2 resultados para Reperfusion Injury
Resumo:
Introduction. This study aims to compare the molecular gene expression during ischemia reperfusion injury. Several surgical times were considered: in the beginning of the harvesting (T0), at the end of the cold ischemia period (T1), and after reperfusion (T2) and compared with graft dysfunction after liver transplant (OLT). Methods. We studied 54 patients undergoing OLT. Clinical, laboratory data, and histologic data (Suzuki classification) as well as the Survival Outcomes Following Liver Transplantation (SOFT) score were used and compared with the molecular gene expression of the following genes: Interleukin (IL)-1b, IL-6, tumor necrosis factor-a, perforin, E-selectin (SELE), Fas-ligand, granzyme B, heme oxygenase-1, and nitric oxide synthetase. Results. Fifteen patients presented with graft dysfunction according to SOFT criteria. No relevant data were obtained by comparing the variables graft dysfunction and histologic variables. We observed a statistically significant relation between SELE at T0 (P ¼ .013) and IL-1b at T0 (P ¼ .028) and early graft dysfunction. Conclusions. We conclude that several genetically determined proinflammatory expressions may play a critical role in the development of graft dysfunction after OLT.
Resumo:
Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.