Pancreas Rejection in the Artificial Intelligence Era: New Tool for Signal Patients at RiskEmanuel Vigia, Luís Ramalhete, Rita A. Ribeiro et al.|Journal of Personalized Medicine|2023 INTRODUCTION: Pancreas transplantation is currently the only treatment that can re-establish normal endocrine pancreatic function. Despite all efforts, pancreas allograft survival and rejection remain major clinical problems. The purpose of this study was to identify features that could signal patients at risk of pancreas allograft rejection. METHODS: We collected 74 features from 79 patients who underwent simultaneous pancreas-kidney transplantation (SPK) and used two widely-applicable classification methods, the Naive Bayesian Classifier and Support Vector Machine, to build predictive models. We used the area under the receiver operating characteristic curve and classification accuracy to evaluate the predictive performance via leave-one-out cross-validation. RESULTS: Rejection events were identified in 13 SPK patients (17.8%). In feature selection approach, it was possible to identify 10 features, namely: previous treatment for diabetes mellitus with long-term Insulin (U/I/day), type of dialysis (peritoneal dialysis, hemodialysis, or pre-emptive), de novo DSA, vPRA_Pre-Transplant (%), donor blood glucose, pancreas donor risk index (pDRI), recipient height, dialysis time (days), warm ischemia (minutes), recipient of intensive care (days). The results showed that the Naive Bayes and Support Vector Machine classifiers prediction performed very well, with an AUROC and classification accuracy of 0.97 and 0.87, respectively, in the first model and 0.96 and 0.94 in the second model. CONCLUSION: Our results indicated that it is feasible to develop successful classifiers for the prediction of graft rejection. The Naive Bayesian generated nomogram can be used for rejection probability prediction, thus supporting clinical decision making.
Une présentation rare du syndrome d’intolérance au greffon renal : la pemphigoïde bulleuseBullous pemphigoid is an autoimmune bullous cutaneous disease. We report the case of a 60 year-old male patient whose kidney allograft failed and was on hemodialysis for the previous 16 months. After tapering immunosuppressive medication, he presented simultaneous bullous eruption and kidney allograft intolerance syndrome. Investigation showed a positive BP180 anti-basement membrane zone antibody and skin biopsy was consistent with bullous pemphigoid. The patient was treated with corticotherapy and bullous pemphigoid resolved. The development of new onset diabetes and concerns over long term immunosuppression, halted the decision to continue corticotherapy and the patient underwent graft nephrectomy, with resolution of the kidney allograft intolerance syndrome without recurrence of the bullous disease. The occurrence of bullous pemphigoid in patients with failed renal allograft is rare, with only eleven cases reported in literature. This case illustrates how graft nephrectomy can provide a definitive cure to bullous pemphigoid in this setting.
Rapid FTIR Spectral Fingerprinting of Kidney Allograft Perfusion Fluids Distinguishes DCD from DBD Donors: A Pilot Machine Learning StudyBackground/Objectives: Rapid, objective phenotyping of donor kidneys is needed to support peri-implant decisions. Label-free Fourier-transform infrared (FTIR) spectroscopy of static cold-storage Celsior® perfusion fluid can discriminate kidneys recovered from donation after circulatory death (DCD) versus donation after brain death (DBD). Methods: Preservation solution from isolated kidney allografts (n = 10; 5 DCD/5 DBD) matched on demographics was analyzed in the Amide I and fingerprint regions. Several spectral preprocessing steps were applied, and feature extraction was based on the Fast Correlation-Based Filter. Support vector machines and Naïve Bayes were evaluated. Unsupervised structure was assessed based on cosine distance, multidimensional scaling, and hierarchical clustering. Two-dimensional correlation spectroscopy (2D-COS) was used to examine band co-variation. Results: Donor cohorts were well balanced, except for higher terminal serum creatinine in DCD. Quality metrics were comparable, indicating no systematic technical bias. In Amide I, derivatives improved classification, but performance remained modest (e.g., second derivative with feature selection yielded an area under the curve (AUC) of 0.88 and an accuracy of 0.90 for support vector machines; Naïve Bayes reached an AUC of 0.92 with an accuracy of 0.70). The fingerprint window was most informative. Naïve Bayes with second derivative plus feature selection identified bands at ~1202, ~1203, ~1342, and ~1413 cm−1 and achieved an AUC of 1.00 and an accuracy of 1.00. Unsupervised analyses showed coherent grouping in the fingerprint region, and 2D correlation maps indicated coordinated multi-band changes. Conclusions: Performance in this 10-sample pilot should be interpreted cautiously, as perfect leave-one-out cross-validation (LOOCV) estimates are vulnerable to overfitting. The findings are preliminary and hypothesis-generating, and they require confirmation in larger, multicenter cohorts with a pre-registered analysis pipeline and external validation.
Prognostic factors of survival in second allogeneic hematopoietic transplantationAllogeneic stem cell transplantation (alloSCT) remains a potentially curative treatment for patients with hematologic malignancies. Nevertheless, relapse and graft failure continue to be major barriers to long-term success. In these high-risk situations, a second alloSCT may represent the only curative option, although outcomes are frequently compromised by high non-relapse mortality and disease progression. Despite improvements in conditioning regimens, donor availability, and supportive care strategies, clinical results remain suboptimal and underscore the importance of careful patient selection.In this study, we report the 15-year experience of our institution-a national reference center for alloSCT in Spain-in managing patients undergoing a second alloSCT. Our objective is to evaluate relevant clinical and transplant-related factors associated with survival outcomes. Ultimately, we aim to enhance the selection process and contribute to a more personalized approach to 2nd-alloSCT, helping clinicians make better-informed decisions about which patients are most likely to benefit from this high-risk but potentially life-saving procedure.
Combined lung-kidney transplantation: First case in PortugalA significant dysfunction of another organ is usually considered an absolute contraindication for lung transplantation, unless multiorgan transplantation is indicated and practical, as is the case of combined lung-kidney transplantation. Few cases of combined lung-kidney transplantation have been described in the literature; however, it is known that, in certain cases, it is the only way to offer an opportunity to selected patients with renal and lung dysfunction. The authors are not aware of any previously published case of a patient receiving both extracorporeal membrane oxygenation and continuous venovenous hemodiafiltration as a bridge for combined kidney-lung transplantation. The authors present the first case of combined lung-kidney transplantation performed in Portugal.