Du R, Wang L, Wang Y, Zhao Z, Zhang D, Zuo S. AKI prediction model in acute aortic dissection surgery: nomogram development and validation.
Front Med (Lausanne) 2025;
12:1562956. [PMID:
40443509 PMCID:
PMC12119464 DOI:
10.3389/fmed.2025.1562956]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2025] [Accepted: 04/28/2025] [Indexed: 06/02/2025] Open
Abstract
Objectives
This multicenter study developed and internally validated a biomarker-enhanced risk prediction nomogram integrating hemodynamic parameters and novel urinary biomarkers to stratify postoperative acute kidney injury (AKI) risks in patients undergoing emergency surgical repair for acute Stanford Type A aortic dissection (ATAAD).
Methods
A cohort of 1,277 patients from the China Aortic Dissection Alliance (CADA) registry was chronologically split into derivation (70%, n = 894) and validation (30%, n = 383) sets. LASSO regression with 10-fold cross-validation (λ1SE criterion) was applied to identify non-redundant predictors from 34 candidate variables (e.g., cardiac dysfunction [LVEF <50% or INTERMACS 1-3]) and elevated urinary biomarkers. Multivariable logistic regression refined these predictors to establish independent risk factors for the final nomogram. Model performance was evaluated using the concordance index (C-index), area under the receiver operating characteristic curve (AUC-ROC), calibration plots (Brier score and Hosmer-Lemeshow test), and decision curve analysis (DCA) to quantify clinical utility.
Results
Multivariable analysis identified seven independent predictors of postoperative AKI: preexisting cardiac dysfunction (adjusted odds ratio [aOR] = 2.17; 95% CI: 1.68-3.56), microvascular complications of diabetes (aOR = 3.26; 2.71-4.34), baseline renal impairment (aOR = 1.72; 1.36-3.29), blood urea nitrogen (BUN) ≥ 20 mg/dL (aOR = 2.19; 1.57-3.64), glomerular filtration rate (GFR) < 90 mL/min/1.73 m2 (aOR = 1.47; 1.02-2.13), serum creatinine >1.3 mg/dL (aOR = 3.28; 2.58-3.75), and peripheral vasculopathy (aOR = 1.78; 1.12-2.32). The model demonstrated strong discrimination (training AUC-ROC: 0.830 [0.802-0.858]; internal validation AUC-ROC: 0.786 [0.737-0.834]), calibration (Brier scores: 0.138 training, 0.141 validation), and clinical utility (net reclassification improvement [NRI] = 0.21, p = 0.001), with optimal decision thresholds at 40-60% probability.
Conclusion
The nomogram demonstrates superior preoperative discriminative accuracy in AKI following ATAAD repair surgery. External validation via the VASCUNET registry is planned to confirm generalizability.
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