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Articles tagged "Prediction models"

  • 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…
  • 2021 American Transplant Congress

    Predictive Index for Liver Retransplantation

    C. Christmann, G. Handing, M. McDonald, A. Anand, S. Keeling, N. T. Galván, R. Cotton, C. O'Mahony, J. Goss, A. Rana

    Baylor College of Medicine, Houston, TX

    *Purpose: Given the increase in demand for donor livers, it has become more critical than ever to predict mortality in order to identify the best…
  • 2021 American Transplant Congress

    Days of Delayed Graft Function and Its Impact on Graft Outcomes in Deceased Donor Kidney Transplant

    P. Budhiraja1, R. J. Butterfield2, S. S. Misra1, K. S. Reddy3, L. Kodali1, H. A. Khamash1, S. Nair1, G. K. Mour1, H. A. Chakkera1, C. C. Jadlowiec3, H. Janna1, R. L. Heilman1

    1Department of Medicine, Mayo Clinic Arizona, Phoenix, AZ, 2Department of Statistics, Mayo Clinic Arizona, Phoenix, AZ, 3Department of Surgery, Mayo Clinic Arizona, Phoenix, AZ

    *Purpose: There has been controversy regarding impact of delayed graft function (DGF) on risk of acute rejection and graft survival. This is likely due to…
  • 2021 American Transplant Congress

    Poor Reliability of Karnofsky Performance Score in Kidney Transplant Candidates

    M. R. Stedman, D. J. Watford, G. M. Chertow, J. C. Tan

    Medicine, Stanford University, Palo Alto, CA

    *Purpose: The Karnofsky Performance Status (KPS) Scale has been used as a proxy for frailty and as a predictor of transplant outcomes, however reliability of…
  • 2021 American Transplant Congress

    Creatinine Reduction Ratio at 2 Postoperative Day as a Predicting Factor of Long-Term Outcomes After Living Donor Kidney Transplantation

    Y. Kinoshita, T. Shinzato, T. Shimizu, D. Iwami

    Division of Renal Surgery and Transplantation, Department of Urology, Jichi Medical University Hospital, Shimotsuke, Tochigi, Japan

    *Purpose: Creatinine reduction ratio from 1 to 2 postoperative days (CRR2) under 30% has been defined as a slow graft function (SGF) and used to…
  • 2021 American Transplant Congress

    Artificial Neural Network Application for MELDNa Prediction

    L. Pruinelli1, M. Nguyen1, S. Olson1, J. Zhou1, J. Schold2, T. Pruett1, S. Ma1, G. Simon1

    1University of Minnesota, Minneapolis, MN, 2Cleveland Clinic Foundation, Cleveland, OH

    *Purpose: The adoption of MELDNa decreased 90-days mortality on patients waiting for liver transplant (LT); however, there are no tools available to predict MELDNa trajectories…
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