Serum Uric Acid and Renal Transplantation Outcomes: At Least 3-Year Post-transplant Retrospective Multivariate Analysis

Abstract

Since the association of serum uric acid and kidney transplant graft outcome remains disputable, we sought to evaluate the predictive value of uric acid level for graft survival/function and the factors could affect uric acid as time varies. A consecutive cohort of five hundred and seventy three recipients transplanted during January 2008 to December 2011 were recruited. Data and laboratory values of our interest were collected at 1, 3, 6, 12, 24 and 36 months post-transplant for analysis. Cox proportional hazard model, and multiple regression equation were built to adjust for the possible confounding variables and meet our goals as appropriate. The current cohort study lasts for 41.86 ± 15.49 months. Uric acid level is proven to be negatively associated with eGFR at different time point after adjustment for age, body mass index and male gender (standardized β ranges from -0.15 to -0.30 with all P<0.001).Males with low eGFR but high level of TG were on CSA, diuretics and RAS inhibitors and experienced at least one episode of acute rejection and diabetic issue were associated with a higher mean uric acid level. Hyperuricemia was significantly an independent predictor of pure graft failure (hazard ratio=4.01, 95% CI: 1.25-12.91, P=0.02) after adjustment. But it was no longer an independent risk factor for graft loss after adjustment. Interestingly, higher triglyceride level can make incidence of graft loss (hazard ratio=1.442, for each unit increase millimoles per liter 95% CI: 1.008-2.061, P=0.045) and death (hazard ratio=1.717, 95% CI: 1.105-2.665, P=0.016) more likely. The results of our study suggest that post-transplant elevated serum uric acid level is an independent predictor of long-term graft survival and graft function. Together with the high TG level impact on poor outcomes, further investigations for therapeutic effect are needed.

Fig 1. UA level predicts post-transplant kidney function.

Scatter plots showed that UA level was negatively associated with eGFR at multiple times post-transplant. (A) This part showed the correlations between 1-month UA and 5 different time points eGFRs post-transplant. (B) The same correlation between 3-mont UA and 4 other time points. (C) 6-month UA cannot predict future eGFRs properly.

Fig 2. 1-month post-transplant eGFRs and UAs for patients of different outcomes.

Every single dot represents for either an eGFR or a UA value. Green dots are plotted on left y axis and red dots are on right y axis. (A) It indicates the group of patients without bad outcomes. (B) Patients suffered allograft failure or dead eventually. (C) Patients only suffered allograft failure. (D) Patients dead with functioning graft.

Fig 3. 1-month post-transplant eGFRs and UAs after exclusion of 5 special cases.

All eGFRs of the 5 patients are lower than 10. One of them was having an acute rejection when tested for eGFR, the other 4 patients were experiencing DGF, 2 of them returned to dialysis eventually and the other 2 had recovered 2 months later. (A) The group of recipients went through allograft failure or death eventually. (B) The group of patients only suffered allograft failure.

Fig 4. Kaplan-Meier survival curve estimates for graft loss.

Hyperuricemic group survival curve was significantly (P = 0.007) lower than that of normouricemic group.Graft loss was defined as graft failure (return to dialysis) or death with functioning graft.

Fig 5. Kaplan-Meier survival curve estimates for pure graft survival.

Excluding the dead with functioning kidney, we could observe greater variance between the two groups.

Fig 6. Kaplan-Meier survival curve estimates for death with functioning graft.

No significant difference can be acquired on patient survival rate between these groups.