BACKGROUND: Suboptimal early graft function following renal transplantation remains a significant challenge. It is suggested that clinical variables (or scoring systems based thereon) may predict the occurrence of delayed graft function (DGF), defined as post-operative dialysis requirement. However, data is conflicting, and suboptimal renal function not requiring dialysis has been little investigated. This study tested the ability of clinical variables to predict suboptimal early function variably assessed by: (i) DGF (dialysis requirement during the first week); (ii) DGF duration; (iii) slow graft function (creatinine>3 mg/dl on day 5); (iv) creatinine reduction ratio on day 2. METHODS: Details on 217 consecutive renal transplant recipients were collected. All received ciclosporin-based immunosuppression. Multiple regression analysis was used to assess the association between individual clinical variables and suboptimal early graft function. Also tested were three scoring systems incorporating clinical variables [US Renal Database System (USRDS score), deceased donor score (DDS) and expanded criteria donor kidneys]. Receiver operated-characteristic curve analysis was used to assess the predictive power of clinical variables and scoring systems. RESULTS: Early graft function was associated with donor age, donor body mass index, donor hypertension, donation following cardiac death, black recipient ethnicity, recipient weight and cold ischaemic time (P<or=0.05 for all). All scoring systems showed associations with early graft function, although only USRDS score remained in the multiple regression model. The overall utility of the USRDS score in predicting DGF was moderate at best, although improved at extreme scores (specificity: 95%; positive predictive value: 73%; for USRDS score>or=150). CONCLUSIONS: Clinical variables and scores have moderate predictive ability for early graft function and although of potential use in clinical practice, caution should be exercised before altering patient management based solely on them.
BACKGROUND: Suboptimal early graft function following renal transplantation remains a significant challenge. It is suggested that clinical variables (or scoring systems based thereon) may predict the occurrence of delayed graft function (DGF), defined as post-operative dialysis requirement. However, data is conflicting, and suboptimal renal function not requiring dialysis has been little investigated. This study tested the ability of clinical variables to predict suboptimal early function variably assessed by: (i) DGF (dialysis requirement during the first week); (ii) DGF duration; (iii) slow graft function (creatinine>3 mg/dl on day 5); (iv) creatinine reduction ratio on day 2. METHODS: Details on 217 consecutive renal transplant recipients were collected. All received ciclosporin-based immunosuppression. Multiple regression analysis was used to assess the association between individual clinical variables and suboptimal early graft function. Also tested were three scoring systems incorporating clinical variables [US Renal Database System (USRDS score), deceased donor score (DDS) and expanded criteria donor kidneys]. Receiver operated-characteristic curve analysis was used to assess the predictive power of clinical variables and scoring systems. RESULTS: Early graft function was associated with donor age, donor body mass index, donorhypertension, donation following cardiac death, black recipient ethnicity, recipient weight and cold ischaemic time (P<or=0.05 for all). All scoring systems showed associations with early graft function, although only USRDS score remained in the multiple regression model. The overall utility of the USRDS score in predicting DGF was moderate at best, although improved at extreme scores (specificity: 95%; positive predictive value: 73%; for USRDS score>or=150). CONCLUSIONS: Clinical variables and scores have moderate predictive ability for early graft function and although of potential use in clinical practice, caution should be exercised before altering patient management based solely on them.
Authors: Daniel W Louvar; Na Li; Jon Snyder; Yi Peng; Bertram L Kasiske; Ajay K Israni Journal: J Am Soc Nephrol Date: 2009-04-23 Impact factor: 10.121
Authors: Basil M Yurcisin; Tara E Davison; Syreena M Bibbs; Bradley H Collins; Jonathan S Stamler; James D Reynolds Journal: Ann Surg Date: 2013-05 Impact factor: 12.969
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