Predictive value of hypothermic machine perfusion parameters combined perfusate biomarkers in deceased donor kidney transplantation / 中华医学杂志(英文版)

BACKGROUND@#Delayed graft function (DGF) is the main cause of renal function failure after kidney transplantation. This study aims at investigating the value of hypothermic machine perfusion (HMP) parameters combined with perfusate biomarkers on predicting DGF and the time of renal function recovery after deceased donor (DD) kidney transplantation.@*METHODS@#HMP parameters, perfusate biomarkers and baseline characteristics of 113 DD kidney transplantations from January 1, 2019 to August 31, 2019 in the First Affiliated Hospital of Xi'an Jiaotong University were retrospectively analyzed using univariate and multivariate logistic regression analysis.@*RESULTS@#In this study, the DGF incidence was 17.7% (20/113); The multivariate logistic regression results showed that terminal resistance (OR: 1.879, 95% CI 1.145-3.56) and glutathione S-transferase (GST)(OR = 1.62, 95% CI 1.23-2.46) were risk factors for DGF; The Cox model analysis indicated that terminal resistance was an independent hazard factor for renal function recovery time (HR = 0.823, 95% CI 0.735-0.981). The model combining terminal resistance and GST (AUC = 0.888, 95% CI: 0.842-0.933) significantly improved the DGF predictability compared with the use of terminal resistance (AUC = 0.756, 95% CI 0.693-0.818) or GST alone (AUC = 0.729, 95% CI 0.591-0.806).@*CONCLUSION@#According to the factors analyzed in this study, the combination of HMP parameters and perfusate biomarkers displays a potent DGF predictive value.

Prognostic utility of LifePort parameters plus perfusate biomarkers during deceased donor kidney transplantation / 中华器官移植杂志

Objective:To explore the prognostic utility of LifePort perfusion parameters plus perfusate biomarkers for predicting delayed graft function(DGF)and recovery time during deceased donor kidney transplantation(KT).Methods:From January 1, 2019 to August 31, 2019, retrospective analysis was performed for clinical data of 113 KT recipients. Based upon whether or not DGF occurred within 3 months, they were divided into two groups of DGF group(20 cases)and non-DGF (93 cases). Two groups were compared using LifePort perfusion parameters, biomarker concentrations, incidence of DGF and kidney recovery time. Statistical analysis was performed.Results:The incidence of DGF was 17.7%(20/113); Multivariate Logistic regression results indicated that terminal resistance(OR 1.879, 95% CI 1.145~3.56)and glutathione S-transferase(GST)(OR 1.62, 95% CI 1.23~2.46)were independent risk factors for DGF; Cox hazard model revealed that terminal resistance was a risk factor for recovery time of renal function(HR=0.823, 95% CI 0.735~0.981). The model combining terminal resistance and GST(AUC=0.888, 95% CI 0.842~0.933)significantly improved the predictive efficacy for DGF as compared with using terminal resistance(AUC=0.756, 95% CI 0.693~0.818)or GST alone(AUC=0.729, 95% CI 0.591~0.806).Conclusions:Combining LifePort perfusion parameters and fluid biomarkers can improve the predictive utility of DGF.

Effects of SSRI Antidepressants on Attentional Bias toward Emotional Scenes in First-Episode Depressive Patients: Evidence from an Eye-Tracking Study

Objective@#Attentional biases toward emotional scenes may represent vulnerability and maintenance factors in depression. Antidepressant therapy may improve cognitive function and reduce depression, and is considered as the mechanism of action of antidepressants. Therefore, we conducted an eye-tracking test to examine whether selective serotonin re-uptake inhibitor (SSRI) antidepressants can reduce negative attentional biases and elicit clinical responses in depression. @*Methods@#Twenty first-episode depressive patients freely viewed three types of pictures that depicted different emotional scenes (i.e., positive-control, neutral-control, and negative-control) for 4,000 ms while their eye movements were monitored. The attentional bias to different emotional scenes was assessed before and after eight weeks of SSRI treatment using the eye-tracking method. The control group included a group of healthy individuals. @*Results@#The results revealed that first-episode depressive patients oriented their gaze more frequently to negative images and less to happy images, compared to controls. Importantly, the attentional bias in depressive patients was regulated after eight weeks of SSRI treatment. Patients showed an increased tendency to fixate on positive images and a decreased tendency to focus on negative images. @*Conclusion@#This suggests that SSRI antidepressants decrease vulnerability to negative images, while having an effect on attention in respect to positive images.

Advancement of research on ferroptosis in acute kidney injury / 器官移植

Acute kidney injury (AKI) is often associated with organ donation and renal transplantation, which leads to an increase of fatality rate, hospitalization time and hospitalization costs. In recent years, studies have shown that ferroptosis is closely related to AKI, but the exact molecular biological mechanism has not been clarified, which need more research. In this article, the role of ferroptosis in AKI was reviewed from the aspects of ferroptosis related biomarkers and biological reactions, in order to find a new possible direction for the prevention and treatmentof AKI.

The efficiency study on different scoring models in predicting delayed graft function after renal transplantation / 器官移植

Objective To analyze the prediction efficiency of scoring models at home and abroad on delayed graft function (DGF) after renal transplantation in China. Methods The clinical data of 112 donors and 220 recipients undergoing renal transplantation were prospectively analyzed. The DGF predicted by KDRI model, Jeldres model, and model of our center was compared with actual DGF incidence of renal transplant recipients. The prediction efficiency of each model was analyzed. The predictive accuracy was compared by the area under curve (AUC) of receiver operating characteristic (ROC) curve. Results The DGF incidence of 220 renal transplant recipients was 14.1% (31/220). DGF prediction using KDRI model showed that 41 cases were high risk donors, the AUC was 0.57, the sensitivity was 0.37, the specificity was 0.66, and the positive predictive value was 22%. DGF prediction using Jedres model showed that 22 cases were high risk recipients, the AUC was 0.56, the sensitivity was 0.13, the specificity was 0.92 and the positive predictive value was 20%. DGF prediction using the model of our center showed that 25 cases were high risk donors, the AUC was 0.80, the sensitivity was 0.53, the specificity was 0.84, the positive predictive value was 40%. Conclusions Compared with the KDRI and Jedres models, the prediction model of our center has higher AUC and sensitivity with a better prediction efficiency on DGF. Therefore, it is a suitable evaluation system of donors from donation after citizen's death in Chinese.