Heliyon (May 2024)

Dialysate cyclophilin A as a predictive marker for historical peritonitis in patients undergoing peritoneal dialysis

  • Shang-Feng Tsai,
  • Cheng-Hsu Chen,
  • Ming-Ju Wu,
  • Mingli Hsieh

Journal volume & issue
Vol. 10, no. 10
p. e31021

Abstract

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Introduction: No markers have been used to diagnose historical peritoneal dialysis (PD)-related peritonitis. Cyclophilin A (CypA) is associated with glucose toxicity and inflammation. We hypothesize that dialysate CypA can be a marker for historical peritonitis (at least 3 months free from peritonitis). Method: An enzyme-linked immunosorbent assay kit was used to measure the concentration of dialysate CypA. Clinical and laboratory data were collected to correlate with historical peritonitis. Mann-Whitney U test and Chi-square test were used for analysis. Receiver operating characteristic (ROC) analysis was used to evaluate predictive power. Results: Out of a total of 31 patients who had undergone PD for at least 2 years, 18 had no history of PD-related peritonitis, while 13 had experienced PD-related peritonitis at least once. Overall, the patients in this population were in good health (normal white blood cell count, no anemia, normal electrolyte and serum albumin levels). There were no significant differences between patients with and without a history of peritonitis, except for blood white blood cell count (5650.6 ± 1848.4 vs. 7154.6 ± 2056.8, p = 0.032) and dialysate CypA value (24.27 ± 22.715 vs. 54.41 ± 45.63, p = 0.020). In the univariate analysis, only the dialysate CypA level showed a statistically significant association with historical peritonitis (HR = 1.030, 95 % CI = 1.010–1.062, p = 0.046). The AUC for dialysate CypA (>34.83 ng/mL) was 0.748, with a sensitivity of 0.615 and specificity of 0.833. Conclusion: PD peritonitis poses a significant threat to the long-term use of peritoneal dialysis. Based on our study, even in the absence of concurrent infection, dialysate CypA can serve as a predictive marker for historical peritonitis, demonstrating high predictive power along with fair sensitivity and good specificity.

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