Marco Fiorentino1,2, Fadi A Tohme1, Raghavan Murugan1,3, John A Kellum4,5. 1. The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. 2. Department of Emergency and Organ Transplantation, Nephrology, Dialysis and Transplantation Unit, University of Bari, Bari, Italy. 3. The CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. 4. The Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA, Kellum@pitt.edu. 5. The CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA, Kellum@pitt.edu.
Abstract
BACKGROUND: Numerous studies have suggested a possible role for acute kidney injury (AKI) biomarkers in predicting renal recovery both before and after renal replacement therapy (RRT). However, definitions for recovery and whether to include patients dying but free of RRT may influence results. OBJECTIVES: To validate plasma neutrophil gelatinase-associated lipocalin (pNGAL) as a useful biomarker for predicting or improving the ability of clinical predictors alone to predict recovery following AKI, including in our model plasma B-type natriuretic peptide (pBNP) to account for cardiovascular events. METHODS: We analyzed 69 patients enrolled in the Acute Renal Failure Trial Network study. pNGAL and pBNP were measured on days 2, 7, and 14. We analyzed their predictive ability for subsequent recovery, defined as alive and independent from dialysis in 60 days. In sensitivity analyses, we explored changes in results with alternative definitions of recovery. RESULTS: Twenty-nine patients (42%) recovered from AKI. Neither pNGAL nor pBNP, alone or in combination, was accurate predictors of renal recovery-the best area under the receiver-operating characteristics curve (AUC) was for pNGAL using the largest relative change (AUC 0.59, 95% CI 0.45-0.74). The best clinical model achieved superior performance to biomarkers (AUC 0.69, 95% CI 0.56-0.81). The AUC was greatest (0.75, 95% CI 0.60-0.91) when pNGAL + pBNP on day 14 were added to the clinical model but this increase did not achieve statistical significance. However, integrated discrimination improvement analysis showed that the addition of pNGAL and pBNP on day 14 to the clinical model significantly improved the prediction of renal recovery (p = 0.008). CONCLUSIONS: pNGAL and pBNP can improve the accuracy of clinical parameters in predicting AKI recovery and a full model using biomarkers together with age achieved adequate discrimination.
BACKGROUND: Numerous studies have suggested a possible role for acute kidney injury (AKI) biomarkers in predicting renal recovery both before and after renal replacement therapy (RRT). However, definitions for recovery and whether to include patients dying but free of RRT may influence results. OBJECTIVES: To validate plasma neutrophil gelatinase-associated lipocalin (pNGAL) as a useful biomarker for predicting or improving the ability of clinical predictors alone to predict recovery following AKI, including in our model plasma B-type natriuretic peptide (pBNP) to account for cardiovascular events. METHODS: We analyzed 69 patients enrolled in the Acute Renal Failure Trial Network study. pNGAL and pBNP were measured on days 2, 7, and 14. We analyzed their predictive ability for subsequent recovery, defined as alive and independent from dialysis in 60 days. In sensitivity analyses, we explored changes in results with alternative definitions of recovery. RESULTS: Twenty-nine patients (42%) recovered from AKI. Neither pNGAL nor pBNP, alone or in combination, was accurate predictors of renal recovery-the best area under the receiver-operating characteristics curve (AUC) was for pNGAL using the largest relative change (AUC 0.59, 95% CI 0.45-0.74). The best clinical model achieved superior performance to biomarkers (AUC 0.69, 95% CI 0.56-0.81). The AUC was greatest (0.75, 95% CI 0.60-0.91) when pNGAL + pBNP on day 14 were added to the clinical model but this increase did not achieve statistical significance. However, integrated discrimination improvement analysis showed that the addition of pNGAL and pBNP on day 14 to the clinical model significantly improved the prediction of renal recovery (p = 0.008). CONCLUSIONS:pNGAL and pBNP can improve the accuracy of clinical parameters in predicting AKI recovery and a full model using biomarkers together with age achieved adequate discrimination.
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