MICROBIOLOGY AND PREDICTOR FACTORS OF PERITONEAL DIALYSIS-RELATED PERITONITIS - A SINGLE-CENTER RETROSPECTIVE STUDY
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Abstract
Background: Peritoneal dialysis (PD)–related peritonitis remains a major complication among patients with end-stage kidney disease undergoing PD. Data on local microbiological patterns and predictors of peritonitis are essential for optimizing empirical therapy and prevention strategies.
Objective: To characterize the microbiological spectrum of PD-related peritonitis and identify clinical predictors of peritonitis in patients undergoing peritoneal dialysis.
Methods: This retrospective cohort study included patients with end-stage kidney disease undergoing peritoneal dialysis at the Department of Nephrology and Dialysis, Thong Nhat Hospital, Ho Chi Minh City, Vietnam, between January 2019 and August 2025. Clinical and laboratory data were extracted from medical records. Microbiological characteristics were determined from peritoneal dialysate culture results. Predictors of peritonitis were evaluated using relative risk (RR), with statistical significance defined as p < 0.05.
Results: Among 190 patients undergoing peritoneal dialysis, 74 developed peritonitis, accounting for 137 episodes and a peritonitis rate of 0.32 episodes per patient-year. Gram-negative organisms were the most common pathogens (45.30%), followed by gram-positive bacteria (23.36%).. Culture-negative peritonitis accounted for 28.50% of episodes, while fungal infections were rare (0.70%). Several factors were associated with an increased risk of peritonitis, including hypokalemia (RR 27.923), hypoalbuminemia (RR 4.337), glomerulonephritis (RR 6.891), and diabetes mellitus (RR 2.55) (p < 0.05).
Conclusions: Gram-negative bacteria were the predominant pathogens causing PD-related peritonitis in this cohort, with Pseudomonas aeruginosa as the leading organism. Hypokalemia, hypoalbuminemia, glomerulonephritis, and diabetes mellitus were significant predictors of peritonitis.
Keywords
Peritoneal dialysis, Peritonitis, Microbiology, Predictors
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References
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