Nutritional and Inflammatory Biomarkers PredictPostoperative Infectious Complications AfterPercutaneous Nephrolithotomy: A Retrospective CohortStudy

Background: Percutaneous nephrolithotomy (PCNL) is the primary surgical modality for managing renal calculi, yet the nonnegligible incidence of postoperative infectious complications significantly compromises patient prognosis. Objective: To develop a pre-operative predictive model based on nutritional and inflammatory biomarkers to quantify the risk of infectious complications following PCNL. Methods: From January 2022 to December 2024, 529 consecutive PCNL patients met the inclusion criteria. Pre-operative baseline characteristics, nutritional biomarkers (Prealbumin (PA), Hemoglobin (Hb), Prognostic Nutritional Index (PNI)), and inflammatory biomarkers (C-Reactive Protein (CRP), Procalcitonin (PCT), White Blood Cell Count (WBC), Neutrophil-toLymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Systemic Immune-Inflammation Index (SII)) were collected. The main outcome was the occurrence of any infectious complication within 30 days. Univariable analysis screened candidate predictors; multivariable logistic regression integrated key biomarkers into a risk-prediction model. Receiver Operating Characteristic (ROC) curves were used to evaluate discrimination, providing the Area Under the Curve (AUC) and optimal cut-off values. Results: Among 529 patients who undergoing PCNL, 54 (10.21%) developed postoperative infectious complications. Multivariate logistic regression analysis identified four independent predictors: PNI (Odds Ratio (OR) = 0.386, p < 0.001), PLR (OR = 3.362, p = 0.009), NLR (OR = 2.446, p = 0.017), and SII (OR = 3.300, p < 0.001). The combined prediction model integrating these biomarkers demonstrated superior discriminative ability (AUC = 0.871, 95% Confidence Interval (CI): 0.839-0.898), significantly outperforming individual biomarkers (all p < 0.001). Conclusions: A pre-operative model integrating nutritional and inflammatory biomarkers may accurately stratifies patients at high risk for infectious complications after PCNL, enabling early risk assessment and targeted intervention to improve outcomes.