Background: Machine perfusion use has been reported to promote graft outcome in case of donation after cardiac death. Our objective was to evaluate the potential for nuclear magnetic resonance (NMR) to predict graft outcome by analyzing perfusates during machine perfusion time.
Method: We used a renal autotransplantation model mimicking deceased after cardiac death donors with pigs. Organs were subjected to 60 min of warm ischemia before the hypothermic machine preservation during 22 hr. We studied the correlation between creatinemia after transplantation and the NMR data from perfusates.
Results: A metabonomic analysis allowed us to highlight the evolution of several metabolites during perfusion: the concentration of lactate, choline, or amino acids such as valine, glycine, or glutamate increased with time, whereas there was a diminution of total glutathione during this period. The changes in these biomarkers were less severe in the group with the better outcome. Statistical analysis revealed a strong association between the level of those metabolites during machine perfusion and function recovery (Spearman rank ≥0.89; P<0.05).
Conclusion: Multivariate analysis of lesion biomarkers during kidney perfusion using NMR data could be an interesting tool to assess graft quality, particularly because analyses times (2 hr total) are compatible with clinical application.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/TP.0000000000000046 | DOI Listing |
Sci Rep
January 2025
Center for Engineering in Medicine and Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Static cold storage of donor livers at 4 °C incompletely arrests metabolism, ultimately leading to decreases in ATP levels, oxidative stress, cell death, and organ failure. Hydrogen Sulfide (HS) is an endogenously produced gas, previously demonstrated to reduce oxidative stress, reduce ATP depletion, and protect from ischemia and reperfusion injury. HS is difficult to administer due to its rapid release curve, resulting in cellular death at high concentrations.
View Article and Find Full Text PDFLiver Transpl
October 2024
Department of General Surgery, Division of Transplantation, Medical University of Vienna, Vienna, Austria.
Hypothermic oxygenated machine perfusion (HOPE) preconditions liver grafts before transplantation. While beneficial effects on patient outcomes were demonstrated, biomarkers for viability assessment during HOPE are scarce and lack validation. This study aims to validate the predictive potential of perfusate flavin mononucleotide (FMN) during HOPE to enable the implementation of FMN-based assessment into clinical routine and to identify safe organ acceptance thresholds.
View Article and Find Full Text PDFLiver Transpl
October 2024
Department of Surgery, Transplant Institute, Tampa General Hospital, University of South Florida School of Medicine, Tampa, Florida, USA.
JTCVS Open
December 2024
Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, Ohio.
Objective: To develop a model for preoperatively predicting postcardiotomy cardiogenic shock (PCCS) in patients with poor left ventricular (LV) function undergoing cardiac surgery.
Methods: From the Society of Thoracic Surgeons Adult Cardiac Database, 11,493 patients with LV ejection fraction ≤35% underwent isolated on-pump surgery from 2018 through 2019, of whom 3428 experienced PCCS. In total, 68 preoperative clinical variables were considered in machine-learning algorithms trained and optimized using scikit-learn software.
Transplantation
January 2025
Hepatobiliary Surgery and Liver Transplantation Unit, Hospital Universitario Reina Sofía, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain.
Background: Several scores have been developed to stratify the risk of graft loss in controlled donation after circulatory death (cDCD). However, their performance is unsatisfactory in the Spanish population, where most cDCD livers are recovered using normothermic regional perfusion (NRP). Consequently, we explored the role of different machine learning-based classifiers as predictive models for graft survival.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!