The combination of kidney function variables with cell cycle arrest biomarkers identifies distinct subphenotypes of sepsis-associated acute kidney injury: a post-hoc analysis (the PHENAKI study) - Dimitri Titeca-Beauport; Momar Diouf; Delphine Daubin; Ly Van Vong; Guillaume Belliard; Cédric Bruel; Yoann Zerbib; Christophe Vinsonneau; Kada Klouche; Julien Maizel (Renal Failure)
Background The severity and course of sepsis-associated acute kidney injury (SA-AKI) are correlated with the mortality rate. Early detection of SA-AKI subphenotypes might facilitate the rapid provision of individualized care.Patients and methods In this post-hoc analysis of a multicenter prospective study, we combined conventional kidney function variables with serial measurements of urine (tissue inhibitor of metalloproteinase-2 [TIMP-2])* (insulin-like growth factor-binding protein [IGFBP7]) at 0, 6, 12, and 24 h) and then using an unsupervised hierarchical clustering of principal components (HCPC) approach to identify different phenotypes of SA-AKI. We then compared the subphenotypes with regard to a composite outcome of in-hospital death or the initiation of renal replacement therapy (RRT).Results We included 184 patients presenting SA-AKI within 6 h of the initiation of catecholamines. Three distinct subphenotypes were identified: subphenotype A (99 patients) was characterized by a normal urine output (UO), a low SCr and a low [TIMP-2]*[IGFBP7] level; subphenotype B (74 patients) was characterized by existing chronic kidney disease (CKD), a higher SCr, a low UO, and an intermediate [TIMP-2]*[IGFBP7] level; and subphenotype C was characterized by very low UO, a very high [TIMP-2]*[IGFBP7] level, and an intermediate SCr level. With subphenotype A as the reference, the adjusted hazard ratio (aHR) [95%CI] for the composite outcome was 3.77 [1.92–7.42] (p < 0.001) for subphenotype B and 4.80 [1.67–13.82] (p = 0.004) for subphenotype C.Conclusions Combining conventional kidney function variables with urine measurements of [TIMP-2]*[IGFBP7] might help to identify distinct SA-AKI subphenotypes with different short-term courses and survival rates.