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Background/Aims: The 7-year Major Adverse Cardiovascular Events Calculator (CRCRTR-MACE) predicts cardiovascular events (CVE) in renal transplant recipients (RTR), and thrombopoietin (TPO) is a humoral inflammatory factor implicated in cardiovascular disease (CVD). The aim of the study was to determine if circulating TPO levels in stable RTR are positively associated with variable(s) in the CRCRTR-MACE score. Methods: CRCRTR-MACE scores were calculated in 95 stable RTR. TPO levels were measured by multiplexed fluorescent bead-based immunoassay in all patients and 48 controls. Multivariate analysis (MVA) was performed between TPO and CV risk variables and patient demographics. Stepwise regression with backward elimination of insignificant variables estimated the impact of risk variables on TPO levels. Significance was defined at p < 0.05. Normalized data were presented as mean ± SD and non-normalized data as median (maximum to minimum). Results: The risk of a CVE within 7 years as predicted by the median was 9.97% (range 1.93-84.2). The percentage of patients who were above 20% risk for a CVE was 28.4%. Control TPO level of 170.41 (4.4-995.9) pg/ml was significantly lower than that of 237.90 (32.77-1,386.79) pg/ml in RTR (p = 0.010). TPO level correlated significantly with the total CRCRTR-MACE score (R = 0.310, p = 0.004), smoking (p = 0.009) and eGFR (R = -0.275, p = 0.012) but not with age, diabetes, LDL level or history of CVE. Only the total CRCRTR-MACE score (p = 0.013) and smoking (p = 0.009) remained significant in the MVA. Stepwise regression estimated that smoking increased TPO levels by 206.28 pg/ml and each 10% increase in CRCRTR-MACE score increased TPO levels by an additional 44.4 pg/ml. Conclusion: TPO levels are increased in RTR with high CRCRTR-MACE, particularly in smokers with diminished eGFR. Circulating TPO may serve as a biomarker and treatment target for CVD in RTR.

Background: This study examines if transplant glomerular filtration rate (GFR) slope prediction is affected by the degree of transplant chronic kidney disease (CKDT) stage. Methods: Serial changes in estimated GFR (ΔeGFR) by Cockcroft-Gault (CG) and Modified Diet in Renal Disease-Isotope Dilution Mass Spectrometry (MDRD-IDMS) equations were compared to simultaneous changes in isotope GFR (ΔiGFR) in renal transplant patients who had at least four scans. Results: Total number of patients (iGFR scans) was 99 (772) while the corresponding numbers in CKDT stages 1–4 were 33 (103), 69 (239), 75 (316) and 37 (96), respectively. Measurement error [(ΔeGFR – ΔiGFR) × 100/ΔiGFR] (median ± IQR, interquartile range) estimated from CG and MDRD-IDMS slopes were –414.29 ± 276.16% and –342.86 ± 210.18% (stage 1); –350.00 ± 301.22% and –300.00 ± 525.00% (stage 2); –26.02 ± 404.38% and –26.58 ± 423.13% (stage 3); 10.26 ± 142.18% and –76.92 ± 145.64% (stage 4), respectively. The proportion of patients with CG measurement error ≤1-fold in stages 1 and 2 of 12 and 14.5% was significantly (p < 0.05) lower than that of 36.3 and 52.8% at stages 3 and 4, respectively. Similar measurement errors were observed for MDRD-IDMS. Conclusions: Transplant GFR slope prediction is affected by the degree of renal dysfunction. Errors in slope prediction are much higher in those with better function and thus add another limitation for eGFR use in longitudinal studies on progressive graft dysfunction.

Background: In chronic kidney disease the contribution of decreased glomerular filtration rate (GFR) versus enhanced inflammation to cause insulin resistance (IR) is controversial. Aim: This pilot observational study examines, therefore, the prevalence of IR after kidney donation and factors that may determine its level. Methods: Insulin, proinsulin, adiponectin, malondialdehyde, and hsCRP were measured by conventional techniques in 14 previous kidney donors and 25 healthy volunteers. Results: Estimated GFR from Cockcroft-Gault formula of 76.42 ± 19.39 ml/min/1.73 m2 in the nephrectomized group was significantly lower (p < 0.01) than that in the control group of 125 ± 32.9 ml/min/1.73 m2. Fasting serum insulin of 16.57 ± 16.86 mU/l and homeostasis model assessment of insulin resistance (HOMA-IR) of 4.86 ± 5.11 in the nephrectomized group were significantly higher (p < 0.01) than the insulin level of 6.02 ± 4.06 mU/l and HOMA-IR of 1.5 ± 1.06 in the control group. There was no significant difference in levels in inflammatory mediators between the two groups. None of the tested inflammatory mediators correlated significantly with IR. Conclusion: Reduced GFR alone in previous kidney donors is associated with increased IR.

Background: Patients with chronic kidney disease (CKD) are susceptible to hyperglycemia. Aim: To study the prevalence of pre-diabetes in CKD patients and determine the contribution of insulin resistance (IR) versus β-cell dysfunction in patients with CKD. Methods: 45 consecutive nondiabetic CKD patients and 40 healthy subjects were included. Patients were divided into a normoglycemic (NG) and a pre-diabetic (PDM) group. IR was assessed by homeostasis model assessment of insulin resistance (HOMA-IR) and β-cell function was assessed by proinsulin/insulin ratio and β-cell%. Results: The prevalence of PDM was 40%. The prevalence of high HOMA-IR was 22.2 and 77.8% in the NG and PDM groups. Compared to NG patients, the PDM group showed higher fasting plasma glucose, HOMA-IR, insulin, and proinsulin, while the prevalence of β-cell dysfunction of 22.2% was lower than the 37% present in the NG group. Conclusion: Increased IR, rather than β-cell dysfunction, is the primary mechanism of PDM in CKD patients.

Background: Cystatin C (Cys C) is measured by particle-enhanced nephelometric immunoassay (PENIA), particle-enhanced turbidimetric immunoassay (PETIA) and ELISA. Aim: To determine differences among these methods. Method: 80 normal human sera and 20 from patients with renal and/or heart disease were simultaneously assayed. Statistical analyses including receiver operating characteristics (ROC) of the three methods were compared. Results: There was a highly significant correlation across the assay range between the ELISA and PENIA (r2 = 0.94) and PETIA methods (r2 = 0.95). Analysis of variance and bias were poor between the ELISA and the other two methods. Mean difference between ELISA and PETIA was 0.65 ± 0.63 μg/ml, while it was 0.58 ± 0.53 μg/ml between ELISA and PENIA. Accuracy (at 30% range) was 17 and 11% between ELISA and PETIA and ELISA and PENIA, respectively. Normalization of the ELISA by a factor of 0.66 improved this relationship. AUC of ROC curves of PENIA, ELISA and normalized ELISA to predict Cys C levels measured from PETIA were all above 0.87 (p = not significant between curves). Criterion values of ELISA*.66 method was close to PETIA measurements. Conclusion: There is a significant difference in measured human Cys C levels among the three methods, and normalization of ELISA narrows these differences.

Background: Donor kidney implantation biopsy (IB) is performed on a regular basis, particularly as part of clinical studies. Objective: To determine the utility of donor implantation renal biopsy to predict the long-term renal allograft outcome. Methods: A Medline search for studies in English was performed with the following key words: implantation biopsy, renal transplantation and long-term outcome. Results: Sixteen trials involving 8,122 kidney transplants were identified, of which 6 were prospective studies. The histological abnormalities were scored mainly by the Banff schema and the graft outcome was defined either by delineating the delta changes in the pathology score or glomerular filtration rate. Normal histology with a well-functioning renal allograft had a favorable outcome. The extent to which the baseline tubular atrophy, interstitial fibrosis, glomerulosclerosis and vascular changes had on the long-term outcome varied from one study to another. Conclusion: Abnormal IB has a better chance of predicting early graft outcome. The review questions the current wisdom for routine IB on all donors. In some donor kidneys, a biopsy provides significant prognostic information, such as older donor kidney, those with history of hypertension, diabetes, cardiovascular disease, and kidneys with abnormal creatinine. Future research on IB is necessary to find a more useful method to predict the long-term transplant outcome.