ABSTRACT
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.
ABSTRACT
PURPOSE: The present article aims to present the data of a Breast Cancer Team Short-Term Surgical Mission in Guinea-Bissau in the setting of the National Bissau Hospital, Hospital Nacional Simão Mendes, level A referral health structure. PATIENTS AND METHODS: Patients with breast disease have been presented to our team for in loco consultation during the total of three missions in 1 year. We have observed a total of 97 female patients with age ranging from 12 to 70 years. We performed 21 excisional biopsies, five radical surgeries, and 28 needle biopsies. RESULTS: There have been diagnosed 19 invasive breast cancer cases in stage IV, and in seven patients, the biopsy resulted in malignancy. On the recall consultation of the needle biopsied patients, just two returned and accepted the proposed treatment. Major issue has been the lack of trained pathology technicians for adequate sampling conditioning, a fact that led to a poor quality of 18 samples. CONCLUSION: Access to surgical care is disparate across the world, and short-term surgical missions are often call-in action to deliver not only patient care but also local staff training. Complex disease management, such as cancer, may create several problems being conditioned by the lack of basic resources required. In Guinea-Bissau, a poor country with very few inhabitants, the need to implement an anticancer national strategy is urgent but seems feasible. Any action should prioritize local team training and enhance specialization. No external intervention can provide any long-term benefit for patients if they are detached from local health workers.
