Sepsis as a complex syndrome: Are combined biomarkers the future of diagnosis and prognosis? Clinical perspective

Abstract

Sepsis remains a major cause of mortality worldwide, driven by a dysregulated host response to infection that leads to life-threatening organ dysfunction. Despite advances in evidence-based medicine, early diagnosis and risk stratification remain significant challenges due to the complex, multifaceted nature of sepsis and substantial interindividual variability in clinical presentation. Current approaches relying on single biomarkers cannot provide comprehensive insights into disease progression, limiting their clinical utility in guiding timely and effective interventions. Given the limitations of current single biomarkers in capturing the complexity of sepsis, there is an urgent need for improved diagnostic approaches. While the discovery of novel biomarkers remains important, combining existing biomarkers may offer a pragmatic and effective strategy to improve diagnostic accuracy by leveraging the strengths of each to compensate for the limitations of other. In this clinical perspective, we highlight the potential of such combined biomarker strategies to enhance diagnostic accuracy, support identification of the infection source, and improve prognostic assessment across the clinical course and into long-term outcomes. We provide examples of key biomarkers and their synergistic potential, emphasizing the need for advanced analytical methods such as machine learning and multi-omics integration to enhance predictive accuracy. Shifting toward multi-component biomarker panels represents a critical step toward a more precise, personalized approach to sepsis management to reduce sepsis-related morbidity and mortality. We advocate for further research and validation efforts to facilitate the clinical implementation of combined biomarker models, ultimately transforming sepsis care.