Abstract: Acute kidney injury (AKI) is a common complication in patients with cirrhosis and is associated with significant mortality. Despite the overall poor outcomes, there exists hope for such patients as, unlike in the majority of setting of AKI, specific treatments are available which have been shown to improve renal function and mortality. However, historically intransient difficulties in differential diagnosis and prognosis have limited the extent to which such treatments can be appropriately utilized. In addition, though AKI has long been appreciated as a feared complication, the definitions of AKI employed in studies involving patients with cirrhosis have not been standardized, lack sensitivity, and have often been limited to narrow clinical settings. We conducted a multicenter, prospective observational cohort study of patients with cirrhosis and AKI, drawn from multiple hospital wards, utilizing the modern acute kidney injury network (AKIN) definition and assessed the association between AKI severity and progression with in-hospital mortality. Following this we investigated whether early changes in serum cystatin C levels were more closely associated with subsequent outcomes than similarly early changes in serum creatinine. We subsequently assessed whether novel biomarkers of kidney structural injury, measured on the day of fulfilling AKI criteria, can predict progression of AKI and mortality. Finally, we investigated the ability of biomarkers to assist with differential diagnosis and potentially change the way in which causes of AKI in cirrhosis are conceptualized. 192 patients were enrolled and included in the study. In the first phase, 85 (44%) of these were found to progress to a higher AKIN stage after initially fulfilling AKI criteria. Patients achieved a peak severity of AKIN stage 1, 26%, stage 2, 24%, and stage 3, 49%. Progression was significantly more common and peak AKI stage higher in non-survivors than survivors (p < 0.0001). After adjusting for baseline renal function, demographics and critical hospital and cirrhosis-associated variables, progression of AKI was independently associated with mortality (adjusted odds ratio = 3.8, 95% confidence interval (CI) 1.3-11.1). We conclude that AKI, as defined by AKIN criteria, in patients with cirrhosis is frequently progressive and severe and is independently associated with mortality in a stage-dependent fashion. Unfortunately, accurately predicting which patients will experience the worst outcomes is challenging as serum creatinine correlates poorly with glomerular filtration in patients with cirrhosis and fluctuations may mask progression early in the course of AKI. Cystatin C, a low-molecular-weight cysteine proteinase inhibitor, is a potentially more accurate marker of glomerular filtration. In the second phase of our study we evaluated whether early changes in serum cystatin C would associate more strongly with a composite endpoint of dialysis or mortality than early changes in creatinine. Of 106 patients studied with at least 2 blood samples, 37 (35%) met the endpoint. Cystatin demonstrated less variability between samples than creatinine. Patients were stratified into four groups reflecting changes in creatinine and cystatin: both unchanged or decreased 38 (36%) (Scr-/CysC-); only cystatin increased 25 (24%) (Scr-/CysC+); only creatinine increased 15 (14%) (Scr+/CysC-); and both increased 28 (26%) (Scr+/CysC+). With Scr-/CysC- as the reference, in both instances where cystatin rose, Scr-/CysC+ and Scr+/CysC+, the primary outcome was significantly more frequent in multivariate analysis, P = 0.02 and 0.03, respectively. However, when only creatinine rose, outcomes were similar to the reference group. We therefore concluded that changes in cystatin levels early in AKI are more closely associated with eventual dialysis or mortality than creatinine and may allow more rapid identification of patients at risk for adverse outcomes. The next aspect of the study evaluated urinary biomarkers, including neutrophil gelatinase-associated lipocalin (NGAL), IL-18, kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP), albuminuria and the fractional excretion of sodium (FENa) as predictors of AKI progression and in-hospital mortality. Of 188 patients with available urine samples, 44 (23%) experienced AKI progression alone and 39 (21%) suffered both progression and death during their hospitalization. NGAL, IL-18, KIM-1, L-FABP and albuminuria were significantly higher in patients with AKI progression and death. These biomarkers were independently associated with this outcome after adjusting for key clinical variables including model of end stage liver disease score, IL-18 (relative risk [RR], 4.09; 95% CI, 1.56 to 10.70), KIM-1 (RR, 3.13; 95% CI, 1.20 to 8.17), L-FABP (RR, 3.43; 95% CI, 1.54 to 7.64), and albuminuria (RR, 2.07; 95% CI, 1.05-4.10) per log change. No biomarkers were independently associated with progression without mortality. FENa demonstrated no association with worsening of AKI. When added to a robust clinical model, only IL-18 independently improved risk stratification on a net reclassification index. This phase of the study demonstrated that multiple structural biomarkers of kidney injury, but not FENa, are independently associated with progression of AKI and mortality in patients with cirrhosis. However, injury marker levels were similar between those without progression and those with progression alone. Knowledge of which patients are at the highest risk of adverse outcomes may allow for earlier targeting of treatments but only if clinicians can may objective, accurate diagnoses as to the cause of AKI. The most common etiologies of AKI in this cirrhosis are prerenal azotemia (PRA), acute tubular necrosis (ATN) and hepatorenal syndrome (HRS). However, establishing an accurate differential diagnosis is extremely challenging. Urinary biomarkers of kidney injury distinguish structural from functional causes of AKI and we hypothesized that they may facilitate more accurate and rapid diagnoses. In the next phase of our study we therefore assessed multiple biomarkers for differential diagnosis in clinically adjudicated AKI. Patients (n = 36) whose creatinine returned to within 25% of their baseline within 48 hours were diagnosed with PRA. In addition, 76 patients with progressive AKI were diagnosed by way of blinded retrospective adjudication. Of these progressors, 39 (53%) patients were diagnosed with ATN, 19 (26%) with PRA, and 16 (22%) with HRS. Median values for neutrophil gelatinase-associated lipocalin (NGAL), interleukin-18 (IL-18), kidney injury molecule-1 (KIM-1), liver-type fatty acid binding protein (L-FABP), and albumin differed between etiologies and were significantly higher in patients adjudicated with ATN. The fractional excretion of sodium (FENa) was lowest in patients with HRS, 0.10%, but did not differ between those with PRA, 0.27%, or ATN, 0.31%, P = 0.54. The likelihood of being diagnosed with ATN increased step-wise with the number of biomarkers above optimal diagnostic cutoffs. From these results we concluded that urinary biomarkers of kidney injury are in fact elevated in patients with cirrhosis and AKI due to ATN and that incorporating biomarkers into clinical decision making has the potential to more accurately guide treatment by establishing which patients have structural injury underlying their AKI. Unfortunately, despite these promising results, it is likely that, as long as the focus is on assigning patients one of three distinct diagnoses, there will always be overlap in biomarkers values between groups such that, on the individual rather than population level, their utility will not be fully optimized. In the final phase of our study we evaluated a diagnostic algorithm utilizing optimal cutoffs for FENa and NGAL and the current diagnostic categories of PRA, ATN and HRS. In conclusion, we suggest moving beyond current diagnoses by instead attempting to physiologically phenotype patients using both function (FENa, urinary cystatin C) and structural (NGAL) urinary biomarkers. Figures are presented demonstrating that patients fall into distinct physiologic clusters which may allow more precise targeting of therapies.