Articles tagged "Prediction models"

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…
2022 American Transplant Congress
Computer vs Human-Based Prediction and Stratification of the Risk of Long-Term Kidney Allograft Failure
G. Divard¹, M. Raynaud¹, V. Tataputii², B. Abdalla³, C. Legendre¹, C. Lefaucheur¹, O. Aubert¹, A. Loupy¹
¹Paris Transplant Group, Paris, France, ²NYU Langone Health, New York, NY, ³UCLA, Los Angeles, CA
*Purpose: Clinical decision-making process after transplantation is mainly driven by patient individual risk of allograft failure prediction assessed by physicians. However, this task remains difficult…
2022 American Transplant Congress
A Hybrid Model Combining Survival Analysis, Knapsack Optimization and Supervised Learning to Extrapolate the Evolution of Kidney Transplantation Patients from Donors with Expanded Criteria After Controlled Circulatory Death
F. Santos Arteaga¹, D. Di Caprio², O. Bestard³, N. Montero⁴, F. Moreso³, M. Crespo⁵, C. Facundo⁶, J. Reinoso-Moreno⁷, D. Cucchiari⁷, B. Bayes⁷, E. Poch⁷, J. M. Campistol⁷, F. Oppenheimer⁷, F. Diekmann⁷, I. Revuelta⁷
¹Faculty of Economics and Management, Universidad Complutense de Madrid, Madrid, Spain, ²Department of Economics and Management, University of Trento, Trento, Italy, ³Department of Nephrology and Kidney Transplant, Hospital Universitari Vall Hebrón, Barcelona, Spain, ⁴Department of Nephrology and Kidney Transplant, Hospital Universitari de Bellvitge, Barcelona, Spain, ⁵Department of Nephrology and Kidney Transplant, Hospital del Mar, Barcelona, Spain, ⁶Department of Nephrology and Kidney Transplant, Fundació Puigvert, Barcelona, Spain, ⁷Department of Nephrology and Kidney Transplant, Hospital Clinic, Barcelona, Spain
*Purpose: Kidney transplantation (KT) with expanded criteria donors (ECD) after controlled circulatory death (cDCD) in high-risk patients is being debated. We categorize patients via a…
2022 American Transplant Congress
Dynamic Risk Prediction of Kidney Graft Failure After Deceased Donor Transplant
D. G. Hu¹, H. Thiessen Philbrook¹, S. Mohan², I. Hall³, M. Doshi⁴, K. F. Kerr⁵, C. R. Parikh¹
¹Johns Hopkins University, Baltimore, MD, ²Columbia University Medical Center, New York, NY, ³University of Utah, Salt Lake City, UT, ⁴University of Michigan, Ann Arbor, MI, ⁵University of Washington, Seattle, WA
*Purpose: Identifying kidney transplant recipients at risk of graft failure allows for early intervention in clinical care. We developed a dynamic risk prediction model based…
2022 American Transplant Congress
Four Separate Frailty Metrics Lack Concordance and Are Non-Reflective of the Kidney Transplant Listing Outcome: A Large Single Center Review
A. Cimeno, G. Lewis, R. Parsons
Transplant Surgery, Emory University Hospital, Atlanta, GA
*Purpose: It is well known that functional status has prognostic value for post-surgical outcomes, however pre-transplant patients are not required to undergo objective frailty testing.…
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…
2021 American Transplant Congress
Incidence and Risk Factors for Nonmelanoma Skin Cancer in Lung Transplant Recipients
G. Holdren¹, E. Lushin¹, M. Duncan², C. Hage²
¹Pharmacy, Indiana University Health, Indianapolis, IN, ²Pulmonary Critical Care, Indiana University Health, Indianapolis, IN
*Purpose: The purpose of this study is to identify the incidence of nonmelanoma skin cancer (NMSC) post lung transplantation and to examine the relationship between…
2021 American Transplant Congress
Transplant Data Platform – An Augmented Clinical Intelligence Framework
C. Focht, W. Tian, J. Zeng, N. Dzebisashvili, S. Ghosh
CareDx, Brisbane, CA
*Purpose: UNOS, SRTR, USRDS registries are rich in patient baseline data. However, all suffer from data attrition as patients move further out post-transplant or between…
2021 American Transplant Congress
Construction of a Waiting Time Predictive Model for Kidney Transplant with Deceased Donor in the State of São Paulo
J. Silva¹, M. Contti¹, M. Valiatti¹, H. Nga¹, G. Santos¹, M. Perosa², G. Ferreira³, L. Modelli de Andrade¹
¹UNESP, Botucatu, Brazil, ²Hospital Leforte, São Paulo, Brazil, ³Santa Casa de Juiz de Fora, Juiz de Fora, Brazil
*Purpose: Chronic kidney disease is an important public health problem and kidney transplant is the therapy of choice when possible. The transplant system in the…
2021 American Transplant Congress
Offer Acceptance Models for Various Endpoints: Initial Response, Final Response, and Conversion from Provisional Yes to Yes
C. Martinez, M. Stuart, A. Placona
United Network for Organ Sharing, Richmond, VA
*Purpose: Offer acceptance models are routinely used for program evaluation and academic research, but the focus tends to be on modelling the final offer response.…