Unveiling risk factors: a prognostic model of frequent peritonitis in peritoneal dialysis patients

Area of Science:

• Nephrology
• Internal Medicine
• Clinical Epidemiology

Background:

• Peritoneal dialysis-associated peritonitis (PDAP) is a significant complication for patients undergoing peritoneal dialysis (PD).
• Identifying patients at high risk for frequent PDAP episodes is crucial for improving patient outcomes and management strategies.

Purpose of the Study:

• To construct and validate a risk prediction model for frequent PDAP episodes in PD patients.
• To develop a user-friendly tool, such as a nomogram, for assessing individual patient risk.

Main Methods:

• A retrospective cohort study of 371 PDAP patients from January 2010 to December 2021.
• Binary logistic regression was employed to build the risk prediction model.
• Patients were randomly allocated into training (80%) and test (20%) sets for model development and validation.

Main Results:

• The final model identified key risk factors for frequent PDAP: diabetes mellitus (DM), hemoglobin (HB), serum albumin (ALB), lactate dehydrogenase (LDH), serum potassium (K), N-terminal pro-brain natriuretic peptide (NT-proBNP), and peritoneal dialysate white cell count on day 1.
• The model achieved an area under the curve (AUC) of 0.75 in the training set and 0.76 in the test set, indicating excellent predictive accuracy.
• A nomogram was developed for intuitive risk assessment.

Conclusions:

• The developed predictive model demonstrates strong performance in identifying PDAP patients at high risk for frequent episodes.
• The nomogram provides a practical tool for clinicians to evaluate patient risk.
• Further validation through larger, multicenter studies is recommended to confirm the model's generalizability.