Shengnan Li1, Shu Wang2, Raghavan Murugan3, Ali Al-Khafaji3, Daniel J Lebovitz4, Michael Souter5, Susan R N Stuart6, John A Kellum7. 1. Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China. 2. Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, United States. 3. Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; The CRISMA (Clinical Research, Investigation and Systems Modeling of Acute Illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States. 4. Department of Critical Care, Akron Children's Hospital, Akron, OH, United States. 5. Department of Anesthesiology & Pain Medicine, University of Washington, Harborview Medical Center, Seattle, WA, United States. 6. Center for Organ Recovery and Education, Pittsburgh, PA, United States. 7. Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; The CRISMA (Clinical Research, Investigation and Systems Modeling of Acute Illness) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States. Electronic address: kellum@pitt.edu.
Abstract
PURPOSE: We sought to build prediction models for organ transplantation and recipient survival using both biomarkers and clinical information. MATERIALS AND METHODS: We abstracted clinical variables from a previous randomized trial (n = 556) of donor management. In a subset of donors (n = 97), we measured two candidate biomarkers in plasma at enrollment and just prior to explantation. RESULTS: Secretory leukocyte protease inhibitor (SLPI) was significant for predicting liver transplantation (C-statistic 0.65 (0.53, 0.78)). SLPI also significantly improved the predictive performance of a clinical model for liver transplantation (integrated discrimination improvement (IDI): 0.090 (0.009, 0.210)). For other organs, clinical variables alone had strong predictive ability (C-statistic >0.80). Recipient 3-years survival was 80.0% (71.9%, 87.0%). Donor IL-6 was significantly associated with recipient 3-years survival (adjusted Hazard Ratio (95%CI): 1.26(1.08, 1.48), P = .004). Neither clinical variables nor biomarkers showed strong predictive ability for 3-year recipient survival. CONCLUSIONS: Plasma biomarkers in neurologically deceased donors were associated with organ use. SLPI enhanced prediction within a liver transplantation model, whereas IL-6 before transplantation was significantly associated with recipient 3-year survival. Clinicaltrials.gov: NCT00987714.
PURPOSE: We sought to build prediction models for organ transplantation and recipient survival using both biomarkers and clinical information. MATERIALS AND METHODS: We abstracted clinical variables from a previous randomized trial (n = 556) of donor management. In a subset of donors (n = 97), we measured two candidate biomarkers in plasma at enrollment and just prior to explantation. RESULTS:Secretory leukocyte protease inhibitor (SLPI) was significant for predicting liver transplantation (C-statistic 0.65 (0.53, 0.78)). SLPI also significantly improved the predictive performance of a clinical model for liver transplantation (integrated discrimination improvement (IDI): 0.090 (0.009, 0.210)). For other organs, clinical variables alone had strong predictive ability (C-statistic >0.80). Recipient 3-years survival was 80.0% (71.9%, 87.0%). DonorIL-6 was significantly associated with recipient 3-years survival (adjusted Hazard Ratio (95%CI): 1.26(1.08, 1.48), P = .004). Neither clinical variables nor biomarkers showed strong predictive ability for 3-year recipient survival. CONCLUSIONS: Plasma biomarkers in neurologically deceased donors were associated with organ use. SLPI enhanced prediction within a liver transplantation model, whereas IL-6 before transplantation was significantly associated with recipient 3-year survival. Clinicaltrials.gov: NCT00987714.
Authors: Nicolas Goldaracena; Gonzalo Sapisochin; Vinzent Spetzler; Juan Echeverri; Moritz Kaths; Mark S Cattral; Paul D Greig; Les Lilly; Ian D McGilvray; Gary A Levy; Anand Ghanekar; Eberhard L Renner; David R Grant; Markus Selzner; Nazia Selzner Journal: Ann Surg Date: 2016-05 Impact factor: 12.969
Authors: Cecilia Montgomery Øien; Anna Varberg Reisaeter; Torbjørn Leivestad; Friedo W Dekker; Pål Dag Line; Ingrid Os Journal: Transplantation Date: 2007-03-15 Impact factor: 4.939
Authors: Victor I Machicao; Hugo Bonatti; Murli Krishna; Bashar A Aqel; Frank J Lukens; Justin H Nguyen; Barry G Rosser; Raj Satyanarayana; Hani P Grewal; Winston R Hewitt; Denise M Harnois; Julia E Crook; Jeffery L Steers; Rolland C Dickson Journal: Transplantation Date: 2004-01-15 Impact factor: 4.939
Authors: Madhukar S Patel; John Zatarain; Salvador De La Cruz; Mitchell B Sally; Tyler Ewing; Megan Crutchfield; C Kristian Enestvedt; Darren J Malinoski Journal: JAMA Surg Date: 2014-09 Impact factor: 14.766
Authors: Ignacio Martin-Loeches; Alberto Sandiumenge; Julien Charpentier; John A Kellum; Alan M Gaffney; Francesco Procaccio; Glauco A Westphal Journal: Intensive Care Med Date: 2019-02-28 Impact factor: 17.440
Authors: K Walweel; K Skeggs; A C Boon; L E See Hoe; M Bouquet; N G Obonyo; S E Pedersen; S D Diab; M R Passmore; K Hyslop; E S Wood; J Reid; S M Colombo; N J Bartnikowski; M A Wells; D Black; L P Pimenta; A K Stevenson; K Bisht; L Marshall; D A Prabhu; L James; D G Platts; P S Macdonald; D C McGiffin; J Y Suen; J F Fraser Journal: J Biomed Sci Date: 2020-10-02 Impact factor: 8.410