Remodeling the model for end-stage liver disease for predicting mortality risk in critically ill patients with cirrhosis and acute kidney injury

2017 
Serum creatinine measurement demonstrates a poor specificity and sensitivity for the early diagnosis of acute kidney injury (AKI) in patients with cirrhosis. The existing model for end-stage liver disease (MELD) score reveals multiple pitfalls in critically ill patients with cirrhosis and acute kidney injury (CAKI). The aim of this study was to re-evaluate the role of creatinine values in the existing MELD score and to develop a novel score for CAKI, named the “acute kidney injurymodel for end-stage liver disease score” (AKI-MELD score). We extracted 651 CAKI from the Multiparameter Intelligent Monitoring in Intensive Care database. A time-dependent Cox regression analysis was performed for developing remodeled MELD scores (Reweight-MELD score, Del-Cr-MELD score, and AKI-MELD score). The area under the receiver operating characteristic curve provided the discriminative power of scoring models related to outcome. The hazard ratio of creatinine was 1.104 (95% confidence interval [CI], 0.945-1.290; P = 0.211). Reweight-MELD score and Del-Cr-MELD score (decreasing the weight of creatinine) were superior to the original MELD score (all P < 0.001). The new AKI-MELD score consists of bilirubin, the international normalized ratio, and the ratio of creatinine in 48 hours to creatinine at admission. It had competitive discriminative ability for predicting mortality (area under the receiver operating characteristic curve, 0.720 [95% CI, 0.653-0.762] at 30 days, 0.688 [95% CI, 0.630-0.742] at 90 days, and 0.671 [95% CI, 0.612-0.725] at 1 year). Further, AKI-MELD score had significantly higher predictive ability in comparison with MELD score, MELD-Na score, and Updated MELD score (all P < 0.001). Conclusion: The predictive value of creatinine for CAKI should be re-evaluated. AKI-MELD score is a potentially reliable tool to determine the prognosis for mortality of CAKI. (Hepatology Communications 2017;1:748–756)
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