BackgroundAnalyze the risk factors for postoperative delirium (POD) in elderly patients undergoing radical prostatectomy, and built a predictive nomogram model for early identification of high-risk individuals.MethodsA total of 156 patients was recruited and categorized based on whether the development of POD within 7 days post-surgery. After identifying independent risk factors through univariate and multivariate logistic regression analyses, predictive models were established. The discrimination and calibration were determined by C-index and calibration curve, with five-fold cross-validation executed. A nomogram model representing the optimal model was constructed based on the results.ResultsPOD occurred in 24 (15.38%) patients. Significant differences were observed in age, anxiety, physical status, sleep disorders, blood glucose, age-adjusted Charlson comorbidity index (ACCI), anticholinergic, blood loss, postoperative infection, and postoperative pain assessed by the numerical rating scale (NRS). Logistic regression analyses showed that sleep disorders (OR:12.931, 95% CI:1.191-140.351, P = 0.035), ACCI (OR:2.608, 95% CI:1.143-5.950, P = 0.023), postoperative infection (OR:19.298, 95% CI:2.53-147.202, P = 0.04), and NRS (OR:4.033, 95% CI:1.062-15.324, P = 0.041) were independent risk factors for POD. Model 1 (postoperative infection, ACCI, preoperative sleep disorder, NRS) showed better diagnostic performance than the others, of which the area under the curve (AUC) was 0.973. The best diagnostic performance was found in model 1 through five-fold cross-validation, with a C-index of 0.963.ConclusionsThis prospective cohort study highlighted that ACCI, preoperative sleep disorder, postoperative pain, and postoperative infection were identified as independent risk factors for POD. Furthermore, the nomogram derived from model 1 proved to be effective in predicting POD in elderly patients undergoing radical prostatectomy.