推进移植精准医学的患者监测、诊断和治疗策略

Alexandre Loupy, Marta Sablik, Kiran Khush, Peter P Reese
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引用次数: 0

摘要

移植医学面临着巨大的挑战,因为患者需要终身免疫抑制来防止移植排斥。迄今为止,免疫抑制方案虽然在预防急性排斥反应方面相当有效,但会导致许多健康并发症,影响生活质量和患者生存。需要向个体化免疫抑制转变,以改善同种异体移植物的健康,减少长期不良反应,并优化移植后结果。这种必要性推动了移植后监测和诊断的进步。创新的监测生物标志物和新的诊断模式已经被开发出来,以推进移植护理,其中许多显示出广泛临床实施的希望。随着人工智能的进步,算法有可能整合免疫系统和同种异体移植健康的多维数据,提供移植状态的全面视图。本系列文章强调了移植后免疫抑制、监测和诊断的现状,强调了新兴创新在个性化同种异体移植和患者护理方面的变革作用。它们的影响可能延伸到异种移植,进一步扩大它们重新定义移植医学的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing patient monitoring, diagnostics, and treatment strategies for transplant precision medicine
Transplant medicine faces substantial challenges, as patients require lifelong immunosuppression to prevent graft rejection. Immunosuppressive regimens to date, while reasonably effective at preventing acute rejection, cause numerous health complications, compromising quality of life and patient survival. A shift towards personalised immunosuppression is needed to improve allograft health, reduce long-term adverse effects, and optimise post-transplant outcomes. This necessity has driven advancements in post-transplant monitoring and diagnostics. Innovative monitoring biomarkers and novel diagnostic modalities have been developed to advance transplant care, with many showing promise for widespread clinical implementation. With advances in artificial intelligence, algorithms have the potential to integrate multidimensional data on the immune system and allograft health, offering a comprehensive view of transplant status. This Series paper highlights the state of post-transplant immunosuppression, monitoring, and diagnostics, emphasising the transformative role of emerging innovations to personalise both allograft and patient care. Their implications could extend to xenotransplantation, further broadening their potential to redefine transplant medicine.
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