Risk stratification for Pseudomonas LRTI in immunocompromised patients: A LASSO-logistic regression model with...

This retrospective cohort study examined 28-day mortality predictors among 177 immunocompromised adults with acute Pseudomonas aeruginosa lower respiratory tract infections (LRTIs) over a 6-year observational period. LASSO regression followed by logistic regression analysis was used to screen 19 clinical and laboratory variables. To evaluate the predictive performance of the model, ROC analysis was performed. Six independent mortality predictors emerged: neutrophil count, D-dimer-to-lymphocyte ratio (DLR), admission aspartate aminotransferase (AST), age, red cell distribution width (RDW), and platelet-to-lymphocyte ratio (PLR). The predictive model demonstrated robust discrimination (AUC = 0.792) with 91.9% sensitivity and 89.5% specificity at the optimal cutoff. The neutrophil-DLR-AST triad emerged as a novel prognostic combination reflecting systemic inflammation, coagulopathy, and hepatic stress. This study identifies 6 clinically accessible biomarkers for mortality risk stratification in immunocompromised hosts with P aeruginosa LRTI, with the neutrophil-DLR-AST triad representing a new prognostic model. The developed model offers clinicians a practical tool for early high-risk patient identification and personalized management. While highlighting the interaction between inflammatory regulation, coagulation abnormalities, and organ dysfunction in determining outcomes, these findings require prospective validation in multicenter cohorts. Future research should elucidate the pathophysiological mechanisms linking these biomarkers to disease progression and explore targeted interventions based on individualized risk profiles.