Identification of acute kidney injury (AKI) can be challenging in patients with underlying chronic disease, and biomarkers often perform poorly in this population. In this study we examined the performance characteristics of the novel biomarker panel of urinary tissue inhibitor of metalloproteinases-2 (TIMP2) and insulin-like growth factor-binding protein 7 ([IGFBP7]) in patients with a variety of comorbid conditions.Methods
We analyzed data from two multicenter studies of critically ill patients in which [TIMP2]•[IGFBP7] was validated for prediction of Kidney Disease: Improving Global Outcomes (KDIGO) Stage 2 or 3 AKI within 12 h. We constructed receiver operating characteristic (ROC) curves for AKI prediction both overall and by comorbid conditions common among patients with AKI, including diabetes mellitus, congestive heart failure (CHF) and chronic kidney disease (CKD).Results
In the overall cohort of 1131 patients, 139 (12.3%) developed KDIGO Stage 2 or 3 AKI. [TIMP2]•[IGFBP7] was significantly higher in AKI versus non-AKI patients, both overall and within each comorbidity subgroup. The AUC for [TIMP2]•[IGFBP7] in predicting AKI was 0.81 overall. Higher AUC was noted in patients with versus without CHF (0.89 versus 0.79; P = 0.026) and CKD (0.91 versus 0.80; P = 0.024).Conclusions
We observed no significant impairment in the performance of cell cycle arrest biomarkers due to the presence of chronic comorbid conditions.