关键词:

心脏移植 , 急性肾损伤 , 预测模型 , 列线图

Abstract:

Objective To analyze and identify the risk factors for acute kidney injury（AKI）afterhearttransplantation（HT）and to develop a predictive model for early postoperative AKI in HT recipients. Methods A retrospective analysis was conducted on clinical data of HT recipients at Zhongnan Hospital of Wuhan Universityfrom January 2021 to October 2025. Patients were divided into AKI and non-AKI groups based on whether AKI occurred within 7 days post-surgery. Lasso regression and multivariate Logistic regression were used to screen forinfluencing factors. A nomogram prediction model was established using R language. The accuracy and discriminationof the model were evaluated using the area under the receiver operating characteristic curve（AUC-ROC）and calibration curves. Results Multivariate Logistic regression analysis showed that age（OR ＝ 3.848，95% CI ＝ 1.321 ～ 11.211），preoperative mean pulmonary artery pressure（MPAP）（OR ＝ 3.775，95% CI ＝ 1.564 ～ 9.111），preoperative serum creatinine（Scr）（OR ＝ 2.027，95% CI ＝ 1.239 ～ 3.315），and postoperative central venouspressure（CVP）（OR ＝ 2.376，95% CI ＝ 1.059 ～ 5.332）were four independent risk factors for AKI after hearttransplantation. The AUC of the nomogram model was 0.910（95% CI ＝ 0.848 ～ 0.971），and the calibration curveapproximated a straight line with a slope close to 1. Conclusion The model developed in this study for predicting AKI after HT demonstrates good reliability and clinical applicability. 

Key words:

Heart Transplantation, Acute Kidney Injury, Predictive Model, Dynamic Nomogram