Literature DB >> 22026730

Prediction of delayed graft function by means of a novel web-based calculator: a single-center experience.

E Rodrigo1, E Miñambres, J C Ruiz, A Ballesteros, C Piñera, J Quintanar, G Fernández-Fresnedo, R Palomar, C Gómez-Alamillo, M Arias.   

Abstract

Renal failure persisting after renal transplant is known as delayed graft function (DGF). DGF predisposes the graft to acute rejection and increases the risk of graft loss. In 2010, Irish et al. developed a new model designed to predict DGF risk. This model was used to program a web-based DGF risk calculator, which can be accessed via http://www.transplantcalculator.com . The predictive performance of this score has not been tested in a different population. We analyzed 342 deceased-donor adult renal transplants performed in our hospital. Individual and population DGF risk was assessed using the web-based calculator. The area under the ROC curve to predict DGF was 0.710 (95% CI 0.653-0.767, p < 0.001). The "goodness-of-fit" test demonstrates that the DGF risk was well calibrated (p = 0.309). Graft survival was significantly better for patients with a lower DGF risk (5-year survival 71.1% vs. 60.1%, log rank p = 0.036). The model performed well with good discrimination ability and good calibration to predict DGF in a single transplant center. Using the web-based DGF calculator, we can predict the risk of developing DGF with a moderate to high degree of certainty only by using information available at the time of transplantation. ©Copyright 2011 The American Society of Transplantation and the American Society of Transplant Surgeons.

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Year:  2011        PMID: 22026730     DOI: 10.1111/j.1600-6143.2011.03810.x

Source DB:  PubMed          Journal:  Am J Transplant        ISSN: 1600-6135            Impact factor:   8.086


  10 in total

1.  Predictive model for delayed graft function based on easily available pre-renal transplant variables.

Authors:  Gianluigi Zaza; Pietro Manuel Ferraro; Gianpaolo Tessari; Silvio Sandrini; Maria Piera Scolari; Irene Capelli; Enrico Minetti; Loreto Gesualdo; Giampiero Girolomoni; Giovanni Gambaro; Antonio Lupo; Luigino Boschiero
Journal:  Intern Emerg Med       Date:  2014-08-28       Impact factor: 3.397

2.  Kinetic Estimation of GFR Improves Prediction of Dialysis and Recovery after Kidney Transplantation.

Authors:  Timothy J Pianta; Zoltan H Endre; John W Pickering; Nicholas A Buckley; Philip W Peake
Journal:  PLoS One       Date:  2015-05-04       Impact factor: 3.240

Review 3.  Autophagy, Innate Immunity and Tissue Repair in Acute Kidney Injury.

Authors:  Pu Duann; Elias A Lianos; Jianjie Ma; Pei-Hui Lin
Journal:  Int J Mol Sci       Date:  2016-05-03       Impact factor: 5.923

4.  Predictive Score Model for Delayed Graft Function Based on Hypothermic Machine Perfusion Variables in Kidney Transplantation.

Authors:  Chen-Guang Ding; Yang Li; Xiao-Hui Tian; Xiao-Jun Hu; Pu-Xu Tian; Xiao-Ming Ding; He-Li Xiang; Jin Zheng; Wu-Jun Xue
Journal:  Chin Med J (Engl)       Date:  2018-11-20       Impact factor: 2.628

5.  The impact of deceased donor maintenance on delayed kidney allograft function: A machine learning analysis.

Authors:  Silvana Daher Costa; Luis Gustavo Modelli de Andrade; Francisco Victor Carvalho Barroso; Cláudia Maria Costa de Oliveira; Elizabeth De Francesco Daher; Paula Frassinetti Castelo Branco Camurça Fernandes; Ronaldo de Matos Esmeraldo; Tainá Veras de Sandes-Freitas
Journal:  PLoS One       Date:  2020-02-06       Impact factor: 3.240

Review 6.  Acute kidney injury: preclinical innovations, challenges, and opportunities for translation.

Authors:  Samuel A Silver; Héloise Cardinal; Katelyn Colwell; Dylan Burger; Jeffrey G Dickhout
Journal:  Can J Kidney Health Dis       Date:  2015-09-01

7.  Karyopherins: potential biological elements involved in the delayed graft function in renal transplant recipients.

Authors:  Gianluigi Zaza; Federica Rascio; Paola Pontrelli; Simona Granata; Patrizia Stifanelli; Matteo Accetturo; Nicola Ancona; Loreto Gesualdo; Antonio Lupo; Giuseppe Grandaliano
Journal:  BMC Med Genomics       Date:  2014-03-14       Impact factor: 3.063

8.  Evaluation of predictive models for delayed graft function of deceased kidney transplantation.

Authors:  Huanxi Zhang; Linli Zheng; Shuhang Qin; Longshan Liu; Xiaopeng Yuan; Qian Fu; Jun Li; Ronghai Deng; Suxiong Deng; Fangchao Yu; Xiaoshun He; Changxi Wang
Journal:  Oncotarget       Date:  2017-11-27

9.  Prediction of delayed graft function using different scoring algorithms: A single-center experience.

Authors:  Magda Michalak; Kristien Wouters; Erik Fransen; Rachel Hellemans; Amaryllis H Van Craenenbroeck; Marie M Couttenye; Bart Bracke; Dirk K Ysebaert; Vera Hartman; Kathleen De Greef; Thiery Chapelle; Geert Roeyen; Gerda Van Beeumen; Marie-Paule Emonds; Daniel Abramowicz; Jean-Louis Bosmans
Journal:  World J Transplant       Date:  2017-10-24

10.  Predictive Score Model for Delayed Graft Function Based on Easily Available Variables before Kidney Donation after Cardiac Death.

Authors:  Chen-Guang Ding; Qian-Hui Tai; Feng Han; Yang Li; Xiao-Hui Tian; Pu-Xun Tian; Xiao-Ming Ding; Xiao-Ming Pan; Jin Zheng; He-Li Xiang; Wu-Jun Xue
Journal:  Chin Med J (Engl)       Date:  2017-10-20       Impact factor: 2.628

  10 in total

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