Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a prevalent complication with poor outcomes, and its early prediction remains a challenging task. Currently available biomarkers for acute kidney injury (AKI) include serum cystatin C (sCysC) and urinary N-acetyl-β-D-glucosaminidase (uNAG). Widely used biomarkers for assessing cardiac function and injury are N-terminal pro B-type natriuretic peptide (NT-proBNP) and cardiac troponin I (cTnI). In light of this, our study aimed to evaluate the effectiveness of these four biomarkers in predicting CSA-AKI. Methods: This prospective observational study enrolled adult patients who had undergone cardiac surgery. The clinical prediction model for CSA-AKI was developed using the least absolute shrinkage and selection operator (LASSO) regression method. The model’s performance was assessed using the area under the curve of the receiver operating characteristic (ROC-AUC), decision curve analysis (DCA), and calibration curves. Furthermore, a separate validation cohort was constructed to externally validate the prediction model. Additionally, a risk nomogram was created to facilitate risk assessment and prediction. Results: In the modeling cohort consisting of 689 patients and the validation cohort consisting of 313 patients, the total incidence of CSA-AKI was 33.4%. The LASSO regression identified several predictors, including age, history of hypertension, baseline serum creatinine (sCr), coronary artery bypass grafting combined with valve surgery, cardiopulmonary bypass duration, preoperative albumin, hemoglobin, postoperative NT-proBNP, cTnI, sCysC, and uNAG. The constructed clinical prediction model demonstrated robust performance, with a ROC-AUC of 0.830 (0.800–0.860) in the modeling cohort and 0.840 (0.790–0.880) in the validation cohort. Furthermore, both calibration and DCA indicated good model fit and clinical benefit. Conclusions: This study demonstrates that incorporating the immediately postoperative renal biomarkers, sCysC and uNAG, along with the cardiac biomarkers, NT-proBNP and cTnI, into a clinical early prediction model can significantly enhance the accuracy of predicting CSA-AKI. These findings suggest that a comprehensive approach combining both renal and cardiac biomarkers holds promise for improving the early detection and prediction of CSA-AKI.

The Intra-Aortic Balloon Pump (IABP) is a widely utilized technique to provide circulatory support for critically ill patients with cardiac dysfunction. While IABP therapy offers clinical benefits, the placement of an IABP catheter can potentially lead to a range of complications in certain high-risk patients. This case report presents a rare instance of progressive jaundice associated with IABP implantation. The patient was a 56-year-old female who had undergone cardiac valve surgery due to rheumatic combined valve disease. She subsequently developed postoperative low cardiac output syndrome, necessitating the implementation of IABP support. However, the patient exhibited a rapid deterioration in jaundice, coupled with aberrant liver function and suspicion of concurrent pancreatitis. Further thoracoabdominal computed tomography (CT) examinations revealed that when the IABP balloon was fully inflated, the aorta was completely occluded. The diagnosis of hepatic impairment was suspected to likely result from a reduced hepatic blood flow caused by obstruction of the celiac trunk related to the occlusive IABP balloon. Therefore, the IABP was removed, leading to a gradual amelioration of jaundice symptoms as well as bilirubin levels. This case advocates a reevaluation of the strategy for selecting the size of the IABP balloon, particularly in high-risk patient populations. A marginally smaller balloon size may be warranted to mitigate the risk of vascular-related complications. In cases presenting with progressive jaundice and hepatic impairment following IABP insertion, proactive imaging studies should be promptly conducted to ascertain their correlation with the IABP placement. If there is suspicion of visceral ischemia associated with the IABP balloon, immediate removal of the device should be undertaken to prevent irreversible adverse events.

Background Cardiac surgery-associated acute kidney injury (CS-AKI) is common and associated with poor outcomes. Early prediction of CS-AKI remains challenging. Currently available biomarkers for AKI are serum cystatin C (sCysC) and urinary N-acetyl-β-D-glucosaminidase (uNAG), and common cardiac biomarkers are N-terminal pro B-type natriuretic peptide (NT-proBNP) and cardiac troponin I (cTNI). This study aimed to evaluate the efficacy of these biomarkers in predicting CS-AKI. Methods Adult patients after cardiac surgery were included in this prospective observational study. The clinical prediction model of CS-AKI was established by the least absolute shrinkage and selection operator (LASSO) regression, and the discriminative ability of the model was evaluated by using the area under the curve of the receiver operating characteristic (AUC-ROC), decision curve analysis (DCA), and calibration curves. The risk nomogram was plotted, and the validation cohort was constructed for external validation. Results In the modeling cohort of 689 and the validation cohort of 313, the incidence of CS-AKI was 29.2% and 39.6%, respectively. Predictors screened by LASSO included age, history of hypertension, baseline serum creatinine, coronary artery bypass grafting combined with valve surgery, cardiopulmonary bypass duration, preoperative albumin, hemoglobin, postoperative NT-proBNP, cTNI, sCysC, and uNAG. The ROC-AUC of the constructed clinical prediction model in the modeling cohort and validation cohort were 0.830 (0.800–0.860) and 0.840 (0.790–0.880), respectively, and the calibration and DCA showed good fit and clinical benefit. Conclusions A clinical early prediction model consisting of the immediately postoperative renal biomarkers sCysC and uNAG and the cardiac biomarkers NT-proBNP and cTNI could improve the predictive accuracy of CS-AKI.