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)

Abstract

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.

Keywords: Acute kidney injury; The AKI-CHECK study was registered at ClinicalTrials.gov (NCT02812784); biomarkers; cluster; phenotype; septic shock.

Figure 1.

Cluster identification. The upper figure shows the hierarchical clustering dendrogram with three clusters. The lower figure shows the factor map from the principal component analysis. Each individual is represented by label, depending on the cluster: a green circle (subphenotype A), a blue triangle (subphentopye B), or a red square (subphenotype C).

Figure 2.

Vtest graph, showing the variables that contribute to the different subphenotypes. The Vtest graph characterizes the groups in terms of the variables whose average is lower or higher than in the total sample. Each bar represents the distance (in multiples of the standard deviation) between the within-class mean value and the total cohort mean value. TIMP-2: tissue inhibitor of metalloproteinases-2; IGFBP-7: insulin-like growth factor-binding protein 7; SCr: serum creatinine; eGFR: estimated glomerular filtration rate.

Figure 3.

Proportions of patients with in-hospital death, renal replacement therapy initiation, and reversible AKI in the different subphenotype groups.

Figure 4.

Crude composite in-hospital survival (no death or RRT initiation) curve for the different subphenotypes.

Figure 5.

Adjusted composite in-hospital survival (no death or RRT initiation) curve for the different subphenotypes. With subphenotype A as the reference, the adjusted hazard ratio (aHR) [95%CI] for the composite in-hospital survival 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. Adjusted for age, renin–angiotensin system inhibitors, the nonrenal SOFA score at inclusion, lactate at inclusion, SAPS II, dobutamine support over the first 24 h, and fluid administered over the first 24 h.