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Development and validation of a nomogram for peritoneal dialysis-associated peritonitis
Zhiwu Tian1, Shuang Zhou1, Biwen Tian1
1Department of Nephrology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China.
Abstract:
Peritoneal dialysis (PD)-associated peritonitis is a leading cause of technique failure. We aimed to develop and internally validate a Cox regression‑based nomogram for predicting peritonitis‑free survival in incident PD patients. This single-center retrospective cohort study included 372 patients who underwent peritoneal dialysis between June 2018 and December 2024, with follow-up through December 2025. LASSO‑Cox regression was used to select predictors from 23 candidate variables. A nomogram was constructed to predict 6‑, 12‑, and 24‑month peritonitis‑free survival. Model performance was assessed by concordance index (C‑index), time‑dependent ROC, calibration curves, and decision curve analysis. Over a median follow‑up of 26.3 months, 92 (35.4%) and 34 (30.4%) peritonitis events occurred in the training and validation cohorts, respectively. Nine predictors (education, start age, BMI, hemoglobin, potassium, sodium, albumin, calcium, phosphorus) were retained. Independent predictors were lower education (≤9 vs >9 years: HR 1.93, 95% CI 1.03-3.64), lower hemoglobin (HR 0.99, 0.97-1.00), lower albumin (HR 0.92, 0.87-0.97), and lower phosphorus (HR 0.53, 0.29-0.99). The C‑index was 0.707 (95% CI 0.650-0.765). Time‑dependent ROCs in the training cohort were 75.8%, 77.5%, and 69.7% at 6, 12, and 24 months; in the validation cohort, they were 77.7%, 63.8%, and 58.4%, respectively. Calibration was satisfactory at 6 and 12 months (Brier scores 6.0%-11.1%), with wider clinical net benefit at 12-24 months. This nomogram using nine routinely available variables demonstrated moderate discrimination and satisfactory calibration for predicting peritonitis‑free survival in PD patients. While promising, the model requires external validation in larger, multicenter cohorts to confirm its generalizability before routine clinical use.
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