Risk factors for invasive fungal infections after kidney transplantation and the construction of a predictive model

BackgroundPost-transplant infection is one of the main complications in the early stage of kidney transplantation. However, there is a lack of risk prediction tools to identify those at high risk of infection.ObjectiveTo investigate the risk factors for invasive fungal infections (IFIs) after kidney transplantation in a single center in Guangxi region and to construct a predictive model.MethodsA total of 997 patients who underwent kidney transplantation were selected as the research subjects. Patients with IFIs after kidney transplantation were classified into the IFIs group (n = 125), while the remaining patients formed the control group (n = 872). The clinical data of the two groups were compared, and the risk factors for IFIs after kidney transplantation were analyzed using multivariate logistic stepwise forward regression. The 997 samples were randomly divided into a training set and a validation set in an 7:3 ratio. The training set was used to build the model, while the validation set was used to evaluate the model performance.ResultsHeart failure (OR = 4.235), low EOS% level (OR = 0.825), high Cr level (OR = 1.003), and low Mg + level (OR = 0.198) are independent risk factors influencing the occurrence of IFIs after kidney transplantation (all P < 0.05). Based on these four risk factors, a nomogram prediction model was constructed. The AUC of the training set was 0.654 (95% CI: 0.591–0.717), with a specificity of 59.3% and a sensitivity of 65.3%. The AUC of the validation set was 0.677(95% CI: 0.583–0.770), with a specificity of 59.0% and a sensitivity of 76.6%.ConclusionHeart failure, low EOS%, high Cr level, and low Mg level are closely related to the occurrence of IFIs after kidney transplantation. The prediction model based on these risk factors has certain predictive value.