Renal Angina Indices and Urinary Biomarkers

Key Points The modified renal angina index outperformed prior indices for early severe AKI prediction in critically ill adults. Combining modified renal angina index with [tissue inhibitor of metalloproteinase-2]×[IGF binding protein 7] improved area under the receiver operating characteristic curve, although not statistically significant, requiring external validation. Early AKI detection supports timely nephroprotective actions and individualized management in critical care. Background Several renal angina indices (RAIs) have been developed to stratify AKI risk in critically ill populations. However, limited evidence supports whether incorporating urinary biomarkers enhances predictive performance. This study aimed to evaluate the diagnostic accuracy of three RAIs, with and without urinary biomarkers integration, for predicting severe AKI (defined as Kidney Disease Improving Global Outcomes stages 2–3) in critically ill adults. Methods In this prospective, multicenter diagnostic study, we assessed the ability of three RAIs to predict severe AKI, defined as Kidney Disease Improving Global Outcomes stages 2–3, within 72 hours of intensive care unit admission. We further evaluated whether the addition of urinary biomarkers improve predictive accuracy, using area under the receiver operating characteristic curve (AUC) and net reclassification improvement (NRI). Results We enrolled 134 critically ill patients, of whom 15% developed severe AKI within 72 hours. Diagnostic performance of RAIs and urinary biomarkers alone was modest (AUC: Matsuura RAI, 0.63; Del Toro RAI, 0.71; and modified RAI [mRAI], 0.76). Incorporating urinary biomarkers improves the predictive performance of all RAIs, particularly enhancing specificity. Among biomarkers assessed, (tissue inhibitor of metalloproteinase-2 [TIMP‐2])×(IGF binding protein 7 [IGFBP7]) demonstrated the greatest capacity to reclassify patients toward event prediction across RAI models. The combination of mRAI with [TIMP‐2]×[IGFBP7] yields the highest absolute predictive performance (AUC, 0.82; 95% confidence interval, 0.72 to 0.93). Conclusions Sequential risk stratification combining clinical RAIs with targeted urinary biomarkers profiling significantly improves early prediction of severe AKI in critically ill adults' patients. Although RAIs and urinary biomarkers alone show limited predictive accuracy, their integration—particularly mRAI plus [TIMP‐2]×[IGFBP7]—optimizes discrimination and may facilitate earlier intervention in high-risk intensive care unit adult patients.

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Journal
Kidney360
Published
2025-11-12
DOI
https://doi.org/10.34067/kid.0000001020
Primary Topic
Acute Kidney Injury Research
Type
article
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article

Renal Angina Indices and Urinary Biomarkers

Olynka Vega‐Vega, Noemí Del Toro-Cisneros, Pablo E. Galindo, Juan M. Villegas-Gamas et al.
Kidney360
Acute Kidney Injury Research
article

Renal Angina Indices and Urinary Biomarkers

Olynka Vega‐Vega, Noemí Del Toro-Cisneros, Pablo E. Galindo, Juan M. Villegas-Gamas, María José López-Ruelas, Cristino Cruz-Rivera, Erick Y. Zúñiga-González, Karla I. Linares-Robles, Rosario G. Hernández-Ortega, Yazmin A. Mercado-Hernández
article en

Abstract

Key Points The modified renal angina index outperformed prior indices for early severe AKI prediction in critically ill adults. Combining modified renal angina index with [tissue inhibitor of metalloproteinase-2]×[IGF binding protein 7] improved area under the receiver operating characteristic curve, although not statistically significant, requiring external validation. Early AKI detection supports timely nephroprotective actions and individualized management in critical care. Background Several renal angina indices (RAIs) have been developed to stratify AKI risk in critically ill populations. However, limited evidence supports whether incorporating urinary biomarkers enhances predictive performance. This study aimed to evaluate the diagnostic accuracy of three RAIs, with and without urinary biomarkers integration, for predicting severe AKI (defined as Kidney Disease Improving Global Outcomes stages 2–3) in critically ill adults. Methods In this prospective, multicenter diagnostic study, we assessed the ability of three RAIs to predict severe AKI, defined as Kidney Disease Improving Global Outcomes stages 2–3, within 72 hours of intensive care unit admission. We further evaluated whether the addition of urinary biomarkers improve predictive accuracy, using area under the receiver operating characteristic curve (AUC) and net reclassification improvement (NRI). Results We enrolled 134 critically ill patients, of whom 15% developed severe AKI within 72 hours. Diagnostic performance of RAIs and urinary biomarkers alone was modest (AUC: Matsuura RAI, 0.63; Del Toro RAI, 0.71; and modified RAI [mRAI], 0.76). Incorporating urinary biomarkers improves the predictive performance of all RAIs, particularly enhancing specificity. Among biomarkers assessed, (tissue inhibitor of metalloproteinase-2 [TIMP‐2])×(IGF binding protein 7 [IGFBP7]) demonstrated the greatest capacity to reclassify patients toward event prediction across RAI models. The combination of mRAI with [TIMP‐2]×[IGFBP7] yields the highest absolute predictive performance (AUC, 0.82; 95% confidence interval, 0.72 to 0.93). Conclusions Sequential risk stratification combining clinical RAIs with targeted urinary biomarkers profiling significantly improves early prediction of severe AKI in critically ill adults' patients. Although RAIs and urinary biomarkers alone show limited predictive accuracy, their integration—particularly mRAI plus [TIMP‐2]×[IGFBP7]—optimizes discrimination and may facilitate earlier intervention in high-risk intensive care unit adult patients.

Kidney360Vol. 7(1)
Hospital General de México (MX), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (MX), Instituto de Salud del Estado de México (MX), Institute for Social Security and Services for State Workers (MX)
Openalex Percentile: Top 59%
Acute Kidney Injury Research
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