to 0.959), and the validation set was 0.949(95%CI, 0.927 to 0.971). The calibration curve and H-L test showed that there was no significant difference between the predicted value and the actual value of the model(P>0.05). The clinical decision curve analysis (DCA) showed that the model had good clinical application value.

Conclusion The model developed in this study can better predict the risk of renal anemia in non-dialysis CKD patients, and provide reference for clinical decision-making.