Combining Serum Cystatin C and Urinary N-Acetyl-Beta-D-Glucosaminidase Improves the Precision for Acute Kidney Injury Diagnosis after Resection of Intracranial Space-Occupying Lesions - Yujun Deng; Jianchao Ma; Yating Hou; Dong Zhou; Tieying Hou; Jinghua Li; Silin Liang; Ning Tan; Chunbo Chen (Karger Publishers, 2020)
Background: Postoperative acute kidney injury (AKI) is frequent and associated with adverse outcomes. Unfortunately, the early diagnosis of AKI remains a challenge. Combining functional and tubular damage biomarkers may provide better precision for AKI detection. However, the diagnostic accuracy of this combination for AKI after neurosurgery is unclear. Serum cystatin C (sCysC) and urinary albumin/creatinine ratio (uACR) are considered functional biomarkers, while urinary N-acetyl-β-D-glucosaminidase (uNAG) represents tubular damage. We aimed to assess the performances of these clinical available biomarkers and their combinations for AKI prediction after resection of intracranial space-occupying lesions. Methods: A prospective study was conducted, enrolling adults undergoing resection of intracranial space-occupying lesions and admitted to the neurosurgical intensive care unit. The discriminative abilities of postoperative sCysC, uNAG, uACR, and their combinations in predicting AKI were compared using the area under the receiver operating characteristic curve (AUC-ROC), continuous net reclassification index (cNRI), and incremental discrimination improvement (IDI). Results: Of 605 enrolled patients, AKI occurred in 67 patients. The cutoff values of sCysC, uNAG, and uACR to predict postoperative AKI were 0.72 mg/L, 19.98 U/g creatinine, and 44.21 mg/g creatinine, respectively. For predicting AKI, the composite of sCysC and uNAG (AUC-ROC = 0.785) outperformed either individual biomarkers or the other two panels (uNAG plus uACR or sCysC plus uACR). Adding this panel to the predictive model improved the AUC-ROC to 0.808. Moreover, this combination significantly improved risk reclassification over the clinical model alone, with cNRI (0.633) and IDI (0.076). Superior performance of this panel was further confirmed with bootstrap internal validation. Conclusions: Combination of functional and tubular damage biomarkers improves the predictive accuracy for AKI after resection of intracranial space-occupying lesions.