Dataset Information

Incorporation of biomarkers with the renal angina index for prediction of severe AKI in critically ill children.

ABSTRACT:

Background and objectives

Novel AKI biomarkers carry variable performance for prediction of AKI in patients with heterogeneous illness. Until utility is demonstrated in critically ill patients outside of the cardiopulmonary bypass population, AKI biomarkers are unlikely to gain widespread implementation. Operationalization of an AKI risk stratification methodology, termed renal angina, was recently reported to enhance prediction at the time of intensive care unit admission for persistent severe AKI. The renal angina index (RAI) was developed to provide the clinical context to direct AKI biomarker testing. This study tested the hypothesis that incorporation of AKI biomarkers in patients fulfilling renal angina improves the prediction of persistent severe AKI.

Design, setting, participants, & measurements

In a multicenter study of 214 patients admitted to the pediatric intensive care unit with sepsis, the discrimination of plasma neutrophil gelatinase-associated lipocalin (NGAL), matrix metalloproteinase-8 (MMP-8), and neutrophil elastase-2 (Ela-2) were determined individually and in combination with the RAI for severe AKI. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated.

Results

Individual biomarkers demonstrated marginal discrimination for severe AKI (area under curve [AUC]: NGAL, 0.72; MMP-8, 0.68; Ela-2, 0.72), inferior to prediction by the clinical model of the RAI (AUC=0.80). Incorporation of each biomarker significantly added to the renal angina model AKI prediction (AUC=0.80, increased to 0.84-0.88; P<0.05 for each). The inclusion of each biomarker with the RAI demonstrated NRI (0.512, 0.428, and 0.545 for NGAL, MMP-8, and Ela-2, respectively; all P<0.03) and IDI (0.075 for Ela-2). The inclusion of both Ela-2 and NGAL with RAI demonstrated an NRI of 0.871 (P<0.001) and an IDI of 0.1 (P=0.01).

Conclusions

This study shows that incorporation of AKI biomarkers into the RAI improves discrimination for severe AKI. The RAI optimizes the utility of AKI biomarkers in a heterogeneous, critically ill patient population.

SUBMITTER: Basu RK

PROVIDER: S-EPMC3974366 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Publications

Incorporation of biomarkers with the renal angina index for prediction of severe AKI in critically ill children.

Basu Rajit K RK Wang Yu Y Wong Hector R HR Chawla Lakhmir S LS Wheeler Derek S DS Goldstein Stuart L SL

Clinical journal of the American Society of Nephrology : CJASN 20140327 4

<h4>Background and objectives</h4>Novel AKI biomarkers carry variable performance for prediction of AKI in patients with heterogeneous illness. Until utility is demonstrated in critically ill patients outside of the cardiopulmonary bypass population, AKI biomarkers are unlikely to gain widespread implementation. Operationalization of an AKI risk stratification methodology, termed renal angina, was recently reported to enhance prediction at the time of intensive care unit admission for persistent ...[more]

PMID: 24677554

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Project description:BackgroundThe renal angina index (RAI) is a tool that has been validated by several studies in the pediatric population to predict the development of severe acute kidney injury (AKI). The aims of this study were to evaluate the efficacy of the RAI in predicting severe AKI in critically ill patients with COVID-19 and to propose a modified RAI (mRAI) for this population.MethodsThis was a prospective cohort analysis of all COVID-19 patients receiving invasive mechanical ventilation (IMV) who were admitted to the intensive care unit (ICU) of a third-level hospital in Mexico City from 03/2020 to 01/2021. AKI was defined according to KDIGO guidelines. The RAI score was calculated for all enrolled patients using the method of Matsuura. Since all patients had the highest score for the condition (due to receiving IMV), the score corresponded to the delta creatinine (ΔSCr) value. The main outcome was severe AKI (stage 2 or 3) at 24 and 72 h after ICU admission. A logistic regression analysis was applied to search for factors associated with the development of severe AKI, and the data were applied to develop a mRAI and compare it vis-à-vis the efficacy of both scores (RAI and mRAI).ResultsOf the 452 patients studied, 30% developed severe AKI. The original RAI score was associated with AUCs of 0.67 and 0.73 at 24 h and 72 h, respectively, with a cutoff of 10 points to predict severe AKI. In the multivariate analysis adjusted for age and sex, a BMI ≥30 kg/m2, a SOFA score ≥6, and Charlson score were identified as risk factors for the development of severe AKI. In the new proposed score (mRAI), the conditions were summed and multiplied by the ΔSCr value. With these modifications, the AUC improved to 0.72 and 0.75 at 24 h and 72 h, respectively, with a cutoff of 8 points.ConclusionsThe original RAI is a limited tool for patients with critical COVID-19 receiving IMV. The mRAI, with the parameters proposed in the present study, improves predictive performance and risk stratification in critically ill patients receiving IMV.

Project description:BackgroundAcute kidney injury (AKI) occurs in one in four children admitted to the intensive care unit (ICU) and AKI severity is independently associated with increased patient morbidity and mortality. Early prediction of AKI has the potential to improve outcomes. In smaller, single center populations, we have previously derived and validated the performance of the renal angina index (RAI), a context driven risk stratification system, to predict severe AKI.MethodsA prospective, observational study (AWARE1, January-December 2014) was conducted in intensive care units from 32 centers in 9 countries. The primary outcome was the presence of severe AKI ("AKIS"; Stage 2-3 AKI KDIGO guidelines) on the third day after ICU admission (). We compared the performance of the RAI to changes in serum creatinine relative to baseline (SCr/Base) for prediction of the primary outcome and secondary outcomes of interest. A RAI ≥ 8 defined fulfillment of renal angina (RA+); RA+ was compared to SCr increased relative to baseline ("SCr>Base"; using maximum SCr in first 12 hours of ICU admission).FindingsThe 1590 patients studied were 55% male and had median age of 54.5 months. 286 patients (17.9%) were RA+. AKIS occurred in 121 (42.3%) RA+ vs. 247 (18.9%) RA-patients (relative risk (RR) 2.23; 95% confidence interval (CI): 1.87-2.66, p<0.001). 368 (23.1%) patients with AKIS had increased renal replacement therapy utilization (10.9% vs. 1.5%, p<0.001) and increased mortality (7.6% vs. 4.3%, p=0.01) compared to patients without AKIS. RA+ demonstrated better prediction for AKIS than SCr>Base (RR: 1.61; (1.33-1.93), p<0.001) which was maintained on multivariate regression (independent odds ratio (OR): RA+ 3.21; 95% CI (2.20-4.67) vs. SCr>Base 0.68; 95% CI (0.49-4.94)).InterpretationEarlier, better prediction of severe AKI has the potential to improve AKI associated patient outcomes. Compared to isolated, context-free changes in SCr, renal angina risk assessment improved accuracy for prediction of severe AKI in critically ill children and young adults.

Dataset Information

Incorporation of biomarkers with the renal angina index for prediction of severe AKI in critically ill children.

Background and objectives

Design, setting, participants, & measurements

Results

Conclusions

Publications

Incorporation of biomarkers with the renal angina index for prediction of severe AKI in critically ill children.

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