Relationship between multiple inflammatory index level trajectories and 28-day mortality in patients on ECMO

Abstract

Background: Extracorporeal membrane oxygenation (ECMO) is a simplified cardiopulmonary bypass device that provides temporary respiratory and circulatory support and adequate recovery time for the heart and lung, but the mortality rate of acute and critically ill patients undergoing ECMO is still high. Progression of systemic inflammatory response is associated with mortality in ECMO patients. The objective of this study was to investigate the dynamic changes of various inflammatory markers and their relationship with 28-day mortality in patients with ECMO. Methods: A retrospective cohort analysis was conducted on 200 patients receiving ECMO treatment evaluating inflammatory markers including neutrophil-to-lymphocyte ratio (NLR), systemic inflammatory response index (SIRI), procalcitonin (PCT), interleukin-6 (IL-6), and C-reactive protein (CRP) at various time points. A dynamic trajectory model was constructed, and survival differences between groups were assessed using Kaplan–Meier plots and log-rank tests. Multiple Cox proportional hazard models were built to analyze the relationship between dynamic trajectories and clinical outcomes. Causal mediation analysis was applied to determine whether changes in inflammatory trajectories mediated survival outcomes in patients on ECMO through other variables. Results: Age, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and elevated aspartate aminotransferase (AST) levels significantly impacted the 28-day survival rate (p<0.05), with higher mortality observed in patients exhibiting poor inflammatory trajectories. Kaplan–Meier survival analysis revealed that patients in the ascending (AS) group had a significantly higher risk of death than those in the stable (ST) and descending (DS) groups (log-rank p<0.001). Furthermore, multivariate Cox regression analysis identified IL-6 as the most strongly correlated inflammatory marker with mortality risk [Hazard ratio (HR) = 1.97, 95% confidence interval (CI) 1.35-2.87, p<0.001]. Conclusions: This study highlights the importance of dynamic monitoring of inflammatory biomarkers in patients on ECMO, suggesting that individualized treatment adjustments based on these markers could enhance survival rates. Future research should prioritize larger, multicenter cohort studies and clinical trials to validate these findings, aiming to optimize treatment strategies for patients on ECMO.