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Biomarker-Based Diagnosis and Risk Stratification in Sepsis-Associated Acute Kidney Injury: From Molecular Mechanisms
Breallan De Jesús Romero Pajaro1, Diana Carolina Caicedo Sánchez1, Michael Mario Vélez Lora1
1Faculty of Health Sciences, Department of Internal Medicine, Universidad Libre Barranquilla Campus, Barranquilla 080001, Colombia.
None:
Sepsis-associated acute kidney injury (SA-AKI) remains a major diagnostic challenge in critically ill patients, as conventional functional criteria-serum creatinine and urine output-often detect AKI after clinically relevant pathophysiological derangement has already evolved. Increasing evidence suggests that SA-AKI reflects a heterogeneous process characterized by early cellular stress, microcirculatory dysfunction, inflammation-associated injury, and maladaptive repair preceding overt functional decline. In this context, biomarker-based approaches have been investigated to improve early risk stratification, phenotypic characterization, and prognostic assessment in septic patients. This narrative review synthesizes current evidence on established and emerging biomarkers relevant to SA-AKI, encompassing stress markers ([TIMP-2]•[IGFBP7]), tubular injury markers (e.g., NGAL, KIM-1, IL-18), functional markers (e.g., proenkephalin/penKid, cystatin C), and exploratory molecular signatures such as circulating microRNAs (miRNAs). We examine their temporal dynamics, performance estimates, and context-dependent applicability in sepsis, and discuss limitations related to heterogeneity, assay variability, and threshold standardization. Particular attention is given to multimodal and longitudinal strategies integrating biomarkers with KDIGO criteria and clinical phenotyping. Finally, we outline a stratified framework for biomarker interpretation in SA-AKI anchored to pathophysiological windows and clinical decision points. While available evidence supports the potential of selected biomarkers for short-term risk stratification and trajectory assessment, implementation requires prospective validation demonstrating incremental value beyond established models and measurable impact on patient-centered outcomes.
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