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Background Handgrip strength (HS) measures have been associated with nutritional status, morbidity, and mortality in end stage of renal disease (ESRD). Objective We aimed to present and discuss the HS method in ESRD patients, by reviewing published studies on the subject. Methods PUBMED, MEDLINE, and LILACS databases were consulted, with no filters regarding the date of publication or age of population. Results The terms “handgrip strength,” “end stage of renal disease,” and “nutrition status” were used, and 32 articles with publication dates from 1983 to 2017 were included. Handgrip strength is considered a simple and rapid method of assessing muscle function in chronic kidney disease and is an important predictor of nutritional status depletion, development of comorbidities, and early mortality. Conclusion There is a lack of studies that analyzed associations between HS and clinical and nutritional outcomes in ESRD. The establishment of HS protocols and reference values in ESRD are necessary, to assist preventive measures of unfavorable outcomes in this population.

Surviving acute kidney (AKI) patients have a higher late mortality compared with those admitted without AKI. The negative impact of malnutrition on the early outcome of AKI patients has recently been confirmed by various studies. However, its impact after hospital discharge has not been studied. The objective of the study was to determine the role of anthropometric measurements and handgrip strength as predictors of mortality 180 days after discharge.Eighty-two survivors AKI patients who were older than 18 y old and followed by AKI team were prospectively evaluated. Patient's characteristics were recorded, anthropometric measurements were taken, handgrip strength (HGS) was measured, subjective global assessment and bioimpedance were applied and blood samples were collected during hospitalization at first and last nephrologist evaluation and in after hospital discharge at 1 month, 3 and 6 months. Multivariable logistic regression was used to adjust confounding and selection bias.Age was 62.3 ± 14.7 years, prevalence of hospitalization in medical wards of 71.6%, index of severity of AKI (ATN-ISS) was 28% and late mortality rates was 25.6%. Risk factors associated with late mortality were the number of comorbidities (HR = 1.79, 95% CI = 1.45-2.46, p = 0.04), cancer (HR = 1.89, 95 CI% = 1.48-3.16, p = 0.01), sepsis (HR = 1.47, 95% CI = 1.18-2.38, p = 0.03), no recovery of renal function at hospital discharge (HR = 1.46, 95% CI = 1.02-2.16, p = 0.03), malnutrition at first evaluation (HR = 1.58, 95% CI = 1.14-2.94, p = 001), the HGS value at the moment of last evaluation by nephrologist (HR = 1.81, 95% CI = 1.17-2.31, p = 0.04) and gain weigh 1 kg between the moment at first evaluation by nephrologist and one month after hospital discharge (HR = 1.95, 95 CI% = 1.29-3.3, p = 0.02).HGS and gain weight were identified as predictors of late mortality. Simple and ease methods can be applied in AKI patients during and after hospitalization to diagnose nutritionally patients who are at higher risk for poor prognosis and, consequently intervention measures can be performed to improve survival in long-term.

Background: The determination of resting energy expenditure (REE) in critically ill patients is essential to prevent hypo and hyper alimentation.

Summary Background/aims Protein-energy wasting (PEW) is common in the end-stage of chronic kidney disease (CKD) and can be caused by factors related to poor dietary intake and changes in energy expenditure. Indirect calorimetry (IC) is the gold standard method to measure resting energy expenditure (REE), however, it is not much available and it is common to use predictive formulas of REE in clinical practice. This study compared the values of REE measured by IC to those estimated by Harris & Benedict formula, the most one used in clinical practice in Brazil. Methods Patients with stage 5 CKD (an estimated glomerular filtration rate 18 years old were included and submitted to the IC test and Harris & Benedict's predictive formula. The assessments were performed at three moments: pre-dialysis indications (P1), at the beginning of dialysis indication (P2) and 30 days after the start of dialysis therapy (P3). Tuckey's test was used to compare energy expenditure variable by groups, and the Bland & Altman analysis was used to compare the agreement between the methods. A significance level of p Results Thirty-five patients with mean age of 61.2 ± 10.9 years were included, 60% female, 17% afrodescendants and 60% with diabetes mellitus. There were no significant differences in REE between the three moments (P1: 1289.8 ± 382.7 kcal, P2: 1218.2 ± 362.8 kcal, P3: 1269.5 ± 335.1 kcal, p = 0.874). Harris & Benedict formula did not show IC agreement for the REE measurement because it presented high limits of agreement or because of the low precision of the estimated measure. Conclusion This study showed that there was no significant alteration of REE by IC and that REE values estimated by Harris & Benedict formula did not agree with the values measured by IC in this population. The role of Harris & Benedict formula should be re-evaluated in stage 5 CKD patients.

Background The determination of resting energy expenditure (REE) in critically ill patients could prevent complications such as hypo- and hyperalimentation. This study aims to describe the REE in septic patients with and without acute kidney injury (AKI) and compare the REE estimated by the Harris-Benedict equation (HB) with the REE measured by indirect calorimetry (IC). Methods Prospective and observational study was performed. Septic patients older than 18 years, undergoing mechanical ventilation, with or without AKI defined by KDIGO criteria, and admitted to the Intensive Care Unit of University Hospital from Brazil were included. The REE was estimated by HB equation and measured by the IC within 72 h after the diagnosis of sepsis and 7 days after the initial measure. Results Sixty-eight patients were evaluated, age was 62.5 ± 16.6 years, 64.7% were male, 63.2% had AKI, and SOFA was 9.8 ± 2.35. The measured REE was 1857.5 ± 685.32 kcal, while the estimated REE was 1514.8 ± 356.72 kcal, with adequacy of 123.5 ± 43%. Septic patients without AKI (n = 25) and with AKI (n = 43) had measured REE statistically higher than the estimated one (1855.0 (1631.75–2052.75) vs. 1551.0 kcal (1349.0–1719.25), p = 0.007 and 1868.0 (1219.5–2364.75) vs. 1388.0 kcal (1254.0–1665.5), p = 0.026, respectively). There was no significant difference between the two groups (with and without AKI) in measured and estimated REE (p = 0.63 and 0.64, respectively). There was no significant difference in evolutional REE (1845.95 ± 658.27 kcal vs. 1809.54 ± 755.08 kcal, p = 0.86). Conclusions The REE measured by IC was significantly higher than that estimated by HB equation in both septic with and without AKI. There was no significant difference in REE between the septic patients with and without AKI, suggesting that AKI does not influence the energy metabolism of septic patients.

Acute renal injury (AKI) interferes greatly with nutritional status, affecting the metabolism of all macronutrients and increased mortality rates in hospitalized patients. Our objective was to evaluate the association of nutritional parameters (albumin, cholesterol, caloric and protein intake and nitrogen balance (NB)) with mortality in patients with AKI.This is a prospective observational study that evaluated 595 consecutive patients over the age of 18 years with AKI, requiring enteral or parenteral feeding. At the time of the patient's enrollment, demographic and laboratorial data, caloric and protein supply and NB were recorded on the first day of referral to the nephrologist. All patients were followed throughout the hospital stay and mortality rate was also recorded.The medium age of patients with AKI was 64 (54-75) years, 64.5% male, 62% admitted to intensive care unit (ICU), 52% on dialysis and the majority (48%) were at stage 3 by AKIN. Length of stay and hospital mortality were 18 (10-31) days and 46%, respectively. Superior age, AKI severity, lower body weight and body mass index (BMI), higher need for dialysis, ICU admission and shorter hospital stay were associated with higher mortality. At logistic regression, caloric (OR: 0.946; CI:95%: 0.901-0.994; p:0.029) and protein intake (OR: 0.947; CI:95%: 0.988-0.992; p = 0.028) and serum albumin (OR: 0.545; CI:95%: 0.401-0741; p 0.001) were associated with hospital mortality. Cholesterol (OR: 0.995; CI:95%: 0.991-1.000; p = 0.052) was not associated with increased mortality in the adjusted analysis. Analysis of the receiver operating characteristic (ROC) curve showed that calorie intake 12 kcal/kg (AUC: 0.745; CI:95%: 0.684-0.765; p 0.001) and protein intake 0.5 g/kg (AUC: 0.726; CI:95%: 0.686-0.767; p 0.001) were predictors of hospital mortality, as well as a negative NB -6.47 g N/day (AUC: 0.745; CI:95%: 0.704-0.786; p 0.001).In conclusion, low caloric and protein intake, negative NB and low albumin value are conditions associated with higher hospital mortality in patients with AKI.

Background Chronic kidney disease is worldwide recognized as a public health problem due to high rates of morbidity and mortality. At the end stage of the disease, which the glomerular filtration rate is equal or less than 15 ml/min/1.73 m2, dialysis initiation is usually indicated. In the absence of a consensus on the best time of beginning, the aim of this study was to identify clinical and nutritional factors associated with clinical outcomes with the start of dialysis and death. Methods In a prospective cohort of 82 patients, clinical (underlying renal disease, renal survival time, systolic and diastolic blood pressure, estimated glomerular filtration rate) and nutritional data (protein intake, anthropometry, bioelectrical impedance test, and strength handgrip) were collected. We used mean and standard deviation or median and association of the variables with the outcome entry into dialysis or death, and a Cox regression model was applied. Statistical significance was p Results Fifty-eight patients were included in group 1—G1 (without dialysis)—and 24 patients in group 2—G2 (dialysis). The groups were different in blood urea nitrogen (p = p = 0.003), estimated glomerular filtration rate (p = 0.002), and serum phosphorus (p = 0.002). After multivariate analysis, only serum albumin (HR 0.342, p = 0.004) and glomerular filtration rate (HR 0.001, p = 0.001) were associated with entry into dialysis and death. Conclusions We concluded that lower levels of serum albumin and glomerular filtration rate values are associated with entry into dialysis or death.

Summary Patients on intensive care present systemic, metabolic, and hormonal alterations that may adversely affect their nutritional condition and lead to fast and important depletion of lean mass and malnutrition. Several factors and medical conditions can influence the energy expenditure (EE) of critically ill patients, such as age, gender, surgery, serious infections, medications, ventilation modality, and organ dysfunction. Clinical conditions that can present with EE change include acute kidney injury, a complex disorder commonly seen in critically ill patients with manifestations that can range from minimum elevations in serum creatinine to renal failure requiring dialysis. The nutritional needs of this population are therefore complex, and determining the resting energy expenditure is essential to adjust the nutritional supply and to plan a proper diet, ensuring that energy requirements are met and avoiding complications associated with overfeeding and underfeeding. Several evaluation methods of EE in this population have been described, but all of them have limitations. Such methods include direct calorimetry, doubly labeled water, indirect calorimetry (IC), various predictive equations, and, more recently, the rule of thumb (kcal/kg of body weight). Currently, IC is considered the gold standard.