Analysis of prognostic prediction and nursing intervention value in PD patients based on nomogram model

To explore the independent risk factors for technical survival in patients undergoing peritoneal dialysis (PD), construct a nomogram model for predicting 1-, 3-, and 5-year technical survival rates, and validate the clinical value of nursing interventions in improving PD patients' prognosis.

A retrospective cohort study was conducted on 475 patients with end-stage renal disease (ESRD) who received PD at Huangshi Central Hospital from February 2010 to April 2025. Patients were randomly divided into a training group (n = 332) and a validation group (n = 143) at a 7:3 ratio. Spearman correlation analysis was used to identify factors associated with PD duration. Univariate and multivariate Cox regression analyses were performed to screen independent risk factors for PD technical survival, based on which a nomogram prediction model was established. The model's performance was validated using receiver operating characteristic (ROC) curves, concordance index (C-index), calibration plots, and decision curve analysis (DCA). Kaplan-Meier method was applied to analyze cumulative risk differences related to nursing intervention factors.

Spearman correlation analysis showed that PD duration was negatively correlated with age, body mass index (BMI), fasting blood glucose, serum creatinine (Scr), peritonitis, catheter-related complications, Self-Rating Depression Scale (SDS) score, and Self-Rating Anxiety Scale (SAS) score, while positively correlated with years of education, DUV, albumin level, number of primary caregivers, and frequency of health education (all p < 0.05). Multivariate Cox regression analysis identified six independent predictors of PD technical survival: age ≥60 years (hazard ratio [HR] = 9.084, 95% confidence interval [CI]:5.912-13.959), history of diabetes mellitus (HR = 15.047, 95%CI:9.802-23.101), albumin level (HR = 0.894, 95%CI:0.849-0.940), peritonitis (HR = 6.172, 95%CI:3.970-9.595), catheter-related complications (HR = 1.740, 95%CI:1.304-2.320), and abnormal mental state (HR = 2.261, 95%CI:1.589-3.217) (all p < 0.01). The nomogram constructed based on these factors showed good predictive performance in both the training and validation groups.

The constructed nomogram can accurately predict the 1-, 3-, and 5-year technical survival rates of PD patients. Enhanced health education (≥1 session/month), optimized caregiving support systems, improved psychological conditions, and narrowed urban-rural disparities in healthcare resources are effective nursing interventions to improve the technical survival outcomes of PD patients.