Abstract: 【Abstract】 Objective To explore the risk factors for depression in peritoneal dialysis (Peritoneal Dialysis, PD) patients and construct a nomogram prediction model. Methods A total of 233 PD patients were selected from Zhongda Hospital Southeast University, Nanjing Drum Tower Hospital and Nanjing Lishui People's Hospital between October 2023 and June 2024 to form the modeling set, while 66 PD patients from July to October 2024 were included in the validation set. Binary logistic regression analysis was employed to identify risk factors for depression, and a nomogram prediction model for depression was constructed and validated.. Results In the modeling set, the anxiety scores (OR=27.579, 95%CI: 12.041~63.165, P＜0.001), work status (OR=0.351, 95%CI: 0.147~0.834, P=0.018), cognitive function scores (OR=0.386, 95%CI: 0.165~0.902, P=0.028), physical health composite index (OR=0.940, 95%CI: 0.899~0.983, P=0.007), hypersensitive C-reactive protein level (OR=1.024, 95%CI: 1.002~1.046, P=0.030), and parathyroid hormone (OR=1.001, 95%CI: 1.000~1.003, P=0.022) were predictive factors for depression in PD patients. The Area Under Curve (AUC) of the Receiver Operating Characteristic Curve for the modeling set was 0.893 (95% CI: 0.852~0.934), with a sensitivity of 76.4% and a specificity of 90.2%. The AUC for the validation set was 0.926 (95% CI: 0.866~0.985), with a sensitivity of 96.0% and a specificity of 82.9%. Conclusion The nomogram prediction model for depression in PD patients demonstrates good clinical utility, aiding health care workers in identifying individuals at high risk of depression.

Key words: Peritoneal dialysis, Depression, Prediction model, Risk factor