Abstract: Objective To construct a nomogram prediction model of the risk of dialysis complicated with restless legs syndrome (RLS) and conduct external verification. Methods A total of 524 dialysis patients were collected as the modeling group, and a nomogram prediction model of the risk of RLS complicated by dialysis was constructed. In addition, 101 dialysis patients were collected as the verification group for external verification of the model. Both groups were divided into concurrent group and non-concurrent group according to whether concurrent RLS. Results The complication rate of RLS in dialysis patients was 11.64% in the modeling group. Compared with the uncomplicated group, the proportion of diabetes history, cerebral infarction history, dialysis age and parathyroid hormone (PTH) levels were higher in the complicated group (P＜0.05), and hemoglobin (Hb) and serum iron were lower (P＜0.05). Multivariate Logistic regression analysis showed that diabetes history, cerebral infarction history, dialysis age≥48 months, PTH ≥500 ng/L and Hb＜100 g/L were independent risk factors for dialysis complicated by RLS in the modeling group. Based on this, the risk nomogram prediction model of dialysis concurrent RLS was verified by Bootstrap internal verification. The H-L test showed that χ2=7.541 (P=0.563). The calibration curve fited well. The area under the ROC curve (AUC) and the C-index both were 0.842 (95%CI: 0.787 - 0.896). The external verification results showed that the predicted probability of the calibration curve was in good agreement with the actual probability, and the AUC was 0.854 (95%CI: 0.738 - 0.969). Conclusion The constructed risk nomogram prediction model of dialysis concurrent RLS has good calibration and discrimination.

Key words: dialysis, restless legs syndrome, nomogram, risk, predictive model