Construction and Evaluation of a Nomogram Model for the Risk of Early Infection in Patients Receiving Triple Immunosuppression after Heart Transplantation
Objective:To analyze the risk factors of early infection in patients receiving triple immuno-suppressive regimens after heart transplantation(HT)and construct a nomogram model for predicting early infection after HT.Methods:A retrospective analysis was performed on patients who underwent HT and received postoperative triple immunosuppressive regimen from October 2012 to January 2024.Univariate analysis,Pearson correlation analysis and multivariate stepwise Logistic regression analysis were used to screen the risk factors of early infection in patients,and a nomogram prediction model was constructed by using the R language.Results:The results of multivariate stepwise Logistic regression analysis showed that preoperative hemoglobin,surgery duration,ICU length of stay,use of metoclopramide and SNPs of CYP3A5 rs776746 were risk factors of early infection.The nomogram prediction model based on the above five fac-tors performed excellent prediction with an AUROC of 0.844.The calibration curve verified by the boot-strap method was well fitted to the standard curve,and the mean absolute error was 0.041,indicating a good consistency of the model.In addition,the DCA also indicated a high level of net benefit of the mod-el.Conclusion:The nomogram prediction model constructed in this study,considered the correlation be-tween immunosuppressants and early infection after HT,can more accurately and efficiently identify high-risk populations for early infection after HT.
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