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Updated: Aug 15, 2026

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Sepsis in Autoimmune Rheumatic Diseases: Risk Factors, Pathophysiology, and Outcomes
Meiyi Tian1, Zhuo Sun1, Yang Zhang1
1Department of Rheumatology, Aerospace Center Hospital, Beijing, 100049, People's Republic of China.
Abstract:
Sepsis remains a leading cause of morbidity and mortality in patients with autoimmune rheumatic diseases (ARDs), with distinct time-dependent outcomes that differ across disease subtypes, sepsis definitions, immune phenotypes, and follow-up time horizons. Chronic immune dysregulation, disease-specific cytokine signatures, cumulative organ damage, and dose- and duration-dependent immunosuppressive therapies render this population particularly vulnerable to sepsis. Evidence indicates that ARDs and sepsis share overlapping immunopathological mechanisms, including cytokine dysregulation, disease-dependent neutrophil extracellular trap (NET) abnormalities, Treg/Th17 imbalance, endotoxin-related immune tolerance, and phenotype-specific immune suppression. However, the functional consequences of these shared pathways diverge substantially by ARD subtype and disease activity. Whether ARDs independently influence sepsis susceptibility and clinical outcomes remains controversial, largely due to heterogeneity in sepsis definitions, endpoint variability, and incomplete confounder control. In this systematic review with narrative synthesis, conducted in accordance with PRISMA 2020 guidance (87 studies included), we synthesize current epidemiological, genetic, and mechanistic evidence and discuss risk-management and healthcare-policy implications. We summarize disease-related, immune-related, treatment-related, demographic, and healthcare-system risk factors, stratified by evidence strength and specificity to ARDs, and critically evaluate the time-dependent mortality paradox: preserved or improved short-term survival in certain ARDs versus substantially elevated long-term mortality. A deeper understanding of these complex interactions, including pathogen spectra, vaccination status, and modifiable risk factors, may facilitate the development of clinically actionable risk stratification tools, inform personalized therapeutic decision-making, and improve both short- and long-term outcomes in this high-risk population.
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