L-Carnitine, a new biomarker screened based on untargeted metabolomics, predict cardiac surgery-associated acute kidney injury: a prospective cohort study

This study aims to evaluate the diagnostic potential of L-carnitine (LC) for the early detection of cardiac surgery-associated acute kidney injury (CSA-AKI). We collected clinical data and serum samples from 27 patients admitted to the Intensive Care Unit (ICU) of Nanjing Medical University Affiliated Nanjing Hospital between February 2024 and March 2024. Among these, 13 patients were diagnosed with CSA-AKI, while 14 served as non-AKI controls. Untargeted metabolomic analysis revealed LC as a differentially expressed metabolite between the two groups. In addition, clinical data and serum samples were prospectively collected from patients undergoing cardiac surgery at Nanjing Medical University Affiliated Nanjing Hospital between May 2024 and July 2024. Serum samples were taken preoperatively (immediately upon entering the operating room) and postoperatively (immediately upon ICU admission). The levels of blood urea nitrogen (BUN), serum creatinine (Scr), neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and LC were measured. Multivariate logistic regression analysis was used to find independent risk variables for CSA-AKI. The predictive performance of the biomarkers, the clinical model, and their combination were evaluated using the area under the receiver operating characteristic curve (AUC). This study included 170 patients who met the inclusion criteria for cardiac surgery. The incidence of CSA-AKI was 27.06% (46/170). Multivariate logistic regression analysis indicated that preoperative heart failure, vasopressor-inotropic score, and postoperative partial pressure of oxygen were independent risk factors for the development of CSA-AKI. Serum biomarker analysis showed significant differences in BUN, Scr, NGAL, and LC levels before and after cardiac surgery. After surgery, LC levels in patients with CSA-AKI were considerably lower than those in patients without CSA-AKI. Postoperative LC showed significant predictive value for CSA-AKI, with an AUC of 0.777 (95%CI: 0.697–0.857, P < 0.001). Incorporating postoperative LC into the clinical model significantly enhanced its predictive performance. Postoperative LC can effectively predict the occurrence of CSA-AKI, and when integrated into a clinical prediction model, it enhances the model’s predictive performance for CSA-AKI.