Echocardiography (Mount Kisco, N.Y.) · 2026
Development of a Preoperative Transthoracic Echocardiography-Based Nomogram for Predicting 1-Year Cardiovascular Events in End-Stage Renal Disease Kidney Transplant Recipients.
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Pan Meishu, Xu Lifang, Cai Yongzhi, Li Yue, Deng Wenze, Ou Ailing, Gan Shuilian, Zhou Yingchuan, Wu Ji
Аннотация
BACKGROUND: Kidney transplantation (KT) is optimal therapy for end-stage renal disease (ESRD), yet cardiovascular events (CVEs) are the top cause of morbidity and mortality in transplant recipients. We aimed to build a preoperative transthoracic echocardiography (TTE)-based predictive model combined with clinical and laboratory indicators to stratify post-transplant cardiovascular risk.
METHODS: This single-center cohort enrolled 547 ESRD patients receiving KT from 2021 to 2022. Preoperative TTE, clinical and lab data were collected, with 1-year post-transplant CVEs as the primary endpoint. LASSO and multivariate logistic regression screened independent risk factors; ROC, calibration curves and decision curve analysis (DCA) validated model performance.
RESULTS: Overall 17.55% (96/547) patients developed 1-year CVEs. Interventricular septal thickness at end-diastole (IVSTd), pulmonary hypertension (PH), aortic valve calcification (AVC) and diabetes history were independent risk factors. The training set AUC reached 0.776 (sensitivity 61.8%, specificity 79.4%, 95%CI 0.711-0.841), and the testing set AUC was 0.749 (95%CI 0.618-0.880). Calibration curves showed favorable consistency, and DCA proved stable clinical net benefit within the 7%-68% threshold range.
CONCLUSIONS: One-year post-transplant CVE incidence remains high. IVSTd, PH, AVC and diabetes are independent predictors. This TTE-integrated model has reliable discrimination and clinical value for non-invasive cardiovascular risk stratification in KT candidates.
METHODS: This single-center cohort enrolled 547 ESRD patients receiving KT from 2021 to 2022. Preoperative TTE, clinical and lab data were collected, with 1-year post-transplant CVEs as the primary endpoint. LASSO and multivariate logistic regression screened independent risk factors; ROC, calibration curves and decision curve analysis (DCA) validated model performance.
RESULTS: Overall 17.55% (96/547) patients developed 1-year CVEs. Interventricular septal thickness at end-diastole (IVSTd), pulmonary hypertension (PH), aortic valve calcification (AVC) and diabetes history were independent risk factors. The training set AUC reached 0.776 (sensitivity 61.8%, specificity 79.4%, 95%CI 0.711-0.841), and the testing set AUC was 0.749 (95%CI 0.618-0.880). Calibration curves showed favorable consistency, and DCA proved stable clinical net benefit within the 7%-68% threshold range.
CONCLUSIONS: One-year post-transplant CVE incidence remains high. IVSTd, PH, AVC and diabetes are independent predictors. This TTE-integrated model has reliable discrimination and clinical value for non-invasive cardiovascular risk stratification in KT candidates.