Cardiac surgery-associated acute kidney injury (CSA-AKI) is a prevalent complication subsequent to cardiopulmonary bypass (CPB) surgery. Timely diagnosis is essential for enhancing patient outcomes. Traditional diagnostic approaches that depend on serum creatinine and urine output frequently result in delays; therefore, there is a pressing necessity to discover sensitive and specific biomarkers. This study is the 1st investigation to concurrently assess the collective predictive capacity of soluble urokinase-type plasminogen activator receptor (suPAR a systemic inflammation biomarker), neutrophil gelatinase-associated lipocalin (NGAL an early indicator of renal tubular damage), and matrix metalloproteinase-7 (MMP-7 a marker of Wnt pathway activation) for CSA-AKI. In this single-center observational study, 116 patients undergoing CPB cardiac surgery were enrolled and categorized into AKI and non-AKI groups according to kidney disease improving global outcomes criteria. Levels of plasma suPAR, urinary NGAL, and urinary MMP-7 were dynamically monitored preoperatively and at 2 hours, 12 hours, 2 days, and 4 days after cardiac surgery. Preoperative plasma suPAR demonstrated significant predictive value for AKI risk prior to surgery, with an area under the curve (AUC) of 0.727. At 2 hours postoperatively, urinary NGAL (AUC = 0.807) and urinary MMP-7 (AUC = 0.805) were identified as the earliest postoperative predictive biomarkers. The combination of suPAR, NGAL, and MMP-7 significantly enhanced predictive performance (AUC = 0.902, sensitivity 90%, specificity 81.8%). Furthermore, a logistic regression model incorporating these biomarkers and CPB time achieved the highest diagnostic accuracy (AUC = 0.931, sensitivity 90%, specificity 84.8%). The simultaneous assessment of preoperative plasma suPAR, postoperative 2-hour urinary NGAL, and urinary MMP-7 markedly improves the diagnostic accuracy for CSA-AKI. Additionally, incorporating CPB time into a nomogram-based predictive model enhances early warning capabilities, which may support early risk stratification. However, further external validation is required before routine clinical implementation.
Xu et al. (Fri,) studied this question.