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Recent studies demonstrate that the edema index (ECW/TBW) may be a significant predictor of poor outcomes as a composite of overhydration and protein-energy wasting. There is no consensus regarding ECW/TBW cut-off values. We aimed to determine the performance of ECW/TBW in all-cause mortality prediction and to establish certain cut-off values in patients on chronic hemodialysis.Body composition of 158 hemodialysis patient was performed by using InBody S10 (Biospace, Seoul, Korea) analyzer. Demographic profile and laboratory data were collected. Subjective Global Assessment Scale (SGA) was used to assess nutrition status. In the mean follow up of 3.5 ± 1.15 years, two independent clinicians evaluated death cases and factors for all-cause mortality were established. Statistical analysis was performed with R software.73 of 158 hemodialysis patients were on kidney transplant waiting list. Mean age of study subjects was 53.6 ± 15.1 years, 51.9% were females, and 13.9% had diabetes. During the follow-up period, 17.72% of patients died. They had significantly higher ECW/TBW values 0.393 vs 0.408, p 0.001. Subjects with lower edema index had better nutrition according to SGA (SGA A 0.391; SGA B 0.400; SGA C 0.413; p 0.001). The calculated ECW/TBW cut-off point for all-cause mortality was 0.4055, with sensitivity of 84.6%, specificity of 69.8%. On the other hand, the cut-off point for SGA scores B and C was 0.396 with sensitivity of 72.7% and specificity of 68.7%.The manufacturer provided ECW/TBW cut-off point of 0.400 should be addressed carefully, because it varies depending on the selected outcome and population studied. InBody ECW/TBW reference values from 0.390 to 0.410 are the most promising in hemodialysis population to assess all-cause mortality, nutrition status and body composition.

Hypertension is a leading risk factor for cardiovascular events and death. A reduction in salt intake is among the most cost-effective strategies to reduce blood pressure and the risk of cardiovascular diseases. Increasing potassium lowers blood pressure and is associated with lower cardiovascular risk. Adequate iodine intake is important to prevent iodine deficiency disorders. Salt iodization is a key strategy to prevent such deficiency. In Lithuania, no surveys have been performed to directly assess sodium, potassium and iodine consumption. The aim of the present study was to measure sodium, potassium and iodine intake in a randomly selected adult Lithuanian adult population using 24 h urine collections, and to assess knowledge, attitudes and behavior towards salt consumption. Salt and potassium intakes were estimated in 888 randomly selected participants by 24 h urine sodium and potassium excretion and 679 individuals provided suitable 24 h urine samples for the analysis of iodine excretion. Average salt intake was 10.0 (SD 5.3) g/24 h and average potassium intake was 3.3 (SD 1.3) g/24 h. Only 12.5% of participants consumed less than 5 g/24 h of salt. The median value of urinary iodine concentration (UIC) was 95.5 μg/L. Our study showed that average salt intake is twice as high as the maximum level recommended by the World Health Organization while potassium and iodine intakes in Lithuania are below the recommended levels.

Background and Objectives: Kidney transplant recipients represent a unique population with metabolic abnormalities, altered nutritional and immune status, as well as an imbalanced regulation of adipocytokine metabolism. Leptin is a hormonally active protein mainly produced by fat tissue that modulates appetite, satiety, and influences growth, energy, and bone metabolism. There has been great interest in the role of this hormone in chronic kidney disease-related protein energy wasting, thus, a positive leptin correlation with body mass index and fat mass was confirmed. This study was designed to determine the association of pre and post-kidney transplant leptin concentration with nutritional status and body composition. Materials and Methods: We studied 65 kidney transplant recipients. Nutritional status was evaluated before kidney transplantation and 6 months later using three different malnutrition screening tools (Subjective Global Assessment Scale (SGA), Malnutrition Inflammation Score (MIS), and Geriatric Nutritional Risk Index (GNRI)), anthropometric measurements, and body composition (bioelectrical impedance analysis (BIA)). Demographic profile, serum leptin levels, and other biochemical nutritional markers were collected. Statistical analysis was performed with R software. Results: Median age of the studied patients was 45 years, 42% were females, and 12% had diabetes. Leptin change was associated with body weight (p &lt, 0.001), waist circumference (p &lt, 0.001), fat mass (p &lt, 0.001) and body fat percentage (p &lt, 0.001), decrease in parathyroid hormone (PTH) (p &lt, 0.001) transferrin (p &lt, 0.001), diabetes mellitus (p = 0.010), and residual renal function (p = 0.039), but not dependent on dialysis vintage, estimated glomerular filtration rate (eGFR), or delayed graft function at any time during the study. After adjustment for age and sex, body mass index (BMI) (p &lt, 0.001), and body fat percentage (p &lt, 0.001) were independent variables significantly associated with post-transplant leptin change. Lower leptin values were found both before and after kidney transplantation in the SGA B group. GNRI as a nutritional status tool was strongly positively related to changes in leptin within the 6-month follow-up period. Conclusions: Kidney transplant recipients experience change in leptin concentration mainly due to an increase in fat mass and loss of muscle mass. GNRI score as compared to SGA or MIS score identifies patients in whom leptin concentration is increasing alongside an accumulation of fat and decreasing muscle mass. Leptin concentration evaluation in combination with BIA, handgrip strength measurement, and GNRI assessment are tools of importance in defining nutrition status in the early post-kidney transplant period.

Gordonia species are aerobic, weakly acid-fast, Gram-positive pathogens that rarely cause human infections, usually in immunocompromised patients. It is uncommon bacilli in cases of peritoneal dialysis-related peritonitis. The small number of infections with Gordonia species reported for humans may be stipulated by the difficulty in identifying the organism using conventional techniques. Careful review of Gram stains and modified-acid-fast stains should be done, so that confusion with other actinomycetes is minimized, pending the genotypic identification. Here we report a case that was caused by Gordonia bronchialis and thus required different considerations of treatment.

Psoriasis vulgaris is not frequently seen in patients with renal replacement therapy, especially in patients on peritoneal dialysis. Dialysis also has been reported to improve psoriatic skin lesions with a much higher response rate for peritoneal dialysis than haemodialysis. Conversely, we present a case of a man who developed psoriasis after 16 months of peritoneal dialysis. Discontinuation of icodextrin as a possible factor provoking systemic inflammation had no impact on the course of the disease. In this report, we review the existing studies and counsel caution against optimistic expectations of benefits from dialysis in patients with psoriasis.

To determine the most potent bioelectrical impedance analysis (BIA) marker of malnutrition and to adjust its application to hemodialysis (HD) patients.An observational study.A total of 99 patients on maintenance HD were enrolled in the study.The nutritional state of the patients was examined before and after the HD procedure using Subjective Global Assessment Scale (SGA), serum albumin, body mass index and BIA-derived fat-free mass index, reactance, resistance, and phase angle (PA). Malnutrition defined by the SGA questionnaire was used to detect the most potent marker of malnutrition. This marker was further analyzed and corrected for the excess fluid, age, and gender producing the nutritional state-specific cutoffs.The SGA rates of nutritional state were as follows: 57.6% (57) well nourished, 28.3% (28) moderately malnourished, and 14.1% (14) severely malnourished. Multivariate forward logistic regression analysis of the nutrition markers revealed PA as the most potent malnutrition predictor (odds ratio = 3.69; 95% confidence interval [CI]: 1.59-8.62; P = .002). PA was adjusted for the excess fluid (5.00 ± 0.97 vs 4.87 ± 1.08 P .001). Patients were assigned into groups with adjusted PA values below the 5th through the 50th percentile of the mean PA reference value. The moderately malnourished patients were most accurately identified by the percentile group of25th (area under the curve = 0.70; 95% CI: 0.60-0.81; P = .001), and the severely malnourished patients were most accurately identified by the percentile group of15th (area under the curve = 0.74; 95% CI: 0.62-0.85; P = .005).Malnutrition is present almost in a half of the HD patients. BIA-provided PA is the most potent predictor of malnutrition. PA can be adjusted for the excess fluid after HD, age, and gender and used accordingly.