To Analyze The Risk Factors And Construct A Prediction Model For Pneumocystis Pneumonia After Renal Transplantation

Objective: To retrospectively analyze the clinical characteristics and risk factors of pneumocystis pneumonia after kidney transplantation in a single center,and to construct a risk prediction model,in order to provide reference for the clinical diagnosis,treatment and prevention of this disease.Materials and Methods: 1.Subjects: patients who underwent renal transplantation in the Second Affiliated Hospital of Hainan Medical University from January,2021 to December,2022 were enrolled.2.Inclusion and exclusion criteria:(1)Inclusion criteria:(1)Patients receiving renal allograft transplantation for the first time in our hospital;(2)patients with long-term conventional immunosuppressive regimen after renal transplantation;(3)Immunocompromised patients without other diseases;(4)Regular outpatient follow-up of patients.(2)Exclusion criteria:(1)patients who underwent renal transplantation in other hospitals;(2)patients with nonfirst renal transplantation or combined with other organ transplantation;(3)Immunocompromised patients with other diseases;(4)patients who did not receive regular immunosuppressive therapy after surgery and had incomplete clinical data.3.Data collection: clinical data and peripheral blood on the day of admission were collected according to the standard,and blood indicators such as C-reactive protein,procalcitonin,lactate dehydrogenase,prealbumin,albumin,and absolute lymphocyte count were measured.The data of treatment drugs and outcomes during hospitalization were recorded.4.Study grouping: according to the inclusion and exclusion criteria,134 patients were enrolled.According to the outcome of Pneumocystis jirovecii pneumonia after renal transplantation,134 patients were divided into two groups: PJP group(Pneumocystis jirovecii pneumonia after renal transplantation)and non-PJP group(non-pneumocystis jirovecii pneumonia after renal transplantation).5.Statistical methods: Measurement data in accordance with normal distribution were described by mean ± standard deviation;The non-normal distribution of measurement data was described by the median(interquartile range).The enumeration data were described by the number of cases(constituent ratio).Univariate Logistics regression analysis was used to screen out the factors with significant differences(P<0.05)between the two groups,and they were included in the multivariate Logistics regression model for analysis.The independent risk factors related to pneumocystis pneumonia after kidney transplantation were identified and used as significant variables to construct a risk prediction model.The receiver operating characteristic(ROC)curve was used to calculate the area under the curve(AUC),sensitivity and specificity of the model for predicting pneumocystis pneumonia,and to evaluate the reliability of the model.Results: 1.A total of 134 patients were enrolled in this study,including 29 patients with PJP and 105 patients without PJP.The incidence of PJP after kidney transplantation was 21.6%.PJP occurred a median of 219 days after transplantation.2.Clinical characteristics of PJP patients: The clinical symptoms and signs of 29 PJP patients were analyzed.It was found that the main clinical manifestation of PJP patients was fever on admission,often with repeated low fever,followed by cough,which was mainly characterized by dry cough.The most common imaging features were multiple exudates in both lungs,mainly interstitial,followed by pleural thickening,and consolidation and pleural effusion in severe cases.3.Univariate binary Logistic regression analysis: PJP group and non-PJP group in BMI,preoperative recombinant anti-CD25 humanized monoclonal antibody induction,serum C-reactive protein,absolute lymphocyte count,Prealbumin,Lactate dehydrogenase,Immunoglobulin G,1-3-β-D-glucan,absolute T lymphocyte count,The difference in cytomegalovirus infection between the two groups was statistically significant(P<0.05).4.Multivariate binary Logistic regression analysis showed that there were the following three independent risk factors(OR>1,P<0.05): serum LDH level(P=0.022,OR value was 1.01,95%CI: 1.00-1.01);Serum 1-3-β-D-glucan(P <0.001,OR = 1.01,95%CI: 1.00-1.02);And CMV infection(P=0.005,OR =26.80,95%CI: 2.94-349).5.Prediction model construction: According to the results of multivariate regression,the above three independent risk factors were used to construct a visual nomogram model to predict the risk of PJP.The area under the ROC curve of the model was 0.939(95%CI: 0.88105-0.98678).Sensitivity: 0.818,specificity: 0.905.It is suggested that the prediction model has high reliability.Conclusion: 1.Increased serum LDH,1-3-β-D-glucan levels,and CMV infection are independent risk factors for PJP after renal transplantation.2.The risk prediction model of PJP after renal transplantation constructed by serum LDH,1-3-β-D-glucan and CMV infection has high prediction reliability.