Remote Monitoring in Automated Peritoneal Dialysis Modifies the Clinical Course of Peritonitis: A Secondary Analysis of a Cluster Randomized Trial

Background: Peritonitis remains the most serious complication of peritoneal dialysis (PD), often resulting in hospitalization, technique failure, and increased mortality. Remote monitoring (RM) in automated peritoneal dialysis (APD) provides fast and opportune access to treatment data, potentially enabling earlier clinical intervention. Aim: To assess whether RM modifies the clinical course of peritonitis in APD patients by evaluating the time to first episode, hospitalization outcomes, and ultrafiltration (UF) dynamics. Methods: This secondary analysis of a cluster randomized controlled trial included 801 APD patients (403 with RM, 398 with conventional APD) followed from 2018 to 2020. A total of 95 patients with confirmed peritonitis were analyzed. Clinical variables and UF trends from the Sharesource® platform were assessed for the 10 days before and after the peritonitis diagnosis. Survival was evaluated using Kaplan–Meier curves and multivariable Cox regression models. Results: RM-APD patients experienced a significantly longer time to first peritonitis episode (13.3 vs. 11.7 months; p < 0.001). Although there were no significant differences in overall peritonitis incidence, hospitalization, or mortality rates, RM-APD patients showed improved post-hospitalization survival (p = 0.003) and lower therapy dropout after infection (p = 0.001). UF trends suggested a pre-infection decline, though not statistically significant. Conclusion: RM does not reduce peritonitis incidence but appears to enable earlier detection and improved outcomes, supporting a shift toward proactive management in APD. Future research should explore predictive algorithms based on RM-derived data to enhance peritonitis care.