4.2 Article

TIMP2○IGFBP7 biomarker panel accurately predicts acute kidney injury in high-risk surgical patients

期刊

JOURNAL OF TRAUMA AND ACUTE CARE SURGERY
卷 80, 期 2, 页码 243-249

出版社

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/TA.0000000000000912

关键词

Acute kidney injury; perioperative medicine; postoperative complications

资金

  1. Astute Medical

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BACKGROUND: Acute kidney injury (AKI) is an important complication in surgical patients. Existing biomarkers and clinical prediction models underestimate the risk for developing AKI. We recently reported data from two trials of 728 and 408 critically ill adult patients in whom urinary TIMP2 circle IGFBP7 (NephroCheck, Astute Medical) was used to identify patients at risk of developing AKI. Here we report a preplanned analysis of surgical patients from both trials to assess whether urinary tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) accurately identify surgical patients at risk of developing AKI. STUDY DESIGN: We enrolled adult surgical patients at risk for AKI who were admitted to one of 39 intensive care units across Europe and North America. The primary end point was moderate-severe AKI (equivalent to KDIGO [Kidney Disease Improving Global Outcomes] stages 2-3) within 12 hours of enrollment. Biomarker performance was assessed using the area under the receiver operating characteristic curve, integrated discrimination improvement, and category-free net reclassification improvement. RESULTS: A total of 375 patients were included in the final analysis of whom 35 (9%) developed moderate-severe AKI within 12 hours. The area under the receiver operating characteristic curve for [TIMP-2]circle[IGFBP7] alone was 0.84 (95% confidence interval, 0.76-0.90; p < 0.0001). Biomarker performance was robust in sensitivity analysis across predefined subgroups (urgency and type of surgery). CONCLUSION: For postoperative surgical intensive care unit patients, a single urinary TIMP2_ IGFBP7 test accurately identified patients at risk for developing AKI within the ensuing 12 hours and its inclusion in clinical risk prediction models significantly enhances their performance. (Copyright (C) 2016 Wolters Kluwer Health, Inc. All rights reserved.)

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