Literature DB >> 26900309

Recipient Criteria Predictive of Graft Failure in Kidney Transplantation.

Ernesto P Molmenti1, Asha Alex2, Lisa Rosen3, Mohini Alexander4, Jeffrey Nicastro2, Jingyan Yang5, Eric Siskind2, Leesha Alex2, Emil Sameyah3, Madhu Bhaskaran4, Nicole Ali4, Amit Basu2, Mala Sachdeva4, Stergiani Agorastos2, Prejith Rajendran2, Prathik Krishnan2, Poornima Ramadas2, Leo Amodu2, Joaquin Cagliani2, Sameer Rehman2, Adam Kressel2, Christine B Sethna6, Georgios C Sotiropoulos7, Arnold Radtke8, George Sgourakis9, Richard Schwarz4, Steven Fishbane4, Alessandro Bellucci4, Gene Coppa2, Horacio Rilo2, Christine L Molmenti5.   

Abstract

Several classifications systems have been developed to predict outcomes of kidney transplantation based on donor variables. This study aims to identify kidney transplant recipient variables that would predict graft outcome irrespective of donor characteristics. All U.S. kidney transplant recipients between October 25,1999 and January 1, 2007 were reviewed. Cox proportional hazards regression was used to model time until graft failure. Death-censored and nondeath-censored graft survival models were generated for recipients of live and deceased donor organs. Recipient age, gender, body mass index (BMI), presence of cardiac risk factors, peripheral vascular disease, pulmonary disease, diabetes, cerebrovascular disease, history of malignancy, hepatitis B core antibody, hepatitis C infection, dialysis status, panel-reactive antibodies (PRA), geographic region, educational level, and prior kidney transplant were evaluated in all kidney transplant recipients. Among the 88,284 adult transplant recipients the following groups had increased risk of graft failure: younger and older recipients, increasing PRA (hazard ratio [HR],1.03-1.06], increasing BMI (HR, 1.04-1.62), previous kidney transplant (HR, 1.17-1.26), dialysis at the time of transplantation (HR, 1.39-1.51), hepatitis C infection (HR, 1.41-1.63), and educational level (HR, 1.05-1.42). Predictive criteria based on recipient characteristics could guide organ allocation, risk stratification, and patient expectations in planning kidney transplantation.

Entities:  

Keywords:  comorbidities; geographic disparities; graft failure; kidney transplant recipients; outcomes predictors; patient education

Year:  2015        PMID: 26900309      PMCID: PMC4758847          DOI: 10.1055/s-0035-1563605

Source DB:  PubMed          Journal:  Int J Angiol        ISSN: 1061-1711


  24 in total

1.  Geographic differences in access to transplantation in the United States.

Authors:  Mary D Ellison; Leah B Edwards; Erick B Edwards; Clyde F Barker
Journal:  Transplantation       Date:  2003-11-15       Impact factor: 4.939

2.  KDIGO clinical practice guideline for the care of kidney transplant recipients: a summary.

Authors:  Bertram L Kasiske; Martin G Zeier; Jeremy R Chapman; Jonathan C Craig; Henrik Ekberg; Catherine A Garvey; Michael D Green; Vivekanand Jha; Michelle A Josephson; Bryce A Kiberd; Henri A Kreis; Ruth A McDonald; John M Newmann; Gregorio T Obrador; Flavio G Vincenti; Michael Cheung; Amy Earley; Gowri Raman; Samuel Abariga; Martin Wagner; Ethan M Balk
Journal:  Kidney Int       Date:  2009-10-21       Impact factor: 10.612

3.  Equal Opportunity Supplemented by Fair Innings: equity and efficiency in allocating deceased donor kidneys.

Authors:  L F Ross; W Parker; R M Veatch; S E Gentry; J R Thistlethwaite
Journal:  Am J Transplant       Date:  2012-06-15       Impact factor: 8.086

4.  The impact of body mass index on renal transplant outcomes: a significant independent risk factor for graft failure and patient death.

Authors:  Herwig-Ulf Meier-Kriesche; Julie A Arndorfer; Bruce Kaplan
Journal:  Transplantation       Date:  2002-01-15       Impact factor: 4.939

5.  Effect of waiting time on renal transplant outcome.

Authors:  H U Meier-Kriesche; F K Port; A O Ojo; S M Rudich; J A Hanson; D M Cibrik; A B Leichtman; B Kaplan
Journal:  Kidney Int       Date:  2000-09       Impact factor: 10.612

6.  Outcome of third renal allograft retransplants versus primary transplants from paired donors.

Authors:  David Horovitz; Yves Caumartin; Jeff Warren; Adeel A Sheikh; Michael Bloch; Anil Kapoor; Anthony M Jevnikar; Patrick P W Luke
Journal:  Transplantation       Date:  2009-04-27       Impact factor: 4.939

7.  Role of socioeconomic status in kidney transplant outcome.

Authors:  Alexander S Goldfarb-Rumyantzev; James K Koford; Bradley C Baird; Madhukar Chelamcharla; Arsalan N Habib; Ben-Jr Wang; Shih-jui Lin; Fuad Shihab; Ross B Isaacs
Journal:  Clin J Am Soc Nephrol       Date:  2006-01-11       Impact factor: 8.237

Review 8.  Hepatitis C and renal transplantation.

Authors:  Jose M Morales; Jose M Aguado
Journal:  Curr Opin Organ Transplant       Date:  2012-12       Impact factor: 2.640

Review 9.  Hepatitis C virus and nonliver solid organ transplantation.

Authors:  Marco Carbone; David Mutimer; James Neuberger
Journal:  Transplantation       Date:  2013-03-27       Impact factor: 4.939

10.  Optimal transplant education for recipients to increase pursuit of living donation.

Authors:  Amy D Waterman; Ann C Barrett; Sara L Stanley
Journal:  Prog Transplant       Date:  2008-03       Impact factor: 1.065

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  4 in total

1.  Assessment of risk factors for increased resource utilization in kidney transplantation.

Authors:  Steven Craig Vranian; Kelly L Covert; Caitlin R Mardis; John W McGillicuddy; Kenneth D Chavin; Derek Dubay; David J Taber
Journal:  J Surg Res       Date:  2018-02       Impact factor: 2.192

2.  A retrospective study of the relationship between postoperative urine output and one year transplanted kidney function.

Authors:  Joungmin Kim; Taehee Pyeon; Jeong Il Choi; Jeong Hyeon Kang; Seung Won Song; Hong-Beom Bae; Seongtae Jeong
Journal:  BMC Anesthesiol       Date:  2019-12-17       Impact factor: 2.217

3.  Changes in quality of life (QoL) and other patient-reported outcome measures (PROMs) in living-donor and deceased-donor kidney transplant recipients and those awaiting transplantation in the UK ATTOM programme: a longitudinal cohort questionnaire survey with additional qualitative interviews.

Authors:  Andrea Gibbons; Janet Bayfield; Marco Cinnirella; Heather Draper; Rachel J Johnson; Gabriel C Oniscu; Rommel Ravanan; Charles Tomson; Paul Roderick; Wendy Metcalfe; John L R Forsythe; Christopher Dudley; Christopher J E Watson; J Andrew Bradley; Clare Bradley
Journal:  BMJ Open       Date:  2021-04-14       Impact factor: 2.692

4.  Using machine learning techniques to develop risk prediction models to predict graft failure following kidney transplantation: protocol for a retrospective cohort study.

Authors:  Sameera Senanayake; Adrian Barnett; Nicholas Graves; Helen Healy; Keshwar Baboolal; Sanjeewa Kularatna
Journal:  F1000Res       Date:  2019-10-29
  4 in total

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