Abstract
Novel Biomarkers for Acute Kidney Injury: Diagnostic Profiles, Etiology-Specific Applications, Prognostic Impacts, and the Path to Precision Medicine: Bridging the Clinical Action Gap—Review
Elmukhtar Habas1, Aml Habas2, Amnna Rayani3, Ala Habas4, Khaled Alarbi5, Eshrak Habas6, Mohamed Baghi5, Mohammad Babikir7, Abdelrahaman Hamad8, Almehdi Errayes9
Keywords: Acute kidney injury, biomarkers, NGAL, TIMP-2, IGFBP7, prognosis, precision medicine, artificial intelligence
DOI: 10.63475/yjm.v4i3.0226
DOI URL: https://doi.org/10.63475/yjm.v4i3.0226
Publish Date: 31-12-2025
Download PDFPages: 514 - 525
Downloads: 3
Citation: 0
Author Affiliation:
1 Senior Consultant, Hamad Medical Corporation, Hamad General Hospital, Doha, Qatar
2 Specialist, Open Libyan University, Tripoli, Libya
3 Professor, University of Tripoli, Tripoli, Libya
4 Tripoli Central Hospital, University of Tripoli, Tripoli, Libya
5 Associate Consultant, Hamad Medical Corporation, Hamad General Hospital,
Doha, Qatar
6 Tripoli University Hospital, University of Tripoli, Tripoli, Libya
7 Medicine Specialist, Hamad Medical Corporation, Hamad General Hospital, Doha, Qatar
8 Consultant, Hamad Medical Corporation, Hamad General Hospital, Doha, Qatar
9 Senior Consultant, Hamad Medical Corporation, Hamad General Hospital, Doha, Qatar
Abstract
Acute kidney injury (AKI) remains a substantial clinical challenge, affecting approximately half of all critically ill patients and is associated with a high risk of mortality, need for dialysis, and progression to chronic kidney disease (CKD). Traditional diagnostic methods, which rely on urine output and serum creatinine (sCr), are non-specific and delayed, thus missing the crucial window for early intervention. New urine and plasma biomarkers, such as neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP), interleukin-18 (IL-18), tissue inhibitor of metalloproteinase-2, insulin-like growth factor-binding protein 7 ([TIMP-2] × [IGFBP7]), and C-C motif chemokine ligand 14 (CCL14), have become effective tools for risk assessment and early detection over the past decade. With diagnostic accuracy superior to creatinine, these biomarkers allow for the identification of AKI within 2 to 12 hours, as they represent tubular stress, damage, and healing processes. Multi-marker panels further enhance diagnostic performance, particularly in complex clinical scenarios such as sepsis and heart surgery. Etiology-specific biomarker patterns are now well-delineated: minimal elevations in prerenal conditions may guide safe fluid management, whereas sustained increases in intrinsic AKI suggest poor recovery and may necessitate renal replacement therapy (RRT). Biomarker-guided interventions have been shown to reduce the incidence of severe AKI by 15% to 30% in high-risk populations. Emerging biomarker types that have the potential to improve early detection and prognosis accuracy include filtration surrogates, oxidative stress indicators, microRNAs (e.g., miR-21, exosomal panels), and inflammation/repair biomarkers. Despite these advancements, difficulties remain, including inconsistencies in testing, high costs, limited data on juvenile and postrenal AKI, and a “clinical action gap” where biomarker findings have not been reliably linked to evidence-based therapies. The integration of artificial intelligence with point-of-care diagnostics has significant potential for future clinical applications. This review consolidates current data to illustrate how emerging biomarkers are transforming thetreatment of AKI from a reactive diagnosis to a proactive, precision-oriented strategy.