2 research outputs found

    Transplant arteriosclerosis: an enigmatic disease due to a misnomer

    Full text link
    Solid organ transplantation across the allogeneic barrier, pioneered by Thomas Starzl, has by now become a common medical procedure. Unfortunately, the number of donor organs lost due to transplant arteriosclerosis (chronic rejection), remains significant and unchanged for decades. We argue that designation of transplant arteriosclerosis as chronic rejection, and its classification as a delayed long-lasting reaction of recipient immune effectors against donor alloantigens have given us a wrong impression that we have identified the necessary cause/pathogenesis of the tissue pathology. However, whatever treatment options we have in the anti-rejection toolbox, despite their success in treating classical rejection, do not work for the transplant arteriosclerosis. Yet, the scientific community has continued to conceptualize and approach the pathology within the alloimmunity model. Due to unproductive research from the alloimmunity and rejection perspective, the number of transplanted hearts lost due to this pathology today is almost the same as it was fifty years ago. We believe that this phenomenon falls under the rubric of linguistic relativity, and that language we chose to name the disease has restricted our cognitive ability to solve the problem. While the initial perception of the transplant arteriosclerosis as chronic rejection was logical and scientific, the subsequent experience revealed that such perception and approach have been fruitless, and likely are incorrect. Considering our tragic failure to prevent and treat the delayed arterial pathology of donor organs using all available knowledge on alloimmunity and rejection, we must finally disassociate the former from the latter. The only way to start this uncomfortable process is to change the words we are using; particularly, the words we chose to name the disease. We have to step out of the alloimmunity rejection box.Comment: 19 pages, 2 figure

    Various Medical Aspects of Liver Transplantation and its Survival Prediction using Machine Learning Techniques

    No full text
    corecore