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. 2020 Mar 12;5(6):839-850.
doi: 10.1016/j.ekir.2020.03.005. eCollection 2020 Jun.

Sepsis-Associated Acute Kidney Disease

Collaborators, Affiliations

Sepsis-Associated Acute Kidney Disease

Sadudee Peerapornratana et al. Kidney Int Rep. .

Abstract

Introduction: About one-third of critically ill patients with acute kidney injury (AKI) develop persistently decreased kidney function, known as acute kidney disease (AKD), which may progress to chronic kidney disease (CKD). Although sepsis is the most common cause of AKI, little is known about sepsis-associated AKD.

Methods: Using data from a large randomized trial including 1341 patients with septic shock, we studied patients with stage 2 or 3 AKI on day 1 of hospitalization. We defined AKD as a persistently reduced glomerular filtration rate for >7 days. In addition to clinical data, we measured several urinary biomarkers (tissue inhibitor of metalloproteinases-2 and insulin-like growth factor-binding protein 7 [TIMP-2∗IGFBP7], neutrophil gelatinase-associated lipocalin [NGAL], kidney injury molecule-1 [KIM-1], liver-type fatty acid binding protein, and type 4 collagen) at 0, 6, and 24 hours, to predict AKD.

Results: Of 598 patients, 119 (19.9%) died within 7 days, 318 (53.2%) had early reversal of AKI within the first 7 days, whereas 161 (26.9%) developed AKD. In patients with early reversal, 45 (14.2%) had relapsed AKI after early reversal, and only about one-third of these recovered. Among patients developing AKD, only 15 (9.3%) recovered renal function prior to discharge. Male sex, African American race, and underlying CKD were more predominant in patients developing AKD. None of the biomarkers tested performed well for prediction of AKD, although NGAL modestly increased the performance of a clinical model.

Conclusions: AKD is common in patients with septic shock, especially among African American males and those with underlying CKD. Existing AKI biomarkers have limited utility for predicting AKD but might be useful together with clinical variables. Novel predictive biomarkers for renal recovery are needed.

Keywords: acute kidney disease; acute kidney injury; biomarker; predict; recovery; sepsis.

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Figures

None
Graphical abstract
Figure 1
Figure 1
Trajectories after acute kidney injury (AKI).
Figure 2
Figure 2
Study flow. AKI, acute kidney injury; Cr, creatinine.
Figure 3
Figure 3
Distribution of tissue inhibitor of metalloproteinases-2 and insulin-like growth factor-binding protein 7 (TIMP-2∗IGFBP7) level at baseline, and 6 and 24 hours by clinical status at 7 days. AKD, acute kidney disease.
Figure 4
Figure 4
(a–c) Comparing areas under the receiver operating characteristic curve (AUC-ROCs) for prediction of acute kidney disease. NGAL, neutrophil gelatinase-associated lipocalin; TIMP-2∗IGFBP7, tissue inhibitor of metalloproteinases-2 and insulin-like growth factor-binding protein 7.
Figure 5
Figure 5
Patient survival comparing acute kidney disease (AKD) and early-reversal groups (a) by 90 days and (b) by 1 year.
Figure 6
Figure 6
Patient survival by 1 year stratified by recovery trajectories of acute kidney injury at hospital discharge.

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