scholarly journals Performance of Bioelectrical Impedance and Anthropometric Predictive Equations for Estimation of Muscle Mass in Chronic Kidney Disease Patients

2021 ◽  
Vol 8 ◽  
Author(s):  
Natália Tomborelli Bellafronte ◽  
Lorena Vega-Piris ◽  
Guillermina Barril Cuadrado ◽  
Paula Garcia Chiarello
Keyword(s):  
Chronic Kidney Disease ◽  
Body Composition ◽  
Regression Analysis ◽  
Kidney Disease ◽  
Muscle Mass ◽  
Linear Regression Analysis ◽  
Bioelectrical Impedance ◽  
Fat Free Mass ◽  
Predictive Equation ◽  
Predictive Equations

Background: Patients with chronic kidney disease (CKD) are vulnerable to loss of muscle mass due to several metabolic alterations derived from the uremic syndrome. Reference methods for body composition evaluation are usually unfeasible in clinical settings.Aims: To evaluate the accuracy of predictive equations based on bioelectrical impedance analyses (BIA) and anthropometry parameters for estimating fat free mass (FFM) and appendicular FFM (AFFM), compared to dual energy X-ray absorptiometry (DXA), in CKD patients.Methods: We performed a longitudinal study with patients in non-dialysis-dependent, hemodialysis, peritoneal dialysis and kidney transplant treatment. FFM and AFFM were evaluated by DXA, BIA (Sergi, Kyle, Janssen and MacDonald equations) and anthropometry (Hume, Lee, Tian, and Noori equations). Low muscle mass was diagnosed by DXA analysis. Intra-class correlation coefficient (ICC), Bland-Altman graphic and multiple regression analysis were used to evaluate equation accuracy, linear regression analysis to evaluate bias, and ROC curve analysis and kappa for reproducibility.Results: In total sample and in each CKD group, the predictive equation with the best accuracy was AFFMSergi (men, n = 137: ICC = 0.91, 95% CI = 0.79–0.96, bias = 1.11 kg; women, n = 129: ICC = 0.94, 95% CI = 0.92–0.96, bias = −0.28 kg). AFFMSergi also presented the best performance for low muscle mass diagnosis (men, kappa = 0.68, AUC = 0.83; women, kappa = 0.65, AUC = 0.85). Bias between AFFMSergi and AFFMDXA was mainly affected by total body water and fat mass. None of the predictive equations was able to accurately predict changes in AFFM and FFM, with all ICC lower than 0.5.Conclusion: The predictive equation with the best performance to asses muscle mass in CKD patients was AFFMSergi, including evaluation of low muscle mass diagnosis. However, assessment of changes in body composition was biased, mainly due to variations in fluid status together with adiposity, limiting its applicability for longitudinal evaluations.

scholarly journals Development and Validation of Bioelectrical Impedance Analysis Equations in Adolescents with Severe Obesity

2019 ◽  
Vol 149 (7) ◽  
pp. 1288-1293 ◽  
Author(s):  
Alissa Steinberg ◽  
Cedric Manlhiot ◽  
Ping Li ◽  
Emma Metivier ◽  
Paul B Pencharz ◽  
...  
Keyword(s):  
Body Composition ◽  
Bioelectrical Impedance Analysis ◽  
Severe Obesity ◽  
Validation Cohort ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Fat Free Mass ◽  
Predictive Equation ◽  
Predictive Equations ◽  
Squared Prediction Error

ABSTRACT Background Body mass index measures excess weight for size, and does not differentiate between fat mass (FM) and fat-free mass (FFM). Bioelectrical impedance analysis (BIA) is most commonly used to assess FM and FFM as it is simple and inexpensive. Variables from BIA measurements are used in predictive equations to estimate FM and FFM. To date, these equations have not been validated for use in adolescents with severe obesity. Objectives In a cohort of adolescents with severe obesity (SO), a BMI ≥ 120% of the 95th percentile, this study aimed to 1) derive a BIA predictive equation data from air displacement plethysmography (ADP) measurements; 2) reassess the equation in a second validation cohort; and 3) compare the accuracy of existing body composition equations. Methods Adolescents with SO were assessed using ADP and BIA. FM values derived from ADP measurements from the first cohort (n = 27) were used to develop a BIA predictive equation (i.e., Hamilton). A second cohort (n = 65) was used to cross-validate the new and 9 existing BIA predictive equations. Results Ninety-two adolescents (15.8 ± 1.9 y; BMI: 46.1 ± 9.9 kg/m2) participated. Compared with measured FFM using ADP: 1) the Lazzer, Hamilton, Gray, and Kyle equations were without significant bias; 2) the Hamilton and Gray equations had the smallest absolute and relative differences; 3) the Kyle and Gray equations showed the strongest correlation; 4) the Hamilton equation most accurately predicted FFM within ± 5% of measured FFM; and 5) 8 out of 9 equations had similar root mean squared prediction error values (6.03–6.64 kg). Conclusion The Hamilton BIA equation developed in this study best predicted body composition values for groups of adolescents with severe obesity in a validation cohort.

scholarly journals Bed-side measures for diagnosis of low muscle mass, sarcopenia, obesity, and sarcopenic obesity in patients with chronic kidney disease under non-dialysis-dependent, dialysis dependent and kidney transplant therapy

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242671
Author(s):  
Natália Tomborelli Bellafronte ◽  
Gabriel Ruiz Sizoto ◽  
Lorena Vega-Piris ◽  
Paula Garcia Chiarello ◽  
Guillermina Barril Cuadrado
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Muscle Mass ◽  
Area Under The Curve ◽  
Bioelectrical Impedance ◽  
Fat Free Mass ◽  
Sarcopenic Obesity ◽  
Anthropometric Parameters ◽  
Hand Grip ◽  
European Working

Muscle depletion and sarcopenic obesity are related to a higher morbimortality risk in chronic kidney disease (CKD). We evaluated bed-side measures/indexes associated with low muscle mass, sarcopenia, obesity, and sarcopenic obesity in CKD and proposed cutoffs for each parameter. Sarcopenia was diagnosed according to the European Working Group on Sarcopenia in Older People revised consensus applying dual energy X-ray absorptiometry (DXA) and hand grip strength (HGS), and obesity according to the International Society for Clinical Densitometry. Anthropometric parameters including calf (CC) and waist (WC) circumferences and WC/height (WC/H); bioelectrical impedance data including appendicular fat free mass (AFFM) and fat mass index (FMI) were assessed. ROC analysis and area under the curve (AUC) were applied for performance analyses. AFFM and CC presented the best performances for low muscle mass diagnosis–AFFM AUC for women was 0.96 and for men, 0.94, and CC AUC for women was 0.89 and for men, 0.85. FMI and WC/H were the best parameters for obesity diagnosis–FMI AUC for women was 0.99 and for men, 0.96, and WC/H AUC for women was 0.94 and for men, 0.95. The cutoffs (sensibility and specificity, respectively) for women were AFFM≤15.87 (90%; 96%), CC≤35.5 (76%; 94%), FMI>12.58 (100%; 93%), and WC/H>0.66 (91%; 84%); and for men, AFFM≤21.43 (98%; 84%), CC≤37 (88%; 69%), FMI>8.82 (93%; 88%), and WC/H>0.60 (95%; 80%). Sensibility and specificity for sarcopenia diagnosis were for AFFM+HGS in women 85% and 99% and in men, 100% and 99%; for CC+HGS in women 85% and 99% and in men, 100% and 100%; and for sarcopenic obesity were for FMI+AFFM in women 75% and 97% and in men, 75% and 95%. The tested bed-side measures/indexes presented excellent performance.

scholarly journals Agreement and bias in the estimation of fat free mass using bioelectrical impedance analysis and a resistance and reactance- based formula for the Mexican adults: A study from Merida, Yucatan

2021 ◽  
Vol 64 (2) ◽  
pp. 91-98
Author(s):  
Sudip Datta Banik
Keyword(s):  
Body Composition ◽  
Regression Analysis ◽  
Bioelectrical Impedance Analysis ◽  
Linear Regression Analysis ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Fat Free Mass ◽  
Altman Plot ◽  
Bland Altman Plot ◽  
Mexican Adults

Bioelectrical impedance analysis (BIA) is used to estimate body composition characteristics. The values of body fat and fat free mass (FFM) are obtained as per algorithms of the device that are often unknown to the researchers. Some models of the analyzer provide resistance and reactance values that may be useful to estimate FFM. Objective of the present study was to test the agreement and proportional bias in the estimation of FFM obtained through BIA and that derived from the resistance and reactance values using a formula for Mexican adults. A cross-sectional study was carried out in 2019 selected 60 university male students aged 21 to 23 years from Merida, Yucatan. A multifrequency whole body bioelectrical impedance analyzer Tanita MC 180 MA (Tanita Corporation, Tokyo-Japan) was used to evaluate body composition characteristics. The device gives estimates of FFM in kg (based on algorithm) and the resistance and reactance values (ohms). There is an existing formula for Mexican adults to estimate FFM (FFM_FOR) from the resistance and reactance values obtained through BIA. An agreement between the two estimates of FFM has been tested using Bland-Altman plot and linear regression analysis. Mean value of age of the participants was 21.88 years. FFM estimated by BIA (FFM_BIA = 41.44 kg) and that derived from FFM_FOR (41.36 kg) had signifi cant intraclass correlation coeffi cient (ICC) (Cronbach’s alpha = 0.99, p<0.0001). One sample t-test estimating the diff erence of mean values between FFM_BIA and FFM_FOR was not signifi cant (t = 1.37, mean diff erence -0.02, p = 0.18). The Bland-Altman plot shows almost all data points lie within 95% confi dence interval limits. A linear regression analysis using the diff erence of FFM values as dependent variable and the average of the measurements as the independent variable showed no signifi cant interrelationships. In conclusion, the formula to estimate FFM using the resistance and reactance values of BIA has been found to be useful in the present study.

scholarly journals A specific bioelectrical impedance equation to predict body composition in Turner's syndrome

2010 ◽  
Vol 54 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Alexis D. Guedes ◽  
Bianca Bianco ◽  
Mônica V. N. Lipay ◽  
Emmanuela Q. Callou ◽  
Marise L. Castro ◽  
...  
Keyword(s):  
Body Composition ◽  
Linear Regression Analysis ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Fat Free Mass ◽  
X Ray ◽  
Great Consistency ◽  
Total Fat ◽  
Specific Equation ◽  
Standard Error Estimate

INTRODUCTION: Cardiovascular disease is one of the main causes for Turner syndrome (TS) mortality and the evaluation of its risk factors such as excess body fat and its distribution is considered one of the major aspects of the adult patient care. OBJECTIVE: To develop and validate a specific bioelectrical impedance analysis (BIA) equation to predict body composition in TS patients. SUBJECTS AND METHODS: Clinical and anthropometric data, dual-energy X-ray absorptiometry (DXA) for total fat-free mass (FFM) and BIA for resistance and reactance were obtained from 50 adult TS patients. Linear regression analysis was performed with multiple clinical and BIA data to obtain a predicting equation. RESULTS: The equation developed to estimate FFM in adult TS patients showed great consistency with DXA, elevated correlation (r = 0. 974) and determination (r² = 0. 948) coefficients and an adequate standard error estimate (SEE = 1.52 kg). CONCLUSIONS: The specific equation developed here allowed making an adequate FFM estimate in adult TS patients.

scholarly journals Relationships of Fat and Muscle Mass with Chronic Kidney Disease in Older Adults: A Cross-Sectional Pilot Study

2020 ◽  
Vol 17 (23) ◽  
pp. 9124
Author(s):  
Bokun Kim ◽  
Hyuntae Park ◽  
Gwonmin Kim ◽  
Tomonori Isobe ◽  
Takeji Sakae ◽  
...  
Keyword(s):  
Older Adults ◽  
Chronic Kidney Disease ◽  
Pilot Study ◽  
Kidney Disease ◽  
Muscle Mass ◽  
Estimated Glomerular Filtration Rate ◽  
Fat Free Mass ◽  
Creatinine Concentration ◽  
Cross Sectional ◽  
Assess Body Composition

This cross-sectional pilot study aimed to assess the relationships of fat and muscle mass with chronic kidney disease (CKD) in older adults. Serum creatinine concentration was used to measure estimated glomerular filtration rate (mL/min/1.73 m2) in the 236 subjects, who were allocated to three groups: a normal (≥60.0), a mild CKD (45.0–59.9), and a moderate to severe CKD (<45.0) group. The Jonckheere-Terpstra test and multivariate logistic regression were employed to assess body composition trends and the relationships of % fat mass (FM) or % muscle mass index (MMI) with moderate-to-severe CKD. Body weight, fat-free mass, MMI, and %MMI tended to decrease with an increase in the severity of CKD, but the opposite trend was identified for %FM. No relationship with BMI was identified. The participants in the middle-high and highest quartile for %FM were 6.55 and 14.31 times more likely to have moderate to severe CKD. Conversely, the participants in the highest quartile for %MMI were 0.07 times less likely to have moderate to severe CKD. Thus, high fat and low muscle mass may be more strongly associated with CKD than obesity per se.

scholarly journals P0921ROLE OF UREMIC TOXIN, INDOXYL SULFATE IN SARCOPENIA OF NONDIALYSIS DEPENDENT-CHRONIC KIDNEY DISEASE PATIENTS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Jun Chul Kim ◽  
Seok Hui Kang ◽  
Miyeun Han ◽  
Su-Hyun Kim ◽  
Ran-Hui Cha ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Muscle Mass ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Indoxyl Sulfate ◽  
High Rate ◽  
Uremic Toxin ◽  
Inverse Association

Abstract Background and Aims Sarcopenia in patients with chronic kidney disease (CKD) is highly prevalent and leads to high rate of morbidity and mortality. The role of indoxyl sulfate (IS) to develop muscle wasting has been researched and proved in several animal model studies. However, there is no human data showing this relationship in CKD population. The aim of the present study was to evaluate the association between serum IS levels and each component of sarcopenia in nondialysis dependent-CKD (NDD-CKD) patients. Method We enrolled 150 NDD-CKD adult patients from 6 medical centers and collected data of demographics, blood chemistry such as indoxyl sulfate, interleukin (IL)-6, and estimated glomerular filtration rate using MDRD equation (eGFR), and body mass index (BMI, kg/m2). We also measured hand-grip strength (HGS, kg), walking speed (WS, m/s), skeletal muscle mass (SMM, kg) by bioelectrical impedance analysis (BIA). Results The numbers of male sex was 97 (64.7%). Mean age was 63.7±10.8 years old. The numbers of patients with diabetes mellitus was 77 (52.0%). Charlson comorbidity index (CCI) score was 3.9 ± 1.9. The stage of CKD ranged from 3 to 5 (eGFR=33.7±12.0 ml/min/1.73m2, mean±SD). Correlation coefficients with indoxyl sulfate levels were 0.211 for serum IL-6 level (P = 0.010), -0.212 for HGS (P = 0.009), -0.188 for WS (P = 0.021), -0.237 for SMM (P = 0.004), and -0.168 for BMI (P = 0.041), respectively. Correlation analysis showed that indoxyl sulfate levels had inverse association significantly with HGS, WS, SMM, and BMI and were positively associated with serum IL-6 levels. Conclusion Our study shows that higher serum indoxyl sulfate level was significantly associated with lower levels of muscle mass, strength, and physical performance function and higher inflammation status in non-dialysis dependent CKD patients. We suggest that the role of AST120 in prevention or treatment of sarcopenia be studied in this CKD population.

scholarly journals Estimation of body composition and water data depends on the bioelectrical impedance device

2018 ◽  
Vol 9 (1) ◽  
pp. 96-105 ◽  
Author(s):  
Natália T. Bellafronte ◽  
Marina R. Batistuti ◽  
Nathália Z. dos Santos ◽  
Héric Holland ◽  
Elen A. Romão ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Chronic Kidney Disease ◽  
Body Composition ◽  
Kidney Disease ◽  
Impedance Spectroscopy ◽  
Body Mass ◽  
Intraclass Correlation ◽  
Bioelectrical Impedance ◽  
Pearson’S Correlation ◽  
Pearson's Correlation

Abstract Overweight, obese and chronic kidney disease patients have an altered and negative body composition being its assessment important. Bioelectrical impedance analysis is an easy-to-operate and low-cost method for this purpose. This study aimed to compare and correlate data from single- and multi-frequency bioelectrical impedance spectroscopy applied in subjects with different body sizes, adiposity, and hydration status. It was a cross-sectional study with 386 non-chronic kidney disease volunteers (body mass index from 17 to 40 kg/m2), 30 patients in peritoneal dialysis, and 95 in hemodialysis. Bioelectrical impedance, body composition, and body water data were assessed with single- and multi-frequency bioelectrical impedance spectroscopy. Differences (95% confidence interval) and agreements (Bland-Atman analyze) between devices were evaluated. The intraclass correlation coefficient was used to measure the strength of agreement and Pearson’s correlation to measure the association. Regression analyze was performed to test the association between device difference with body mass index and overhydration. The limits of agreement between devices were very large. Fat mass showed the greatest difference and the lowest intraclass and Pearson’s correlation coefficients. Pearson’s correlation varied from moderate to strong and the intraclass correlation coefficient from weak to substantial. The difference between devices were greater as body mass index increased and was worse in the extremes of water imbalance. In conclusion, data obtained with single- and multi-frequency bioelectrical impedance spectroscopy were highly correlated with poor agreement; the devices cannot be used interchangeably and the agreement between the devices was worse as body mass index and fat mass increased and in the extremes of overhydration.

P0752THE EXPRESSION AND DIAGNOSTIC VALUE OF URINE ANGIOTENSINOGEN IN CHRONIC KIDNEY DISEASE

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Qiuyan Huang ◽  
Junzhe Chen ◽  
Ying Tang ◽  
Yanchun Xu ◽  
Anping Xu
Keyword(s):  
Chronic Kidney Disease ◽  
Regression Analysis ◽  
Kidney Disease ◽  
Linear Regression ◽  
Predictive Value ◽  
Linear Regression Analysis ◽  
Diagnostic Value ◽  
Glomerular Sclerosis ◽  
Ckd Stage ◽  
Stage 1

Abstract Background and Aims This article aims to detect the expression of urine angiotensinogen (uAGT) in patients with chronic kidney disease (CKD) and its correlation with clinical and renal pathology. Method Patients who diagnosed with CKD and undergoing renal biopsy for the first visit to Sun Yat-sen Memorial Hospital from March 1st ,2018 to October 1st, 2019 were enrolled. First morning urine samples from CKD patients before renal biopsy and healthy volunteers as controls were collected during the same period. These samples were tested for uAGT by ELISA. Linear regression analysis was used to explore the correlation between uAGT and clinical indicators as well as renal pathology in CKD patients. The receiver operating curve (ROC curve) was used to explore the diagnostic value of uAGT for CKD stage 3 or above and glomerular sclerosis ratio&gt;50%. Results A total of 133 CKD patients with 59 (44.4%) in stage 1, 31 (23.3%) in CKD stage 2, 17 (12.8%) in stage 3, 17 (12.8%) in stage 4 and 9 (6.7%) in stage 5 were included in our study. At the same time, 20 healthy volunteers were included as control. uAGT levels of CKD patients were significantly higher than healthy controls(275.0 vs 774.2,P&lt;0.001). Compared with CKD stage 1-2 patients, uAGT levels in patients with stage CKD 3 or above were significantly increased, and the difference was statistically significant (P&lt;0.001) (Table 1). The result of multivariate linear regression analysis showed that uAGT levels in CKD patients were positively correlated with 24h urine protein (beta = 0.193, P = 0.012) and negatively correlated with eGFR (beta = -0.489, P&lt;0.001) (Table 2). We also demonstrated that uAGT was positively correlated with the ratio of glomerular sclerosis(P = 0.003) (Table 3). Our results showed that the area under the curve (AUC)of uAGT for the diagnosis of renal function with CKD stage 3 or above was 0.789 (Figure 1) with the cut-off value was1959.9pg/ml. The sensitivity and specificity were 51.2% and 97.3% respectively, Furthermore, the positive predictive value (PPV) was 88.0% and negative predictive value (NPV) was 82.95%.The AUC of uAGT for the diagnosis of renal pathological glomerular sclerosis ratio&gt;50% was 0.677 (Figure 2).The cut-off value of uAGT was 2131.8pg/ml.The sensitivity and specificity were 50% and 89.5% respectively. Meanwhile, the PPV was 41.67% and the NPV was 92.25%. Conclusion uAGT was significantly increased in CKD patients, which is closely related with the urinary protein, eGFR, and renal pathology.The specific cut-off value of uAGT can be used as a predictive indicator of advanced CKD stage and severe glomerular sclerosis.

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