Literature DB >> 24670483

A new clinical prediction tool for 5-year kidney transplant outcome.

Colin R Lenihan1, Joseph B Lockridge1, Jane C Tan2.   

Abstract

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Year:  2014        PMID： 24670483      PMCID： PMC4088343          DOI： 10.1053/j.ajkd.2014.01.004

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN： 0272-6386            Impact factor:   8.860


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  27 in total

1.  Post-transplant renal function in the first year predicts long-term kidney transplant survival.

Authors:  Sundaram Hariharan; Maureen A McBride; Wida S Cherikh; Christine B Tolleris; Barbara A Bresnahan; Christopher P Johnson
Journal:  Kidney Int       Date:  2002-07       Impact factor: 10.612

2.  Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in general population.

Authors:  Hans L Hillege; Vaclav Fidler; Gilles F H Diercks; Wiek H van Gilst; Dick de Zeeuw; Dirk J van Veldhuisen; Rijk O B Gans; Wilbert M T Janssen; Diederick E Grobbee; Paul E de Jong
Journal:  Circulation       Date:  2002-10-01       Impact factor: 29.690

3.  Performance of different prediction equations for estimating renal function in kidney transplantation.

Authors:  Flavio Gaspari; Silvia Ferrari; Nadia Stucchi; Emmanuel Centemeri; Fabiola Carrara; Marisa Pellegrino; Giulia Gherardi; Eliana Gotti; Giuseppe Segoloni; Maurizio Salvadori; Paolo Rigotti; Umberto Valente; Donato Donati; Silvio Sandrini; Vito Sparacino; Giuseppe Remuzzi; Norberto Perico
Journal:  Am J Transplant       Date:  2004-11       Impact factor: 8.086

4.  Estimated one-year glomerular filtration rate is the best predictor of long-term graft function following renal transplant.

Authors:  Maurizio Salvadori; Alberto Rosati; Andreas Bock; Jeremy Chapman; Bertrand Dussol; Lutz Fritsche; Volker Kliem; Yvon Lebranchu; Federico Oppenheimer; Erich Pohanka; Gunnar Tufveson; Elisabetta Bertoni
Journal:  Transplantation       Date:  2006-01-27       Impact factor: 4.939

5.  Subclinical rejection associated with chronic allograft nephropathy in protocol biopsies as a risk factor for late graft loss.

Authors:  F Moreso; M Ibernon; M Gomà; M Carrera; X Fulladosa; M Hueso; S Gil-Vernet; J M Cruzado; J Torras; J M Grinyó; D Serón
Journal:  Am J Transplant       Date:  2006-04       Impact factor: 8.086

6.  Comparison of the predictive performance of eGFR formulae for mortality and graft failure in renal transplant recipients.

Authors:  Xiang He; Jason Moore; Shazia Shabir; Mark A Little; Paul Cockwell; Simon Ball; Xiang Liu; Atholl Johnston; Richard Borrows
Journal:  Transplantation       Date:  2009-02-15       Impact factor: 4.939

7.  Microalbuminuria as a predictor of clinical nephropathy in insulin-dependent diabetes mellitus.

Authors:  G C Viberti; R D Hill; R J Jarrett; A Argyropoulos; U Mahmud; H Keen
Journal:  Lancet       Date:  1982-06-26       Impact factor: 79.321

8.  Sirolimus-based therapy following early cyclosporine withdrawal provides significantly improved renal histology and function at 3 years.

Authors:  Alfredo Mota; Manuel Arias; Eero I Taskinen; Timo Paavonen; Yves Brault; Christophe Legendre; Kerstin Claesson; Marco Castagneto; Josep M Campistol; Brian Hutchison; James T Burke; Sedar Yilmaz; Pekka Häyry; John F Neylan
Journal:  Am J Transplant       Date:  2004-06       Impact factor: 8.086

9.  Histological chronic allograft damage index accurately predicts chronic renal allograft rejection.

Authors:  H Isoniemi; E Taskinen; P Häyry
Journal:  Transplantation       Date:  1994-12-15       Impact factor: 4.939

10.  Poor predictive value of serum creatinine for renal allograft loss.

Authors:  Bruce Kaplan; Jesse Schold; Herwig-Ulf Meier-Kriesche
Journal:  Am J Transplant       Date:  2003-12       Impact factor: 8.086
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  2 in total

1.  Predicting Individual Renal Allograft Outcomes Using Risk Models with 1-Year Surveillance Biopsy and Alloantibody Data.

Authors:  Manuel Moreno Gonzales; Andrew Bentall; Walter K Kremers; Mark D Stegall; Richard Borrows
Journal:  J Am Soc Nephrol       Date:  2016-03-09       Impact factor: 10.121

2.  A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

Authors:  Kyung Don Yoo; Junhyug Noh; Hajeong Lee; Dong Ki Kim; Chun Soo Lim; Young Hoon Kim; Jung Pyo Lee; Gunhee Kim; Yon Su Kim
Journal:  Sci Rep       Date:  2017-08-21       Impact factor: 4.379
  2 in total

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