BACKGROUND: Whether chronic kidney disease (CKD) staging provides a useful framework for predicting outcomes after kidney transplant is unclear. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: We used data from the Patient Outcomes in Renal Transplantation (PORT) Study, including 13,671 transplants from 12 centers during 10 years of follow-up. PREDICTOR: Estimated glomerular filtration rate (eGFR; in milliliters per minute per 1.73 m(2)) at 12 months posttransplant. OUTCOMES: All-cause graft failure (a composite end point consisting of return to dialysis therapy, pre-emptive retransplant, or death with function), death-censored graft failure, and death with a functioning graft. MEASUREMENTS: The relationship between 12-month eGFR and subsequent graft outcomes through 10 years posttransplant was assessed using Cox proportional hazards analyses. RESULTS: Stage 3 included 63% of patients and was subdivided into stages 3a (eGFR, 45-59 mL/min/1.73 m(2); 34%) and 3b (eGFR, 30-44 mL/min/1.73 m(2); 29%). Compared with stage 2 (eGFR, 60-89 mL/min/1.73 m(2); 24%), adjusted Cox proportional HRs for graft failure were 1.12 (95% CI, 1.01-1.24; P = 0.04) for stage 3a, 1.50 (95% CI, 1.35-1.66; P < 0.001) for stage 3b, 2.86 (95% CI, 2.53-3.22; P < 0.001) for stage 4 (eGFR, 15-29 mL/min/1.73 m(2); 9%), and 13.2 (95% CI, 10.7-16.4; P < 0.001) for stage 5 (eGFR <15 mL/min/1.73 m(2); 1%). For stage 1 (eGFR ≥ 90 mL/min/1.73 m(2); 3%), risk of graft failure was increased (1.41 [95% CI, 1.13-1.75]; P < 0.001), likely due to serum creatinine associations independent of kidney function. Similar associations were seen between CKD stages and mortality. LIMITATIONS: Retrospective study; lack of gold-standard measurements of true GFR; lack of measures of comorbidity, inflammation, muscle mass, proteinuria, and other noncreatinine markers of eGFR. CONCLUSIONS: CKD stages validated in the general population provide a useful framework for predicting outcomes after kidney transplant.
BACKGROUND: Whether chronic kidney disease (CKD) staging provides a useful framework for predicting outcomes after kidney transplant is unclear. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: We used data from the Patient Outcomes in Renal Transplantation (PORT) Study, including 13,671 transplants from 12 centers during 10 years of follow-up. PREDICTOR: Estimated glomerular filtration rate (eGFR; in milliliters per minute per 1.73 m(2)) at 12 months posttransplant. OUTCOMES: All-cause graft failure (a composite end point consisting of return to dialysis therapy, pre-emptive retransplant, or death with function), death-censored graft failure, and death with a functioning graft. MEASUREMENTS: The relationship between 12-month eGFR and subsequent graft outcomes through 10 years posttransplant was assessed using Cox proportional hazards analyses. RESULTS: Stage 3 included 63% of patients and was subdivided into stages 3a (eGFR, 45-59 mL/min/1.73 m(2); 34%) and 3b (eGFR, 30-44 mL/min/1.73 m(2); 29%). Compared with stage 2 (eGFR, 60-89 mL/min/1.73 m(2); 24%), adjusted Cox proportional HRs for graft failure were 1.12 (95% CI, 1.01-1.24; P = 0.04) for stage 3a, 1.50 (95% CI, 1.35-1.66; P < 0.001) for stage 3b, 2.86 (95% CI, 2.53-3.22; P < 0.001) for stage 4 (eGFR, 15-29 mL/min/1.73 m(2); 9%), and 13.2 (95% CI, 10.7-16.4; P < 0.001) for stage 5 (eGFR <15 mL/min/1.73 m(2); 1%). For stage 1 (eGFR ≥ 90 mL/min/1.73 m(2); 3%), risk of graft failure was increased (1.41 [95% CI, 1.13-1.75]; P < 0.001), likely due to serum creatinine associations independent of kidney function. Similar associations were seen between CKD stages and mortality. LIMITATIONS: Retrospective study; lack of gold-standard measurements of true GFR; lack of measures of comorbidity, inflammation, muscle mass, proteinuria, and other noncreatinine markers of eGFR. CONCLUSIONS: CKD stages validated in the general population provide a useful framework for predicting outcomes after kidney transplant.
Authors: D E Weiner; M A Carpenter; A S Levey; A Ivanova; E H Cole; L Hunsicker; B L Kasiske; S J Kim; J W Kusek; A G Bostom Journal: Am J Transplant Date: 2012-05-17 Impact factor: 8.086
Authors: Anish Kirpalani; Eyesha Hashim; General Leung; Jin K Kim; Adriana Krizova; Serge Jothy; Maya Deeb; Nan N Jiang; Lauren Glick; Gevork Mnatzakanian; Darren A Yuen Journal: Clin J Am Soc Nephrol Date: 2017-08-30 Impact factor: 8.237