Abstract

Background: Peritoneal dialysis (PD) is widely used for treating end-stage renal disease (ESRD) in diabetic nephropathy patients. Suboptimal dialysis outcomes are often linked to chronic microinflammation, yet predictive models integrating immune markers remain limited.
Materials and methods: In this prospective cohort study, 236 diabetic nephropathy patients undergoing PD were categorized into high-inflammation (HI) and microinflammation (MI) groups based on serum levels of CRP, IL-6, and TNF-α. Clinical and biochemical data – including Kt/V, infection rates, and survival – were collected. Logistic regression was applied to identify predictors of poor dialysis outcomes and construct a predictive model.
Results: The HI group showed significantly lower dialysis efficiency (Kt/V < 1.5), increased peritonitis and catheter infections, and reduced survival. Elevated CRP, IL-6, and TNF-α levels were observed alongside higher creatinine, urea nitrogen, fasting glucose, lipids, and notable electrolyte and acid-base imbalances. Logistic regression identified CRP, IL-6, TNF-α, Kt/V, infection rates, and selected biochemical markers as independent predictors of poor outcomes. The resulting predictive model yielded an AUC of 0.87, demonstrating strong discriminative power.
Conclusion: Microinflammation is a key determinant of dialysis efficacy in diabetic nephropathy patients receiving PD. The proposed model, based on inflammatory and dialysis-related parameters, offers a promising approach for early risk stratification and personalized treatment. Further validation may enhance long-term management and survival outcomes in this population.

Author Details

Authors

• Meiyang Zhou
• Haole Huang
• Canxin Zhou

Departments

• Department of Nephrology, The Affiliated People’s Hospital, Ningbo University, Ningbo, Zhejiang, China

Address

Zhou Meiyang, MM
Department of Nephrology
The Affiliated People’s Hospital of Ningbo University
Ningbo, Zhejiang, 315040, China
Email: [email protected]

Citation