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Articles tagged "Prediction models"

  • 2022 American Transplant Congress

    Six-Month Outcomes Among Lung Transplant Patients with COVID-19

    L. D. Mahan, J. Rose, M. Mohanka, A. Banga

    UT Southwestern Medical Center, Dallas, TX

    *Purpose: There is limited data on the outcomes beyond the acute illness among lung transplant (LT) patients with Coronavirus disease 2019 (COVID-19). The current study…
  • 2022 American Transplant Congress

    Tracking of Donor Reactive T Cell Clones Can Be Used to Diagnose or Even Predict Kidney Transplant Rejection

    J. M. Mathew1, Y. Sambandam1, M. Kandpal1, J. He1, G. Perottino1, B. Banbury2, P. Fields2, L. Gallon1, J. R. Leventhal1

    1Northwestern University, Chicago, IL, 2Adaptive Biotechnologies, Seattle, WA

    *Purpose: Transplant (Tx) rejection currently requires an invasive biopsy for diagnosis. We have tested if serial quantitation of donor reactive T cell clones (DRTC) can…
  • 2022 American Transplant Congress

    Mortality in Solid Organ Transplant Recipients with a Pretransplant Cancer Diagnosis

    A. Hart1, R. Pfeiffer2, B. Morawski3, C. Lynch4, Y. Zeng5, K. Pawlish6, K. Yu7, D. Hurley8, E. Engels7

    1Hennepin Healthcare, University of Minnesota, Minneapolis, MN, 2Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 3Cancer Registry of Idaho, Boise, ID, 4Epidemiology, University of Iowa, Iowa City, IA, 5North Dakota Statewide Cancer Registry, Grand Forks, ND, 6New Jersey State Cancer Registry, Trenton, NJ, 7Infections and Immunoepidemiology Branch, National Cancer Institute, Bethesda, MD, 8University of South Carolina, Columbia, SC

    *Purpose: Transplant-associated immunosuppression may cause cancer recurrence in patients with a pretransplant cancer, but little is known about outcomes among these recipients.*Methods: We used data…
  • 2022 American Transplant Congress

    Prediction Model of Post-Donation Renal Function Using Dynamic Kidney CT Volumetry in Living Donor

    S. Lim1, J. Kwon2, Y. Ko1, H. Kwon1, J. Jung1, H. Kwon1, Y. Kim1, J. Park2, K. Lee2, S. Shin1

    1Asan Medical Center, Seoul, Songpa, Korea, Republic of, 2Samsung Medical Center, Seoul, Gangnam, Korea, Republic of

    *Purpose: The risk of renal failure after live kidney donation can be predicted based on various clinical information. We tried introduce a model to predict…
  • 2022 American Transplant Congress

    Validation of a Prediction System for Risk of Allograft Loss (iBOX) in Pediatric Kidney Transplant Recipients

    J. Hogan1, G. Divard2, R. Garro3, O. Boyer4, M. Seifert5, J. Smith6, B. Toenshoff7, K. Twombley8, B. Warady9, P. Weng10, R. Zaar11, R. Patzer12, A. Loupy2

    1Pediatric Nephrology, Robert Debré Hospital, APHP, Paris, France, 2Paris Transplant Group, INSERM, Paris, France, 3Pediatric Nephrology, Children Healthcare of Atlanta, Atlanta, GA, 4Pediatric Nephrology, Necker Hospital, Paris, France, 5UAB School of Medicine, Birmingham, AL, 6Pediatric Nephrology, Seattle Children, Seattle, WA, 7University Children's Hospital, Heidelberg, Germany, 8Medical University of South Carolina, Charleston, SC, 9Childrens Mercy Hospital, Kansas City, MO, 10Pediatric Nephrology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 11Pediatric Nephrology, Le Bonheur Children's Hospital, Memphis, TN, 12Emory Transplant Center, Emory University, Atlanta, GA

    *Purpose: Kidney allograft loss is a common cause of end-stage renal disease but accurate prediction models of kidney allograft loss are lacking in children. The…
  • 2022 American Transplant Congress

    Multidimensional Prognostication Tool for Kidney Transplant Patient Survival: The Mortality Mbox

    C. Debiais-Deschamps1, O. Aubert1, D. Yoo1, G. Divard1, C. Lefaucheur2, C. Legendre3, A. Loupy1

    1Université de Paris, PARCC, INSERM, Paris, France, 2Service de Transplantation Rénale, AP-HP, Hôpital Saint-Louis, Paris, France, 3Service de Transplantation Rénale Adulte, AP-HP, Hopital Necker, Paris, France

    *Purpose: Predicting kidney transplant patient mortality has been hampered by registry-based studies and low level phenotyped cohorts without specific design towards mortality prediction. This represents…
  • 2022 American Transplant Congress

    Prediction of Waitlist Mortality in Liver Transplant Candidates: Do Time-Varying Models Help?

    A. Kwong1, W. Kim1, D. Schladt2, A. Wey2, J. Snyder2, A. Israni2, J. Lake3

    1Stanford University, Stanford, CA, 2Hennepin Healthcare Research Institute, Minneapolis, MN, 3University of Minnesota, Minneapolis, MN

    *Purpose: In the United States, priority on the liver transplant waitlist is determined by the model for end-stage liver disease (MELD)-Na, a score composed of…
  • 2022 American Transplant Congress

    Distinct Phenotypes of Kidney Transplant Recipients Aged 80 Years or Older in the United States by Machine Learning Consensus Clustering

    S. A. Mao1, C. Thongprayoon2, M. A. Mao3, C. C. Jadlowiec4, N. Leeaphorn5, M. Cooper6, W. Cheungpasitporn2

    1Transplant Surgery, Mayo Clinic, Jacksonville, FL, 2Nephrology and Hypertension, Mayo Clinic, Rochester, MN, 3Nephrology and Hypertension, Mayo Clinic, Jacksonville, FL, 4Transplant Surgery, Mayo Clinic, Phoenix, AZ, 5Renal Transplant Program, University of Missouri-Kansas City School of Medicine/Saint Luke's Health System, Kansas City, MO, 6MedStar Georgetown Transplant Institute, Georgetown University School of Medicine, Washington, DC

    *Purpose: Our study aimed to cluster very elderly kidney transplant recipients aged 80 years and above using an unsupervised machine learning approach.*Methods: We performed consensus…
  • 2022 American Transplant Congress

    Meld 3.0 for Liver Allocation: Results From the Liver Simulated Allocation Model

    A. Kwong1, T. Weaver2, D. Schladt2, A. Wey2, K. Audette2, S. Biggins3, J. Snyder2, A. Israni2, J. Lake4, W. Kim1

    1Stanford University, Stanford, CA, 2Hennepin Healthcare Research Institute, Minneapolis, MN, 3University of Washington, Seattle, WA, 4University of Minnesota, Minneapolis, MN

    *Purpose: Priority on the US liver transplant waitlist is determined by the model for end-stage liver disease (MELD), a score composed of serum bilirubin, creatinine,…
  • 2022 American Transplant Congress

    Evaluating the Performance and External Validity of Machine Learning-Based Prediction Models in Liver Transplantation: An International Study

    T. Ivanics1, D. So2, M. P. Claasen3, D. Wallace4, M. Patel5, A. Gravely6, K. Walker7, T. Cowling7, L. Erdman8, G. Sapisochin3

    1University of Toronto - University Health Network, Toronto, ON, Canada, 2The Centre for Computational Medicine, The Hospital for Sick Children, Toronto, ON, Canada, 3Multi-organ transplant program, University Health Network, Toronto, ON, Canada, 4Department of Health Services Research and policy, London School of Hygiene and Tropical Medicine, London, United Kingdom, 5Division of Surgical Transplantation, University of Texas Southwestern Medical Center, Dallas, TX, 6Multi-organ transplant program, University of Toronto - University Health Network, Toronto, ON, Canada, 7Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom, 8The Centre of Computational Medicine, The Hospital for Sick Children, Toronto, ON, Canada

    *Purpose: National liver transplant (LT) registries are curated in many countries. We compared data from three national registries and developed machine learning algorithm (MLA)-based models…
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