Khamash, Hasan

Background and objectives Delayed graft function is a form of AKI resulting from ischemia-reperfusion injury. Our aim was to study the effect of delayed graft function on the progression of interstitial fibrosis after deceased donor kidney transplantation. Design, setting, participants, & measurements Our study is a retrospective study of all patients transplanted at our center between July of 2003 and September of 2014 using a kidney from a deceased donor. The primary outcome was the progression of interstitial fibrosis on serial protocol biopsies done during the first year post-transplant. We analyzed the distribution of the change in the Banff interstitial fibrosis (ci) score between the delayed graft function and nondelayed graft function groups for all of the paired biopsies done at time 0 and 12 months post-transplant ( Δ fibrosis). We also performed a linear mixed model analyzing the difference in the slopes for the progression of mean Banff ci score for all of the biopsies done at time 0 and 1, 4, and 12 months post-transplant. Results There were 343 (36.7%) in the delayed graft function group and 591 in the control group. The biopsy rates for the delayed graft function and nondelayed graft function groups at time 0 were 65.3% ( n =224) and 67.0% ( n =396), respectively, and at 12 months, they were 64.4% ( n =221) and 68.4% ( n =404), respectively. Paired biopsies were available for 155 in the delayed graft function group and 283 in the control group. In a risk-adjusted model, Banff ci score >0 on the time 0 biopsy had a higher odds of delayed graft function (odds ratio, 1.70; 95% confidence interval, 1.03 to 2.82). The distribution of the Δ fibrosis between 0 and 12 months was similar in delayed graft function and control groups ( P =0.91). The slopes representing the progression of fibrosis were also similar between the groups ( P =0.66). Conclusions Donor-derived fibrosis may increase the odds of delayed graft function; however, delayed graft function does not seem to increase the progression of fibrosis during the first year after transplantation.

AbstractBackgroundWhile simultaneous pancreas kidney transplant (SPKTx) is a therapeutic option for patients with type 1 diabetes (T1DM) and renal failure, few centers offer SPKTx to “select” non‐T1DM patients. To address concerns that existing insulin resistance may limit the benefits of the pancreas allograft among non‐T1DM, we compared several indices of glucose homeostasis, in “select” non‐T1DM and T1DM patients who received SPKTx.MethodsCriteria for “select” non‐T1DM included the following: positive C‐peptide, BMI <30 kg/m2, treatment with oral agents before insulin initiation, and insulin at <1 unit/kg/d. We compared several indices of glucose homeostasis within 1 yr post‐SPKTx among seven “select” patients with non‐T1DM and nine patients with T1DM with similar age, BMI, and immunosuppression. Measurements of insulin resistance included the following: homeostatic model, insulin sensitivity index, and insulin–glucose ratio; insulin secretion measures included the following: corrected insulin response.ResultsNon‐T1DM had similar pre‐transplant metabolic (fasting glucose, HbA1c, blood pressure, and lipid) parameters to the T1DM cohort. There were no significant differences in the various measures of insulin resistance and secretion between T1DM and “select” non‐T1DM patients.ConclusionOur results suggest SPKTx should be considered in the therapeutic armamentarium among carefully select non‐T1DM with features of minimal insulin resistance; however, a larger cohort with longer follow‐up is needed to confirm our results.

AbstractBackgroundIn a recent clinical trial in kidney transplant recipients, induction with alemtuzumab and rabbit‐antithymocyte globulin (r‐ATG) was equally effective in preventing rejection during the first post‐transplant year; however, this study did not include protocol biopsies.MethodsThe aim of this study was to analyze the impact of alemtuzumab induction on rejection and subclinical inflammation during the first post‐transplant year compared with a historic control group receiving induction with r‐ATG. All patients received tacrolimus and mycophenolate mofetil (MMF).ResultsThere were 361 in the alemtuzumab group and 478 in the r‐ATG groups. Rejection (excluding Banff borderline), during the first year, occurred in 14% of the alemtuzumab group and 9% of the r‐ATG group (p = 0.03). Estimated glomerular filtration rate (GFR) (chronic kidney disease (CKD)‐EPI formula) at one yr and graft survival at three yr were similar. On the protocol biopsies, interstitial inflammation (Banff i scores) and tubulitis (Banff t scores) were more likely in the r‐ATG group at one month, but at four and 12 months, both inflammation and tubulitis were more likely in the alemtuzumab group.ConclusionsWe conclude that alemtuzumab induction is associated with delayed inflammation at four and 12 months, but this inflammation did not appear to negatively impact the GFR or graft survival.

OBJECTIVE New-onset diabetes after kidney transplantation (NODAT) has adverse clinical and economic implications. A risk score for NODAT could help identify research subjects for intervention studies. RESEARCH DESIGN AND METHODS We conducted a single-center retrospective cohort study using pretransplant clinical and laboratory measurements to construct a risk score for NODAT. NODAT was defined by hemoglobin A1c (HbA1c) ≥6.5%, fasting serum glucose ≥126 mg/dL, or prescribed therapy for diabetes within 1 year posttransplant. Three multivariate logistic regression models were constructed: 1) standard model, with both continuous and discrete variables; 2) dichotomous model, with continuous variables dichotomized at clinically relevant cut points; and 3) summary score defined as the sum of the points accrued using the terms from the dichotomous model. RESULTS A total of 316 subjects had seven pretransplant variables with P &lt; 0.10 in univariate logistic regression analyses (age, planned corticosteroid therapy posttransplant, prescription for gout medicine, BMI, fasting glucose and triglycerides, and family history of type 2 diabetes) that were selected for multivariate models. Areas under receiver operating curves for all three models were similar (0.72, 0.71, and 0.70). A simple risk score calculated as the sum of points from the seven variables performed as well as the other two models in identifying risk of NODAT. CONCLUSIONS A risk score computed from seven simple pretransplant variables can identify risk of NODAT.