Objective  To explore the influencing factors of peritoneal dialysis-associated peritonitis (PDAP) and establish a nomogram model for predicting the risks of PDAP.

Methods  From January 2016 to December 2021, clinical data were retrospectively reviewed for 297 peritoneal dialysis (PD) patients followed up regularly. According to whether or not PDAP occurred after PD, they were assigned into non-peritonitis group (n=170) and peritonitis group (n=82, 97 bouts of peritonitis). Logistic regression analysis was utilized for comparing the clinical data of two groups. Univariate variables with statistically significant differences were included into multivariate Logistic regression model. And stepwise regression analysis was utilized for examining the influencing factors of PDAP. R language was employed for establishing a nomogram model to predict the risks of PDAP. The area under the receiver operating characteristic (ROC) curve and P value of Hosmer-Lemeshow test were utilized for evaluating the discrimination and calibration of the model.

Results  Multivariate Logistic regression analysis indicated that higher alkaline phosphatase (OR=1.006, 95%CI:1.001-1.011, P<0.05), lower albumin (OR=0.907, 95%CI:0.847-0.972, P<0.01), higher neutrophil-to-lymphocyte ratio (OR=1.327, 95%CI:1.162-1.515, P<0.001) and higher ferritin (OR=1.003, 95%CI:1.001-1.004, P<0.001) were independent risk factors for PDAP. The area under the ROC curve (AUC) of risk prediction model was 0.811 (95%CI:0.755-0.867, P<0.001). The result of Hosmer-Lemeshow test was χ²=2.336 (P=0.969).

Conclusions  The prediction model of PDAP has been established based upon alkaline phosphatase, albumin, neutrophil-to-lymphocyte ratio and ferritin. It has satisfactory discrimination accuracy. Such a model may effectively evaluate the risks of peritonitis in PD patients.