{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T23:47:04Z","timestamp":1793144824134,"version":"4.5.0"},"reference-count":192,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T00:00:00Z","timestamp":1773878400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:p>Sepsis remains a leading global cause of morbidity and mortality among the critically ill, driven by a dysregulated host response to infection that culminates in systemic inflammation and multi-organ dysfunction. While numerous potential biomarkers have been identified, their translation into robust clinical tools remains challenging. This review synthesizes the current understanding of sepsis biomarkers, focusing on their utility in delineating the intricate pathophysiological mechanisms underlying this heterogeneous syndrome and predicting patient outcomes. Crucially, we emphasize the pivotal role of cutting-edge methodologies, including advanced multi-omics integration, sophisticated bioinformatics, and machine learning algorithms, in accelerating the discovery and validation of novel precision-guided strategies. 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