Omar H. Maarouf

Key Points Urinary neutrophil gelatinase–associated lipocalin (uNGAL) can distinguish intensive care unit (ICU) admission diagnosis, especially cardiogenic shock, where creatinine rise is a reflection of ischemia not injury. uNGAL is an early predictor of AKI and its severity in the ICU, which can be a tool to tailor AKI intervention in the ICU. uNGAL can predict AKI in the ICU despite urinary tract infection, which expands its utility. Background Acute kidney injury (AKI) is most commonly caused by tubular injury and is associated with a wide variety of critical illnesses. It is well known that urinary biomarkers can lead to the early identification of AKI. However, the ability of urinary biomarkers to distinguish between different types of critical illness has been less studied. Methods In this prospective cohort study, urinary neutrophil gelatinase–associated lipocalin (uNGAL) was measured in 107 patients consecutively admitted to the ICUs in our tertiary medical center. uNGAL samples were collected within 3–6 hours of admission to an ICU and measured by ELISA. All data were analyzed using R statistical software, and univariate analysis was used to determine the correlations of uNGAL levels with AKI stage, admission diagnoses, and ICU course. Results uNGAL level increased by a mean of 24-fold (SD 10–59) in ICU patients with AKI and demonstrated a significant correlation with the different AKI stages. uNGAL predicted the need for RRT, with values increased by more than 15-fold ( P <0.05) in patients needing RRT, and remained a useful tool to predict AKI in ICU patients with a urinary tract infection. uNGAL level was correlated with certain ICU admitting diagnoses whereby uNGAL levels were lower in ICU patients with cardiogenic shock compared with other admission diagnoses ( β =–1.92, P <0.05). Conclusions uNGAL can be used as an early predictor of AKI and its severity in patients admitted to the ICU, including the need for RRT. uNGAL may also help in distinguishing patients with cardiogenic shock from those with other critical illnesses and identifying those at risk for poor outcomes irrespective of the presence of AKI.