Development and Internal Validation of a Nomogram for Predicting Acute Kidney Injury After Cardiac Valve Surgery Using the Serum Uric Acid-to-Albumin Ratio

利用血清尿酸/白蛋白比值构建预测心脏瓣膜手术后急性肾损伤的列线图并进行内部验证

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Abstract

BACKGROUND: The serum Uric Acid-to-Albumin Ratio (sUAR) is a novel inflammatory indicator. We aimed to construct and validate a prediction model for acute kidney injury (AKI) following cardiac valve surgery (CVS) based on the preoperative sUAR. METHODS: We retrospectively collected clinical data from adult patients undergoing CVS with cardiopulmonary bypass at the Heart Center of Henan Provincial People's Hospital between December 2020 to December 2021. The primary outcome was postoperative AKI, defined according to the KDIGO creatinine criteria. Patients were categorized as either AKI or non-AKI based on this outcome. Multivariate logistic regression to identify independent risk factors. A nomogram model was developed. The receiver operating characteristic (ROC) curve assessed discrimination. The calibration curve and Hosmer-Lemeshow test evaluated calibration. Clinical practicability was assessed through decision curve analysis (DCA) and clinical impact curve (CIC). The Bootstrap method was used for internal verification. RESULTS: A total of 440 patients were enrolled, and the incidence of AKI was 33.4%. Multivariate analysis revealed that sUAR (per μmol/g, OR=1.467, 95% CI 1.311-1.642, P<0.001), age (per 10 years, OR=1.612, 95% CI 1.261-2.062, P<0.001), atrial fibrillation (OR=2.485, 95% CI 1.573-3.924, P<0.001), hemoglobin (per g/L, OR=0.985, 95% CI 0.973-0.998, P=0.025) were the independent risk factors. The nomogram based on sUAR achieved an area under the curve (AUC) of 0.779 (95% CI 0.734-0.824, P<0.001) for predicting AKI. The average AUC after internal validation of the nomogram model was 0.776 (95% CI 0.767-0.779). The calibration curve and Hosmer-Lemeshow test indicated that the predicted and observed results agreed well, while the DCA and CIC curves demonstrated favorable clinical applicability within a specific threshold range. CONCLUSION: The prediction model incorporating sUAR provides reliable discrimination and clinical utility for assessing AKI risk following CVS.

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