1554: Predictive Value of SPD-L1 Combined With Disease Severity Scores for 28-Day Mortality in Sepsis

Introduction: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host immune response to infection. Early identification of high-risk patients is crucial for improving clinical outcomes. Currently, no validated methods have been established for accurate prediction of sepsis diagnosis and prognosis. This study aims to develop a prognostic prediction method through the combined application of existing sepsis-related severity scores and the immune-related biomarker soluble programmed death-ligand 1 (sPD-L1), with the objective of achieving enhanced prognostic accuracy in septic patients. Methods: This retrospective study was conducted at the Department of Critical Care Medicine, Shandong Provincial Hospital from June 2022 to December 2023. A total of 164 septic patients were enrolled, with clinical data and serum samples collected for subsequent analyses. We investigated the prognostic value of combining sPD-L1 with established severity scoring systems -APACHE II, SOFA, and SSS, while simultaneously analyzing the correlation between sPD-L1 levels and disease severity.This study incorporates AI-assisted text refinement. Results: SOFA score demonstrated optimal predictive ability for 28-day mortality in septic patients (AUC=0.799), followed by the SSS score (AUC=0.739), while the APACHE II score showed inferior performance (AUC=0.701). sPD-L1 exhibited moderate predictive value for 28-day mortality (AUC=0.712) with an optimal cutoff value of 48.99 pg/mL. In combined prediction models, the incorporation of sPD-L1 significantly enhanced the prognostic performance of all scoring systems, particularly the sPD-L1+SOFA combination which achieved superior predictive accuracy (AUC=0.846). Conclusions: sPD-L1 demonstrated significant association with 28-day mortality in septic patients and served as an independent prognostic predictor. By compensating for the immunological limitations of the SOFA score, sPD-L1 effectively addressed the quantification blind spot of traditional SOFA in evaluating immunosuppressive status. The optimized sPD-L1+SOFA hybrid model significantly enhanced prognostic performance, achieving improved predictive capacity while resolving the persistent limitations of existing scoring systems in objectively assessing immunosuppressive states.