Objective: To investigate the risk factors for peritonitis in peritoneal dialysis patients and to develop and validate a predictive model.
Methods: A total of 219 patients undergoing continuous ambulatory peritoneal dialysis (CAPD) who had their first peritoneal dialysis catheter placement and regular follow-up at Wuhan No. 1 Hospital between April 2020 and August 2023 were included in this study. Patients were categorized into two groups: a peritoneal dialysis-associated peritonitis (PDAP) group and a non-PDAP group, based on the occurrence of PDAP. Univariate and multivariate logistic regression analyses were conducted to identify risk factors for PDAP in peritoneal dialysis patients. A risk prediction model was constructed, and its predictive performance was assessed using the receiver operating characteristic (ROC) curve.
Results: Among the study population, 59 patients developed PDAP, with an incidence rate of 26.94%. Univariate and multivariate Logistic regression analyses identified serum albumin, age, hemoglobin, diabetes mellitus, and dialysis duration as independent risk factors for PDAP (all P<0.05). The ROC curve analysis of the predictive model yielded an area under the curve (AUC) of 0.914. A validation cohort consisting of 75 patients who underwent peritoneal dialysis between September 2023 and May 2024 included 22 PDAP. In this validation set, the predictive model achieved an AUC of 0.883 for PDAP.
Conclusion: Serum albumin, age, hemoglobin, diabetes, and dialysis duration are independent risk factors for PDAP in peritoneal dialysis patients. The developed predictive model demonstrates strong performance in identifying patients at high risk for PDAP.
Keywords: Peritoneal dialysis; clinical validation; peritonitis; predictive modeling; risk factors.
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