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Background: The ability of urinary biomarkers to complement established clinical risk prediction models for postoperative adverse kidney events is unclear. We assessed the effect of urinary biomarkers linked to suspected pathogenesis of cardiac surgery-induced acute kidney injury (AKI) on the performance of the Cleveland Score, a risk assessment model for postoperative adverse kidney events. Methods: This pilot study included 100 patients who underwent open-heart surgery. We determined improvements to the Cleveland Score when adding urinary biomarkers measured using clinical laboratory platforms (neutrophil gelatinase-associated lipocalin [NGAL], interleukin-6) and those in the preclinical stage (hepcidin-25, midkine, alpha-1 microglobulin), all sampled immediately post-surgery. The primary endpoint was major adverse kidney events (MAKE), and the secondary endpoint was AKI. We performed ROC curve analysis, assessed baseline model performance (odds ratios [OR], 95% CI), and carried out statistical reclassification analyses to assess model improvement. Results: NGAL (OR [95% CI] per 20 concentration-units wherever applicable): (1.07 [1.01–1.14]), Interleukin-6 (1.51 [1.01–2.26]), midkine (1.01 [1.00–1.02]), 1-hepcidin-25 (1.08 [1.00–1.17]), and NGAL/hepcidin-ratio (2.91 [1.30–6.49]) were independent predictors of MAKE and AKI (1.38 [1.03–1.85], 1.08 [1.01–1.15], 1.01 [1.00–1.02], 1.09 [1.01–1.18], and 3.45 [1.54–7.72]). Category-free net reclassification improvement identified interleukin-6 as a model-improving biomarker for MAKE and NGAL for AKI. However, only NGAL/hepcidin-25 improved model performance for event- and event-free patients for MAKE and AKI. Conclusions: NGAL and interleukin-6 measured immediately post cardiac surgery may complement the Cleveland Score. The com

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