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Machine Learning Consensus Clustering of Morbidly Obese Kidney Transplant Recipients in the United States.

Charat ThongprayoonShennen A MaoCaroline C JadlowiecMichael A MaoNapat LeeaphornWisit KaewputPradeep VaitlaPattharawin PattharanitimaSupawit TangpanithandeePajaree KrisanapanFawad QureshiPitchaphon NissaisorakarnMatthew CooperWisit Cheungpasitporn
Published in: Journal of clinical medicine (2022)
With the application of unsupervised machine learning, variable post-transplant outcomes are observed among morbidly obese kidney transplant recipients. Recipients with earlier access to transplant and living donation show superior outcomes. Unexpectedly, reduced graft survival in cluster 3 recipients perhaps underscores socioeconomic access to post-transplant support and minorities being disadvantaged in access to preemptive and living donor transplants. Despite obesity-related concerns, one-year patient and graft survival were favorable in all clusters, and obesity itself should be reconsidered as a hard barrier to kidney transplantation.
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