A Simplified Immune-Dysregulation Index (IL-6/LY) as a Robust Predictor of 28-Day In-Hospital Mortality and MODS in Patients with Sepsis.

Abstract

Objective: To evaluate the prognosis significance of a newly simplified immune-dysregulation index, interleukin-6-to-lymphocyte ratio (IL-6/LY), in individuals diagnosed with sepsis.

Methods: This was a retrospective cohort study enrolling consecutive patients diagnosed with sepsis who qualified the inclusion criteria and were admitted to the intensive care unit of the First Affiliated Hospital of Soochow University between March 2017 and January 2023. Multivariate COX and logistic regression models were used to estimate the association between IL-6/LY and 28-day in-hospital mortality or multiple organ dysfunction syndrome (MODS). Restricted cubic splines and survival analysis were used to show a nonlinear correlation between IL-6/LY and mortality. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the prognostic value of IL-6/LY. was performed using the Kaplan‒Meier method.

Results: The study encompassed 301 participants, categorized into two groups-those with low IL-6/LY and high IL-6/LY-determined by the cutoff value of 326.04. On multivariate analyses, a high IL-6/LY was independently associated with 28-day in-hospital mortality (hazard ratio [HR]: 8.01, 95% confidence interval [CI] 4.67-13.74, P < 0.001) and MODS (odds ratio [OR] 3.44, 95% CI 1.85‒6.38, P < 0.001). The area under the curve of IL-6/LY for predicting death and MODS were 0.893 (95% CI, 0.855-0.931) and 0.743 (95% CI, 0.688-0.798), respectively. The Kaplan‒Meier analysis showed a significantly higher risk of mortality in the high IL-6/LY group (≥ 326.04) (log-rank P < 0.001).

Conclusion: The IL-6/LY is significantly associated with the risk of 28-day in-hospital mortality and MODS in patients with sepsis, making it a potential prognostic marker for risk stratification, which enables early identification of high-risk patients, timely interventions, and personalized treatment strategies to optimize patient outcomes.