Abstract
Urinary matrix metalloproteinase-7 (uMMP-7) levels consistently reflect the activity of intrarenal Wnt/b-catenin, which is activated in AKImodels. To test the hypothesis that uMMP-7 is a predictor for severe AKI in patients after cardiac surgery, we performed a prospective, multicenter, two-stage cohort study in 721 patients undergoing cardiac surgery. In stage 1,we enrolled 323 children from three academic medical centers. In stage 2, we enrolled 398 adults at six centers. We analyzed levels of uMMP-7 and other injury biomarkers during the perioperative period. SevereAKI was defined asKidneyDisease ImprovingGlobalOutcomesstage2or3. uMMP-7 levelpeaked within 6 hours after surgery in patients who subsequently developed severe AKI. After multivariate adjustment, the highest quintile of postoperative uMMP-7 level, compared with the lowest quintile, associated with 17-fold (in adults) and 36-fold (in children) higher odds of severe AKI. ElevateduMMP-7 level associatedwith increased risk of composite events (severe AKI, acute dialysis, and in-hospital death) and longer stay in the intensive care unit and hospital. For predicting severe AKI, uMMP-7 had an area under the receiver operating characteristic curve of 0.81 (in children) and 0.76 (in adults), outperforming urinary IL-18, angiotensinogen, neutrophil gelatinase-associated lipocalin, albumin-to-creatinine ratio, and tissue inhibitor of metalloproteinase-2zIGF-binding protein-7 and the clinical model. uMMP-7 significantly improved risk reclassification over the clinicalmodel alone, as measured by net reclassification improvement and integrated discrimination improvement. In conclusion, uMMP-7 is a promising predictor for severe AKI and poor in-hospital outcomes in patients after cardiac surgery.
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CITATION STYLE
Yang, X., Chen, C., Teng, S., Fu, X., Zha, Y., Liu, H., … Hou, F. F. (2017). Urinary matrix metalloproteinase-7 predicts severe AKI and poor outcomes after cardiac surgery. Journal of the American Society of Nephrology, 28(11), 3373–3382. https://doi.org/10.1681/ASN.2017020142
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