Construction of predictive model for renal allograft rejection based on clinical multimodal ultrasound features / 中华超声影像学杂志

ABSTRACT

Objective:To construct a nomogram for predicting the occurrence of renal allograft rejection based on the combination of multimodal ultrasound features and clinical data.Methods:The ultrasound findings and clinical characteristics of 102 patients with transplanted kidneys who underwent renal biopsy in the General Hospital of Eastern Theater Command from January 2021 to March 2022 were analyzed retrospectively. Patients were divided into rejection group and nephropathy group according to Banff transplant kidney pathological diagnostic criteria (2017 edition). Multivariate Logistic regression was used to screen independent predictors related to the status of rejection, and nomograms were drawn based on the independent predictors. The internal validation of the nomogram was carried out by Bootstrap method, and the ROC curve and calibration curve were utilized to evaluate the diagnostic efficacy of the nomogram.Results:Blood urea nitrogen concentration, renal aortic resistance index, absolute time to peak and cortical echo were independent predictors of rejection( OR=1.073, 1.078, 0.843, 0.205; all P<0.05). Incorporating blood urea nitrogen concentration, renal aortic resistance index, absolute peak time and cortical echo, the nomogram was constructed. The AUC of the predictive model was 0.814(95% CI=0.722-0.905) and the cutoff value was 0.67(corresponding to a total score of about 157 points). Both internal verification (AUC=0.788) and calibration curve demonstrated the clinical usefulness of the nomogram. Conclusions:The nomogram for predicting the occurrence of rejection in renal allograft patients based on multimodal ultrasound features and clinical data can guide the individualized treatment of patients with renal dysfunction.