Metabolic Determinants of Systemic Inflammation Dynamics During Hemodialysis: Insights from the Systemic...

Background/Objective: Systemic inflammation is a hallmark of end-stage renal disease (ESRD) and contributes to the high burden of cardiovascular morbidity and mortality in hemodialysis (HD) patients. The systemic immune-inflammation index (SII), derived from peripheral neutrophil, lymphocyte, and platelet counts, has emerged as a promising biomarker of immune-inflammatory status. This study aimed to assess the acute effect of a single HD session on systemic inflammation and to identify metabolic predictors associated with this response. Methods: In this single-center observational before-after study, 44 chronic HD patients were enrolled. Blood samples were collected immediately before and after a single HD session. SII was calculated as platelet count × neutrophil count/lymphocyte count. Subgroup analyses were conducted based on renal disease etiology and diabetic status. Multivariable linear regression models identified baseline predictors of SII variation. Results: Median SII significantly decreased post-HD in the overall cohort (from 553.4 [342.6-847.5] to 449.1 [342.6-866.6], p = 0.001), with a more pronounced reduction in patients with cardiometabolic etiologies (from 643.4 [353.3-1360.0] to 539.1 [324.8-1083.4], p = 0.007) and diabetes (from 671.1 [408.7-1469.1] to 458.3 [285.7-1184.4], p = 0.028), but not in those with nephroangiosclerosis (p = 0.182). Baseline total cholesterol (p = 0.001) and gamma-glutamyl transferase (p = 0.034) were positively associated with smaller reductions in SII, while higher baseline glycaemia predicted a greater decrease in post-dialysis SII (p = 0.021). Conclusions: HD acutely modulates systemic inflammation, as reflected by reduction in SII. The magnitude of this response is significantly influenced by individual metabolic profiles. These findings highlight the relevance of metabolic-immune crosstalk in ESRD and suggest that SII may serve as a dynamic biomarker integrating inflammatory and metabolic signals, deserving further validation in larger, outcome-driven studies.