Prediction of acute kidney injury after total aortic arch replacement with serum cystatin C and urine N-acetyl-β-D-glucosaminidase: A prospective observational study

Background: Acute kidney injury (AKI) after total aortic arch replacement (TAAR) is frequent and associated with adverse outcomes, whereas its early detection remains a challenge. Serum cystatin C (sCysC) and urinary N- acetyl-beta-D-glucosaminidase (uNAG) are clinically available renal biomarkers, but their combination for AKI detection requires more evidence. This study aimed to assess the discriminative abilities of these biomarkers in AKI after TAAR. Materials and Methods: Patients undergoing TAAR were included in this prospective observational study. The AKI prediction model was developed and internal verificated, and the significance of each variable was analyzed by random forest (RF). Finally, the best predictive critical values of sCysC and uNAG were explored by the AUC-ROC curve.Results: The AUC-ROC of the prediction model was substantially enhanced by adding sCysC and uNAG (0.909 vs 0.844, p < 0.001), and the clinical utility and risk reclassification were significantly improved. Additionally, the RF showed that sCysC and uNAG ranked first and second. The AUC-ROC for each were 0.864 and 0.802 respectively, and the cut-off values were 1.395 mg/L and 31.90 U/g Cre respectively.Conclusion: The prediction model incorporating functional marker sCysC and tubular injury marker uNAG can improve the discriminative abilities of AKI after TAAR.

Automated summary

This study aimed to assess the discriminative abilities of serum cystatin C (sCysC) and urinary N-acetyl-beta-D-glucosaminidase (uNAG) in acute kidney injury (AKI) after total aortic arch replacement (TAAR). The results showed that incorporating sCysC and uNAG into the prediction model significantly improved its predictive ability, and the clinical utility and risk reclassification were also significantly improved. The study also found that sCysC and uNAG had the best discriminative abilities for AKI.