Evaluation of nutritional status in renal transplant recipients in accordance with changes in graft function.

INTRODUCTION AND AIMS: Renal transplantation (RT) is the ultimate treatment modality for end-stage renal disease (ESRD) patients. Malnutrition is a strong predictor of cardiovascular disease among ESRD patients. Body composition analysis using bioimpedance devices (BIA) is a useful noninvasive tool to detect malnutrition in this population. We investigated the impact of graft function on nutritional status and reliability of BIA to detect malnutrition in RT recipients. METHODS: We evaluated retrospectively 189 RT recipients including 59 females, and of overall mean age of 38.3 ± 10.6 years who had a minimum posttransplant follow-up of 12 months. Body Composition Analyzer (Tanita BC-420MA) determinations were complemented with monthly assessments of biochemical parameters. Patients were divided into 3 groups according to glomerular filtration rate (GFR) levels: normal graft function/high GFR group (group 1, normal creatinine levels, no proteinuria and GFR ≥ 90 mL/min; n = 59); low renal function/low GFR group (normal or high creatinine levels with low GFR levels; group 2; GFR 89-60 mL/min; n = 87) and group 3, (GFR < 60 mL/min; n = 43). RESULTS: Group 3 patients displayed significantly lower as well as hemoglobin albumin and calcium concentrations, with higher phosphorus and parathyroid hormone levels (P = .0001). They also showed significantly lower body weight (P = .0001), body mass index (P = .002), fat (P = .002) and muscle (P = .0001) contents as well as fat-free mass (P = .0001). Group 2 patients had significantly lower values compared with group 1 and higher values than group 3. GFR values positively correlated with albumin, fat, muscle, and fat-free mass (r = 0.337, 0.299, 0.281, 0.278, respectively; P = .0001). GFR values positively correlated with visceral fat ratio (r = 0.170; P = 0.02), body mass index (r = 0.253; P = .0001), and waist-hip ratio (r = 0.218; P = .006). CONCLUSION: Loss of muscle and fat mass is an early sign of malnutrition among RT recipients. It is closely associated with loss of GFR. BIA is a noninvasive and reliable diagnostic tool that should be included in the follow-up of these patients for an early diagnosis of malnutrition-related complications.

Low graft function and ongoing hyperparathyroidism are closely related to post-transplantation osteoporosis.

INTRODUCTION: Renal transplantation (RT) is the gold standard therapy for chronic renal failure. Immunosuppressive drug choice, malnutrition, adynamic bone disease and hyperparathyroidism are important factors impacting the development of posttransplant osteoporosis. Body composition analysis with bioimpedance devices (BIA) is a useful noninvasive tool to detect malnutrition among the RT population. We investigated the effects of graft function, immunosuppressive drug regimens and biochemical characteristics on bone mineral density of RT patients as well as the reliability of BIA measurements to diagnose osteoporosis. METHODS: One hundred three recipients with a minimum of 12 months post-RT follow-up underwent body composition analysis using the Tanita Analyzer. The last 6 months of monthly biochemical parameters and glomerular filtration rates (GFR) as well as drug regimens were collected retrospectively from patient charts. Patients were divided into 2 groups, according to their femoral neck and lumbal T scores, as osteoporosis (n = 42) and control groups (n = 61). RESULTS: The mean GFR of osteoporotic patients was significantly lower (P = .04) and parathyroid hormone (PTH) levels significantly higher (P = .002). According to BIA, osteoporotic patients showed lower bone mass, fat mass, visceral fat ratio, muscle mass, waist-hip ratios, and body mass index values (P < .05). Correlation analysis revealed GFR to negatively correlate with PTH (r = -0.231, P = .010) and positively with femur t scores (r = 0.389, P = .0001) as well as with BIA findings (P = .0001). In contrast, PTH levels in negatively correlated with lumbar and femoral neck t scores (r = -0.22, -0.4 and P = .026, .0001, respectively) but not with BIA findings including bone mass. CONCLUSION: Changes in bone density after RT were affected by graft function. The rapid loss of bone mineral density emphasizes the need for prevention started in the early posttransplant period. BMD measurements provided a guide for treatment and for subsequent evaluation.

Left ventricular mass index and its relationship to ambulatory blood pressure and renal resistivity index in renal transplant recipients.

INTRODUCTION AND AIMS: Left ventricular hypertrophy (LVH) is frequently observed in patients with end-stage renal disease and renal allograft recipients. It is an independent, strong predictor of morbidity and mortality. Renal resistive index (RRI) is an important determinant of graft function in transplant recipients. In essential hypertension, increased RRI is associated with reduced renal function and tubulointerstitial damage. In this present study, we investigated the association of ambulatory blood pressure monitoring parameters and RRI on left ventricular mass index among renal transplant recipients. METHODS: Charts of 98 renal transplant recipients with echocardiography, ambulatory blood pressure monitoring, and renal Doppler ultrasonography as well as laboratory tests including serum creatinine, glomerular filtration rate, and C-reactive protein (CRP) level at the end of post-transplantation year 1 were analyzed in this study. LVMI was calculated using the Devereux formula with echocardiographic findings. RESULTS: Left ventricular mass index (LVMI) positively correlated with mean systolic blood pressure (SBP) (r = 0.512; P = .0001), mean nighttime SBP (r = 0.312; P = .007), mean nighttime diastolic blood pressure (DBP) (r = 0.427; P = .005), renal resistive index (RRI; r = 0.290; P = .004), and age (r = 0.371; P = .001). Multiple logistic regression analysis revealed that mean and maximum nighttime SBP and RRI were independent risk factors for LVMI (P = .001, .035, and .05, respectively). CONCLUSION: High RRI is one of the main indicators of cardiovascular disease in renal transplant recipients. Additionally, older age, high blood pressure, and nondipper pattern are important risk factors of LVH.

Factors associated with insulin resistance after long-term renal transplantation.

Insulin resistance (IR) is an early and very strong predictor of posttransplantation diabetes mellitus as well as an important cardiovascular risk factor even in the absence of hyperglycemia. Patients after renal transplantation are insulin resistant compared with a control group with similar demographic characteristics. The aim of this study was to determine the frequency of IR in renal allograft patients without glucose disorders, to correlate IR indexes with the doses of immunosuppressive medications, and to examine other risk factors, such as age, obesity, and antihypertensive therapy used. One hundred six patients who received a kidney transplant at Baskent University Hospital between 1992 and 2006 were enrolled the study. IR was diagnosed by using homeostasis model assessment (HOMA); 53.8% of the patients (n=57) had IR. HOMA-IR was correlated with age, body mass index, and waist-hip ratio (P values .004, .001, and .000, respectively). In regression analysis, only waist-hip ratio was significantly associated with HOMA-IR. Our results indicate that abdominal waist-hip ratio is a major determinant of IR after renal transplantation. Even in the absence of hyperglycemia, renal transplant patients may have IR. If obesity is prevented, long-term patient and graft survival may be improved.