Impact of a nomogram-based antibiotic decision-making pathway on prophylactic antibiotic use in acute pancreatitis...

This study aimed to develop a multivariable predictive model for early identification of infection risk in patients with acute pancreatitis (AP) complicated by systemic inflammatory response syndrome (SIRS) and to evaluate the clinical impact of a nomogram-based antibiotic decision-making pathway on prophylactic antibiotic use. We retrospectively analyzed the clinical data of 200 patients with AP and SIRS admitted between January 2024 and April 2025. Independent risk factors for infection were identified using multivariable logistic regression analysis. A predictive nomogram was constructed based on the regression coefficients, and its performance was evaluated by the area under the receiver operating characteristic curve, calibration curve, and decision curve analysis. Clinical outcomes, including antibiotic use, intensive care unit admission, 28-day mortality, and length of hospital stay, were compared between infected and non-infected patients. Multivariable analysis identified Acute Physiology and Chronic Health Evaluation II score, neutrophil-to-lymphocyte ratio, procalcitonin, C-reactive protein, and arterial partial pressure of oxygen as independent predictors of infection (P < .05 for all). The nomogram demonstrated good discrimination with an area under the receiver operating characteristic curve of 0.82 and satisfactory calibration. Decision curve analysis confirmed its superior net clinical benefit compared with traditional scoring systems and empirical treatment strategies. The infection group had significantly higher antibiotic utilization rates (100.0% vs 45.8%), intensive care unit admission rates (28.8% vs 7.5%), 28-day mortality (15.0% vs 3.3%), and longer hospital stays (18.10 ± 6.63 vs 11.83 ± 4.13 days; P < .001). The proposed nomogram provides an accurate and practical tool for early infection risk prediction in AP patients with SIRS. Implementing a nomogram-based antibiotic decision-making pathway may reduce unnecessary prophylactic antibiotic use, improve clinical decision-making, and optimize patient outcomes.