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Tissue Donors

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[Renal graft survival in patients transplanted from organs of deceased donors].

Revista medica del Instituto Mexicano del Seguro Social
BACKGROUND: In Mexico, out of the total number of transplants it was reported, in 2014, a frequency of 29% of deceased donor renal transplantation (DDRT). The use of kidneys from deceased elderly donors is increasing over the years. Currently, some a...

Usefulness of Delayed Introduction of Tacrolimus in Kidney Transplants Using Type-III Donors After Circulatory Death.

Transplantation proceedings
INTRODUCTION: Our study compares 2 immunosuppressive strategies to reduce tacrolimus nephrotoxicity and its risk of acute tubular necrosis: delayed introduction of tacrolimus plus thymoglobulin vs initial tacrolimus plus basiliximab on the results of...

Analysis of Kidney Donation and Its Relationship With Graft Failure of the Recipient at 1 Year.

Transplantation proceedings
INTRODUCTION: Currently, the shortage of organs available for kidney transplantation and a change in donors' and recipients' profiles (elderly, with cardiovascular risk, donors after cardiac death), it is becoming necessary to assess grafts from expa...

Graft Rejection Prediction Following Kidney Transplantation Using Machine Learning Techniques: A Systematic Review and Meta-Analysis.

Studies in health technology and informatics
Kidney transplantation is recommended for patients with End-Stage Renal Disease (ESRD). However, complications, such as graft rejection are hard to predict due to donor and recipient variability. This study discusses the role of machine learning (ML)...

Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our po...

Machine learning methods in organ transplantation.

Current opinion in organ transplantation
PURPOSE OF REVIEW: Machine learning techniques play an important role in organ transplantation. Analysing the main tasks for which they are being applied, together with the advantages and disadvantages of their use, can be of crucial interest for cli...

Machine-learning algorithms for predicting results in liver transplantation: the problem of donor-recipient matching.

Current opinion in organ transplantation
PURPOSE OF REVIEW: Classifiers based on artificial intelligence can be useful to solve decision problems related to the inclusion or removal of possible liver transplant candidates, and assisting in the heterogeneous field of donor-recipient (D-R) ma...

Artificial neural network and bioavailability of the immunosuppression drug.

Current opinion in organ transplantation
PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical, immunological and genetic variables. Artificial intelligence tools, such as artificial neural networks (ANNs) or classification and regression trees ...

[The first 50 robot-assisted donor nephrectomies : Lessons learned].

Der Urologe. Ausg. A
BACKGROUND: Minimally invasive donor nephrectomy (DN) is considered the gold standard, but the role of robot-assisted surgery is still controversial.