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Currently, a high prevalence of hypophosphatemia exists in Portuguese HD patients. This condition is associated with worst nutritional and body composition parameters. In the context of additional indices of malnutrition (low albumin, low BMI or severe overhydration), hypophosphatemic patients presented higher mortality risk.

Monitoring nutritional parameters is an integral part of hemodialysis (HD) patient treatment program. The purpose of this study was to evaluate the impact of the personalized nutritional counseling (PNC) on calcium-phosphorus metabolism, potassium, albumin, protein intake, interdialytic weight gain (IDWG), body composition parameters and fluid overload in HD patients. This was a multicenter longitudinal intervention study with 6 months of follow-up and 731 patients on maintenance HD from 34 dialysis units in Portugal were enrolled. Biochemical and body composition parameters were measured at baseline, 1, 3 and 6 months after the PNC. Patient's mean age was 64.9 (95% confidence interval [CI]: 63.8-66.0) years and mean HD time was 59.8 (95% CI: 55.3-64.3) months. Regarding data comparison collected before PNC vs. 6 months after, we obtained, respectively, the following results: patients with normalized protein catabolic rate (nPCR) ≥ 1 g/kg/day = 66.5% vs. 73.5% (P = 0.002); potassium > 5.5 mEq/L = 52% vs. 35.8% (P < 0.001); phosphorus between 3.5 and 5.5 mg/dL = 43.2% vs. 52.5% (P < 0.001); calcium/phosphorus (Ca/P) ratio ≤ 50 mg/dL = 73.2 % vs. 81.4% (P < 0.001); albumin ≥ 4.0 g/dL = 54.8% vs. 55% (P = 0.808); presence of relative overhydration = 22.4% vs. 25% (P = 0.283); IDWG > 4.5% = 22.3% vs. 18.2% (P = 0.068). PNC resulted in a significant decrease in the prevalence of hyperkalemia, hypophosphatemia and also showed amelioration in Ca/P ratio, nPCR and an increase in P of hyphosphatemic patients. Our study suggests that dietetic intervention contributes to the improvement of important nutritional parameters in patients receiving hemodialysis treatment.

Background: Hemodialysis (HD) patients are vulnerable to multiple metabolic and nutrition derangements, leading to changes in body composition. Handgrip strength (HGS) has been used as a nutrition marker. We aimed to evaluate the relationship between HGS and lean tissue mass (LTM) with several parameters in HD patients and develop HGS predictive equations. Methods: Cross‐sectional study with 155 patients in HD treatment for ≥3 months. Body composition was assessed through bioimpedance spectroscopy. HGS was measured with a hydraulic hand dynamometer. Biochemical parameters were evaluated. Data were analyzed by sex. Results: Ninety‐four were men, and mean age was 64.4 ± 14.7 years. We found positive correlation of HGS with LTM, lean tissue index, and body cell mass and negative correlation between HGS, age, and overhydration in both sexes. Serum albumin level presented a positive correlation and magnesium a negative correlation with HGS only in men. The LTM presented a positive correlation with protein intake, serum albumin level, and body cell mass and a negative correlation with age in both groups. A significant positive correlation with magnesium and a negative correlation with overhydration were observed in men. The predictability of the models was R2 = 0.618 for men and R2 = 0.500 for women. Conclusion: HGS is highly correlated with LTM, and both differ between sexes and are, therefore, differently correlated with the parameters studied. Body composition, overhydration, and some biochemical parameters explain changes in HGS. Predictive models including body composition and biochemical parameters may explain at least 50% of the variance of HGS.

Objective Evaluate which of two combinations of parameters based on International Society of Renal Nutrition and Metabolism recommendations could better identify patients with protein‐energy wasting (PEW) and to compare the relationship of these two combinations with other clinical and body composition parameters. Methods This was a multicentre longitudinal study with 24 months of follow‐up. The PEW patients were characterized by: Group A (GA) – normalized protein catabolic rate (nPCR) < 1.0 g/kg per day, albumin <3.8 g/dL and body cell mass index (BCMI) < 6.4 kg/m2 (n = 203); Group B (GB) – nPCR <1.0 g/kg per day, albumin <3.8 g/dL and body mass index (BMI) <23 kg/m2 (n = 109). All the patients who did not meet these requirements were considered “well‐nourished” (GA: n = 1818; GB: n = 3292). Results When compared to the well‐nourished patients, PEW patients in the GA presented higher age, Kt/V, C‐reactive protein, relative overhydration, fat tissue index (FTI); lower creatinine, albumin, nPCR, PTH, haemoglobin, phosphorus, calcium X phosphorus product, potassium, dry weight, BMI, BCMI, lean tissue index, %IDWG . In the GB, well‐nourished patients FTI was significantly higher. In Cox analysis, the combination with BCMI was a strong independent predictor of mortality in these patients (hazard ratio: 1.48; confidence interval: 1.00–2.19; P = 0.048), even after adjustment. Although GB combination seemed to be also a predictor of death (hazard ratio: 2.67; confidence interval: 1.92–3.71; P < 0.001), when adjusted, the association remained no longer significant. Conclusion A new combination of parameters including protein intake, albumin and BCMI demonstrated significant associations with other nutrition and inflammation parameters as well as with mortality.

Depending on the gender, different parameters such as protein intake, potassium, phosphorus, body mass index and albumin are associated with mortality in patients undergoing HD. Albumin <3.5 g/dl is an independent mortality predictor in both genders, whereas a body mass index <23 kg/m is an independent predictor of death, but only in men.

Introduction: Body cell mass (BCM) is a useful nutritional marker and is not affected by changes in the hydration status that commonly occur in hemodialysis (HD) patients. This study aimed to examine the association between body cell mass index (BCMI) and nutritional parameters, as well as its relationship with long-term survival in these patients.Methods: This longitudinal prospective multicenter study followed a cohort of patients in HD for 24 months. The clinical parameters of 2527 patients (mean age 70.3 AE 14.6 years, 55.8% male and mean HD vintage 58 (IQR:33-95) months) were measured and their body composition parameters were assessed by a body composition monitor before the HD session. BCM was converted to BCMI (BCM/height 2 ) and, taking into account the mean value (6.4 AE 2.1 kg/m 2 ), we split our study population into 2 groups: G1 (BCMI <6.4 kg/m 2 ; n = 1366) and G2 (BCMI ≥ 6.4 kg/m 2 ; n = 1161). All statistical tests were performed using SPSS 20.0 software. A P value lower than 0.05 was considered statistically significant.Findings: Patients with a BCMI <6.4 kg/m 2 displayed higher age (P < 0.001), dialysis adequacy (Kt/V) (P < 0.001), total cholesterol (TC) (P = 0.033), high-density lipoprotein cholesterol (HDL-C) (P < 0.001), relative overhydration (overhydration/extracellular water [OH/ECW]) (P < 0.001), CRP (P < 0.001), fat tissue index (FTI) (P < 0.001) and lower normalized protein equivalent of nitrogen appearance (nPNA) (P < 0.001), albumin (P < 0.001), serum creatinine (P < 0.001), creatinine index (P < 0.001), potassium (P < 0.001), phosphorus (P < 0.001), calcium/phosphorus product (Ca X P) (P < 0.001), lean tissue index (LTI) (P < 0.001) and body mass index (BMI) (P = 0.046). The Kaplan-Meier survival curve showed a significantly better survival in female and male patients with BCMI ≥6.4 kg/m 2 (P = 0.001 and P < 0.001, respectively). In the cox regression analysis, a significantly higher mortality risk was observed in G1 patients (P = 0.001).Discussion: Our study showed that a low BCMI was a mortality predictor and was associated with worse nutritional parameters in patients undergoing HD.