ArticleBMC nephrology2021
Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis.
Article in BMC nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- The predictive value of [TIMP-2]*[IGFBP7] in adverse outcomes for acute kidney injury: a systematic review and meta-analysis.Renal failure · 2023Pooled it
- Does combining urine sediment examination to renal cell arrest and damage biomarkers improve prediction of progression and mortality of sepsis associated acute kidney injury?BMC nephrology · 2025Trial
- Sepsis in critically ill dogs: identification of clinical and laboratory risk factors and evaluation of sepsis scoring systems.Journal of veterinary internal medicine · 2026Article
- An interpretable machine-learning model for predicting in-hospital mortality in patients with sepsis-associated acute kidney injury.Frontiers in medicine · 2026Article
- Review of research progress in sepsis-associated acute kidney injury.Frontiers in molecular biosciences · 2025Review
- Article
- A Genome-Wide Association Study of Serum Metabolite Profiles in Septic Shock Patients.Critical care explorations · 2024Article
- Article
- Acute Kidney Injury and Sepsis after Cardiac Surgery: The Roles of Tissue Inhibitor Metalloproteinase-2, Insulin-like Growth Factor Binding Protein-7, and Mid-Regional Pro-Adrenomedullin.Journal of clinical medicine · 2023Article
- Evaluation of the Efficiency of TIMP-2 as a Biomarker for Acute Kidney Injury in Sepsis.Bulletin of experimental biology and medicine · 2023Article
- Update on prognosis driven classification of pediatric AKI.Frontiers in pediatrics · 2022Review
- Multi-Omics Techniques Make it Possible to Analyze Sepsis-Associated Acute Kidney Injury Comprehensively.Frontiers in immunology · 2022Review
- Assessment of cell cycle arrest biomarkers and neutrophil gelatinase-associated lipocalin to distinguish acute kidney injury from other diseases in dogs.Journal of veterinary internal medicineArticle
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSepsis is the most common trigger for AKI and up to 40% of mild or moderate septic AKI would progress to more severe AKI, which is associated with significantly increased risk for death and later CKD/ESRD. Early identifying high risk patients for AKI progression is a major challenge in patients with septic AKI.
methodsThis is a prospective, multicenter cohort study which enrolled adult patients with sepsis and initially developed stage 1 or 2 AKI in the intensive care unit from January 2014 to March 2018. AKI was diagnosed and staged according to 2012 KDIGO-AKI guidelines. Renal cell arrest biomarkers (urinary TIMP2*IGFBP7, u[TIMP-2]*[IGFBP7]) and renal damage biomarkers (urinary KIM-1[uKIM-1] and urinary IL-18 [uIL-18]) were measured at time of AKI clinical diagnosis, and the performance of biomarkers for predicting septic AKI progression alone or in combination were evaluated. The primary outcome was AKI progression defined as worsening of AKI stage. The secondary outcome was AKI progression with subsequent death during hospitalization.
resultsAmong 433 screened patients, 149 patients with sepsis and stage 1 or 2 AKI were included, in which 63 patients developed progressive AKI and 49 patients subsequently died during hospitalization. u[TIMP-2]*[IGFBP7], uKIM-1 and uIL-18 independently predicted the progression of septic AKI in which u[TIMP-2]*[IGFBP7] showed the greatest AUC (0.745; 95%CI, 0.667-0.823) as compared to uKIM-1 (AUC 0.719; 95%CI 0.638-0.800) and uIL-18 (AUC 0.619; 95%CI 0.525-0.731). Combination of u[TIMP-2]*[IGFBP7] with uKIM-1 improved the performance of predicting septic AKI progression with AUC of 0.752. u[TIMP-2]*[IGFBP7], alone or combined with uKIM-1/uIL-18, improved the risk reclassification over the clinical risk factor model alone both for the primary and secondary outcomes, as evidenced by significant category-free net reclassification index.
conclusionsCombination of renal cell arrest and damage biomarkers enhanced the prediction of AKI progression in patients with sepsis and improved risk reclassification over the clinical risk factors.
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