Abstract: Objectives   The risk of cardiac valve calcification (CVC) in patients with maintenance hemodialysis (MHD) was predicted by a nomogram.  Methods   Patients with end-stage kidney disease (ESKD) who received MHD in Nanchong Central Hospital from 2014 to 2022 were included in this study. Basic information, disease information, laboratory and imaging examination data were collected. The risk factors for CVC were analyzed by univariate and multivariate logistic regression analyses, and a nomograph model for predicting the risk of CVC was established using R language software. Bootstrap method was used for the verification. The prediction efficiency of the model was evaluated by the area under the ROC curve, and the accuracy and practicability of the model were evaluated by calibration curve and decision curve analysis (DCA).  Results   A total of 173 MHD patients were included, including 63 CVC patients (36.4%). Multivariate logistic regression analysis showed that age (OR:1.046, 95% CI: 1.016~1.077, P=0.002), serum calcium (OR: 5.181, 95% CI: 1.015~27.252, P=0.042), serum phosphorus (OR:2.401,95% CI:1.177~4.898, P=0.038), diabetes (OR: 2.943, 95% CI: 1.397~6.195, P=0.013) and secondary hyperparathyroidism (OR: 2.844, 95% CI: 1.003~8.082, P=0.041) were the independent risk factors for CVC. The line chart showed good differentiation. The area under ROC curve of the training set was 0.757 (95% CI: 0.735 ~0.763), the internal verification C-index was 0.732, and the area under ROC curve of the test set was 0.700 (95% CI: 0.695~0.714). The calibration curve results show that the actual probability of CVC occurrence was in better agreement with the predicted probability.  Conclusions  The column graph constructed in this study can be used to identify the patient group in high risk of CVC, which may be clinically useful.

Key words: Maintenance hemodialysis, Cardiac valve calcification, Nomogram