The relationship between novel inflammatory biomarkers (SII, NLR, PLR and MLR) and 30-day mortality risk in sepsis-associated encephalopathy: a retrospective analysis

The relationship between the novel inflammatory biomarkers (SII, NLR, PLR, and MLR) and mortality risk in SAE patients remains poorly understood, and their potential as predictors for 30-day mortality in these patients has not been fully understood. This study aimed to investigate the relationship between these inflammatory biomarkers and 30-day mortality in SAE patients. To assess their predictive value, receiver operating characteristic (ROC) curves were used to evaluate the ability of a combined model, incorporating SII, NLR, PLR, MLR, and SOFA scores, to predict 30-day mortality in this population. Data was sourced from the MIMIC-IV database. SAE patients who were aged ≥ 18 years, admitted to the ICU for the first time, had an ICU stay of ≥ 24 h, were included in the study. The outcome was 30-day mortality. Restricted cubic spline (RCS) curves were used to analyze the potential correlation between SII, NLR, PLR, MLR and all-cause mortality. Additionally, the area under the receiver operating characteristic (ROC) curve (AUC) was employed to compare the predictive abilities of these parametres for all-cause mortality. The study included 714 SAE patients who met the inclusion and exclusion criteria. These patients were divided into three groups according to tertiles of SII, NLR, PLR, and MLR. It was observed that the T3 group of SII, NLR, PLR, and MLR experienced significantly higher mortality rates at 30-day compared to the T1 group ( p < 0.05). Kaplan-Meier analysis indicated significant differences in 30-day mortality rates across the groups. Multivariate Cox regression analysis further confirmed that the T3 group for SII, NLR, PLR, and MLR was independently associated with an increased risk of 30-day mortality compared to the T1 group. Restricted cubic spline models revealed a generally monotonic increasing relationship between the four inflammatory biomarkers with 30-day mortality. The combination model showed the highest apparent AUC for 30-day mortality prediction (AUC 0.678, 95% CI 0.633–0.722), and the optimism-corrected AUC after bootstrap validation was 0.666. This retrospective analysis demonstrated that SII, NLR, PLR, and MLR could serve as potential inflammatory biomarkers for evaluating the 30-day mortality risk in SAE patients. The combination of these biomarkers with SOFA score showed the highest apparent predictive performance and may provide complementary information for 30-day mortality risk assessment in SAE patients.