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Objectives: To evaluate the efficacy and safety of low-dose trimethoprim (TMP)-sulfamethoxazole (SMX) (TMP-SMX) as the primary prophylaxis for Pneumocystis jirovecii pneumonia (PJP) in adult recipients of kidney transplantation. Methods: Three kinds of prescriptions in kidney recipients were documented, including 20 mg TMP/100 mg SMX oral daily, 20 mg TMP/100 mg SMX oral every other day, and nonprophylaxis. The primary outcome was the incidence of PJP in the first 180 days of follow-up after kidney transplantation. The secondary outcomes were changes in renal and liver function. Results: Among the 1469 recipients, 1066 (72.56%) received 20 mg TMP/100 mg SMX daily, 127 (8.65%) received 20 mg TMP/100 mg SMX every other day, and 276 (18.79%) did not have prophylaxis prescription. The 276 recipients in the nonprophylaxis group had 124.92 person-years of follow-up, during which PJP occurred in 29 patients, for an incidence rate of 23.21 (95% confidence interval 15.76-32.72) per 100 person-years. The TMP-SMX daily group and the TMP-SMX every other day group had 524.89 and 62.07 person-years of follow-up, respectively, with no occurrence of PJP. There was no significant difference among the three groups in changes in renal and liver function (P >0.05, respectively). A total of 111 recipients in each group were enrolled in the propensity score matching analysis. It was revealed that the 111 nonprophylaxis recipients had 51.27 person-years of follow-up and 10 PJP cases. Prophylaxis was considered effective because there was a significant difference between the three groups (P

BackgroundRenal ischemia-reperfusion injury (IRI) is an inevitable occurrence during kidney transplantation. Mitophagy, ferroptosis, and the associated immune microenvironment (IME) have been shown to play important roles in renal IRI. However, the role of mitophagy-associated IME genes in IRI remains unclear. In this study, we aimed to construct a prediction model of IRI prognosis based on mitophagy-associated IME genes.MethodThe specific biological characteristics of the mitophagy-associated IME gene signature were comprehensively analyzed using public databases such as GEO, Pathway Unification, and FerrDb. Correlations between the expression of prognostic genes and immune-related genes and IRI prognosis were determined by Cox regression, LASSO analysis, and Pearson’s correlation. Molecular validation was performed using human kidney 2 (HK2) cells and culture supernatant as well as the serum and kidney tissues of mice after renal IRI. Gene expression was measured by PCR, and inflammatory cell infiltration was examined by ELISA and mass cytometry. Renal tissue damage was characterized using renal tissue homogenate and tissue sections.ResultsThe expression of the mitophagy-associated IME gene signature was significantly correlated with IRI prognosis. Excessive mitophagy and extensive immune infiltration were the primary factors affecting IRI. In particular, FUNDC1, SQSTM1, UBB, UBC, KLF2, CDKN1A, and GDF15 were the key influencing factors. In addition, B cells, neutrophils, T cells, and M1 macrophages were the key immune cells present in the IME after IRI. A prediction model for IRI prognosis was constructed based on the key factors associated with the mitophagy IME. Validation experiments in cells and mice indicated that the prediction model was reliable and applicable.ConclusionWe clarified the relationship between the mitophagy-related IME and IRI. The IRI prognostic prediction model based on the mitophagy-associated IME gene signature provides novel insights on the prognosis and treatment of renal IRI.

ObjectiveTo investigate the risk factors of infectious diseases in adult kidney transplantation recipients and to establish a simple and novel nomogram to guide the prophylactic antimicrobial therapy.MethodsPatients who received kidney transplantation between January 2018 and October 2021 were included in the study and were divided into a training and a testing set at a 1:1 ratio. Risk factors correlated to infectious diseases were selected using a Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The prediction model was built by incorporating the variables selected by the LASSO model into a logistic regression equation. Calibration curves and receiver operating characteristic (ROC) curves were also applied to assess the model calibration and discrimination. A nomogram consisting of the selected factors was established to provide individualized risks of developing infections. Decision curve analysis (DCA) was adopted to estimate the net benefit and reduction in interventions for a range of clinically reasonable risk thresholds.ResultsIn all, 863 adult kidney recipients were included in the study, and 407 (47.16%) of them developed infectious diseases during the 3-year follow–up period. A total of 8 variables were selected using LASSO regression and were retained for subsequent model construction and infection prediction. The area under the curve (AUC) was 0.83 and 0.81 in the training and testing sets, with high F scores of 0.76 and 0.77, sensitivity of 0.76 and 0.81, and specificity of 0.88 and 0.74, respectively. A novel nomogram was developed based on 8 selected predictors (requirement for albumin infusion, requirement for red blood cell infusion, triglyceride, uric acid, creatinine, globulin, neutrophil percentage, and white blood cells). The net benefit indicated that the nomogram would reduce unnecessary interventions at a wide range of threshold probabilities in both sets.ConclusionsAdult kidney transplantation recipients are high-risk hosts for infectious diseases. The novel nomogram consisting of 8 factors reveals good predictive performance and may promote the reasonable antimicrobial prescription. More external validations are required to confirm its effectiveness for further clinical application.