Quantifying appendicular muscle mass in geriatric inpatients: Performance of different single frequency BIA equations in comparison to dual X-ray absorptiometry

Sarcopenic obesity: a review

The global increase in life expectancy has led to a concomitant rise in diagnoses of sarcopenia. At the same time, the epidemic levels of obesity have given rise to the emergence of a complex condition known as sarcopenic obesity. Characterized by the simultaneous presence of loss of muscle mass and strength along with obesity or excess body fat, sarcopenic obesity represents a concerning health condition. Contrary to prevailing assumptions, sarcopenic obesity is not exclusive to older adults, as it may also manifest in individuals with obesity and chronic diseases and in those who undergo rapid weight loss. This juxtaposition of fat accumulation and muscle depletion epitomizes a harmful combination, especially in healthy adults. A precise definition of sarcopenic obesity and an understanding of how different body composition components affect functional parameters, comorbidities, and mortality rates are crucial for grasping the full extent and significance of this condition. Despite its multifaceted nature, sarcopenic obesity is often undiagnosed and undertreated, posing a considerable challenge to healthcare systems worldwide. In this review, we explore the intricate interplay of factors contributing to the development and consequences of sarcopenic obesity and discuss newly proposed diagnostic guidelines aimed at improved screening. Enhancing awareness and understanding of sarcopenic obesity is imperative for addressing its growing prevalence and mitigating its adverse health effects.

Assessing skeletal muscle mass and lean body mass: an analysis of the agreement among dual X-ray absorptiometry, anthropometry, and bioelectrical impedance

Introduction

Methods of body composition estimation such as dual-energy X-ray absorptiometry (DXA), anthropometry, and bioimpedance (BIA) are used for the estimation of skeletal muscle mass (SMM) and lean body mass (LBM). No previous studies have examined whether these methods generate comparable results, or whether they are valid by using DXA as the reference. The aims of the present investigation were: (a) to assess the differences between DXA, anthropometry, and BIA in the estimation of SMM and LBM, taking into consideration the impact of sex and hydration status; and (b) to examine the agreement of anthropometry and BIA as compared to DXA for the estimation of SMM and LBM.

Methods

A descriptive cross-sectional design was followed with 262 healthy young adults (159 males and 103 females). LBM and SMM were assessed by anthropometry with the formulas from Lee et al. and Kulkarni et al. for LBM; and Kerr (opt a), Kerr (opt b), Lee et al., Poortmans, Matiegka, Martin et al., Drinkwater and Ross, and Heymsfield et al. for SMM; by BIA with the formula reported by the TANITA MC-780-MA software for LBM and SMM; and DXA with the formula reported by the Hologic Horizon software for LBM, and the conversion by Kim et al. for SMM.

Results

Significant differences were found for both SMM and LBM in kg, and percentages between most methods and formulas for the overall sample (p < 0.001-0.003) and divided by sex (p < 0.001-0.035). Hydration status did not have a significant effect on the differences between methods and formulas (p = 0.058-0.870). Lin's coefficient revealed limited agreement among the majority of formulas and methods (CCC = 0.007-0.880). The Bland-Altman analysis showed significant differences in most methods and formulas, both in the overall sample and divided by sex, when using SMM and LBM with DXA as the reference (p < 0.001-0.030).

Conclusion

There is a lack of agreement between methods and formulas for assessing SMM and LBM. Sex was found to be a significant factor in this analysis. Furthermore, significant differences were observed between most formulas and methods as compared to DXA, except for the equations to estimate SMM with anthropometry by Poortmans.

Incident sarcopenia in hospitalized older people: A systematic review

Hospitalization has been associated with the development of sarcopenia. This study aimed to examine the new incidences of hospital sarcopenia, associated risk factors and health outcomes, as defined by internationally recognized diagnostic criteria in hospitalized older people. Pre-defined search terms were run through five databases. Six studies that assessed sarcopenia on two separate time points during hospitalization on older inpatients were included. Prevalence of sarcopenia varied from 14.1% to 55% depending on diagnostic criteria and cut-off points used. New sarcopenia occurred between 12% to 38.7% patients following hospitalization. Risk factors were older age, longer duration of bed rest, lower baseline body mass index, cognitive impairment and activities of daily living disability. None of the studies reported health outcomes associated with newly developed sarcopenia in hospital.

External validation of BIA equations to estimate appendicular skeletal muscle mass in older adults: Importance of the bias analysis and derivation of correction factors to achieve agreement

There are several equations based on bioelectrical impedance analysis (BIA) to estimate with high precision appendicular skeletal muscle mass (ASM). However, most of the external validation studies have reported that these equations are inaccurate or biased when applied to different populations. Furthermore, none of the published studies has derived correction factors (CFs) in samples of community-dwelling older adults, and none of the published studies have assessed the influence of the dual-energy X-ray absorptiometry (DXA) model on the validation process. This study assessed the agreement between six BIA equations and DXA to estimate ASM in non-Caucasian older adults considering the DXA model and proposed a CF for three of them. This analysis included 547 non-institutionalized subjects over 60 years old from the northwest of Mexico who were physically independent and without cognitive impairment: 192 subjects were measured using DXA Hologic, while 355 were measured by DXA Lunar. The agreement between each of the equations and DXA was tested considering the DXA model used as a reference method for the design of each equation, using the Bland and Altman procedure, a paired t test, and simple linear regression as objective tests. This process was supported by the differences reported in the literature and confirmed in a subsample of 70 subjects measured with both models. Only six published BIA equations were included. The results showed that four equations overestimated ASM_DXA, and two underestimated it (p < 0.001, 95% CI for Kim's equation:−5.86-−5.45, Toselli's:−0.51-−0.15, Kyle's: 1.43–1.84, Rangel-Peniche's: 0.32–0.74, Sergi's: 0.83–1.23, and Yoshida's: 4.16–4.63 kg). However, Toselli's, Kyle's and Rangel-Peniche's equations were the only ones that complied with having a homogeneous bias. This finding allowed the derivation of CFs, which consisted of subtracting or adding the mean of the differences from the original equation. After estimating ASM applying the respective CF, the new ASM estimations showed no significant bias and its distribution remained homogeneously distributed. Therefore, agreement with DXA in the sample of non-Caucasian was achieved. Adding valid CFs to some BIA equations allowed to reduce the bias of some equations, making them valid to estimate the mean values of ASM at group level.

Potential Utility of Electrical Impedance Myography in Evaluating Age-Related Skeletal Muscle Function Deficits

Skeletal muscle function deficits associated with advancing age are due to several physiological and morphological changes including loss of muscle size and quality (conceptualized as a reduction in the intrinsic force-generating capacity of a muscle when adjusted for muscle size). Several factors can contribute to loss of muscle quality, including denervation, excitation-contraction uncoupling, increased fibrosis, and myosteatosis (excessive levels of inter- and intramuscular adipose tissue and intramyocellular lipids). These factors also adversely affect metabolic function. There is a major unmet need for tools to rapidly and easily assess muscle mass and quality in clinical settings with minimal patient and provider burden. Herein, we discuss the potential for electrical impedance myography (EIM) as a tool to evaluate muscle mass and quality in older adults. EIM applies weak, non-detectible (e.g., 400 μA), mutifrequency (e.g., 1 kHz–1 MHz) electrical currents to a muscle (or muscle group) through two excitation electrodes, and resulting voltages are measured via two sense electrodes. Measurements are fast (~5 s/muscle), simple to perform, and unaffected by factors such as hydration that may affect other simple measures of muscle status. After nearly 2 decades of study, EIM has been shown to reflect muscle health status, including the presence of atrophy, fibrosis, and fatty infiltration, in a variety of conditions (e.g., developmental growth and maturation, conditioning/deconditioning, and obesity) and neuromuscular diseases states [e.g., amyotrophic lateral sclerosis (ALS) and muscular dystrophies]. In this article, we describe prior work and current evidence of EIM’s potential utility as a measure of muscle health in aging and geriatric medicine.

Sarcopenia in hospitalized geriatric patients: insights into prevalence and associated parameters using new EWGSOP2 guidelines

Background

Data on prevalence of sarcopenia and its associated parameters in hospitalized geriatric patients are heterogeneous due to various definitions of the disease. The aim of this study was to determine the prevalence of sarcopenia using latest recommendations of the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), and to investigate associated parameters in patients admitted to acute geriatrics and geriatric rehabilitation.

Methods

In this cross-sectional single-centre study including 305 hospitalized geriatric patients, handgrip strength (pneumatic hand dynamometer) and muscle quantity (body impedance analysis) were assessed. Probable sarcopenia was defined by low handgrip strength, and the diagnosis was confirmed when both handgrip strength and muscle quantity were below cut-off points. Furthermore, parameters of the geriatric baseline examination were analyzed for association with probable and confirmed sarcopenia using logistic regression models.

Results

Median age of the study population was 84.0 years, and 65.6% were female. The prevalence of probable sarcopenia was 24.6% (CI 19.8–29.4%), and the prevalence of confirmed sarcopenia was 22.6% (CI 17.9–27.3%). Low calf circumference, low body mass index, cognitive impairment and an increased risk of malnutrition were found to be associated with confirmed sarcopenia. In contrast, only cognitive impairment was positively associated with probable sarcopenia.

Conclusions

Sarcopenia is highly prevalent in geriatric inpatients, and multiple parameters were found to be associated with the disease. To reduce negative clinical outcomes, our findings support the need for routinely performed admission examinations for prompt diagnosis of sarcopenia, and a timely start of treatment in hospitalized geriatric patients.

Prediction Equations of the Multifrequency Standing and Supine Bioimpedance for Appendicular Skeletal Muscle Mass in Korean Older People

Bioimpedance analysis (BIA) has been demanded for the assessment of appendicular skeletal muscle mass (ASM) in clinical and epidemiological settings. This study aimed to validate BIA equations for predicting ASM in the standing and supine positions; externally to cross-validate the new and published and built-in BIA equations for group and individual predictive accuracy; and to assess the overall agreement between the measured and predicted ASM index as sarcopenia diagnosis. In total, 199 healthy older adults completed the measurements of multifrequency BIA (InBody770 and InBodyS10) and dual-energy X-ray absorptiometry (DXA). Multiple regression analysis was used to validate the new multifrequency bioelectrical impedance analysis (MF-BIA) prediction equations. Each MF-BIA equation in the standing and supine position developed in the entire group included height²/resistance, sex, and reactance as predictors (R² = 92.7% and 92.8%, SEE = 1.02 kg and 1.01 kg ASM for the standing and supine MF-BIA). The new MF-BIA equations had a specificity positive predictive value and negative predictive value of 85% or more except for a sensitivity of about 60.0%. The new standing and supine MF-BIA prediction equation are useful for epidemiological and field settings as well as a clinical diagnosis of sarcopenia. Future research is needed to improve the sensitivity of diagnosis of sarcopenia using MF-BIA.

Think Globally, Act Locally: The Importance of Population-Specific Bioelectrical Impedance Analysis Prediction Equations for Muscle Mass Assessment

BACKGROUND

Bioelectrical impedance analysis (BIA) is a convenient muscle assessment method, but its accuracy highly depends on population-specific aspects of the adopted equation. We aimed to develop appendicular lean mass (ALM) prediction models for older South Americans and to compare their performances to those of reference equations in the same sample.

METHODS

Cross-sectional evaluation of 192 community-dwelling Brazilian subjects ≥60 years old from the COMO VAI?

STUDY

Using measurements from single-frequency and multifrequency devices (BIASF and BIAMF, respectively), new ALM prediction equations were developed (reference method: dual-energy x-ray absorptiometry [DXA]). Validity was assessed by bootstrapping. Four previously established equations were also tested, and the performances were compared using Bland-Altman analysis.

RESULTS

Stepwise variable selection produced the following equations: ALM_SF-BIA = (2.08 × sex) + (0.04 × weight) + (0.24 × RI₅₀ ) + (0.07 × Xc₅₀ ) - 0.16; ALM_MF-BIA = (1.85 × sex) + (0.03 × weight) + (0.31 × RI₅₀ ) + (0.04 × Xc₅₀ ) + (0.01 × Z₅ ) - 8.16, where ALM is estimated in kg; female sex = 0 and male sex = 1; weight is measured in kg; RI₅₀ is the resistance index at 50 kHz measured in cm² /Ω); Xc₅₀ is the reactance at 50 kHz measured in Ω; and Z₅ is impedance at 5 kHz measured in Ω. The equations explained, respectively, 89% and 90% of the variability of ALM_DXA in our sample, and their estimates were not significantly different from DXA measurements. Bland-Altman analysis revealed accurate and unbiased performances for both models, with similar limits of agreement (BIA_SF : ±2.58 kg; BIA_MF : ±2.48 kg), and their validity was considered adequate by the bootstrap method. The reference equations, however, systematically overestimated ALM in our sample.

CONCLUSION

The proposed equations might represent practical options to estimate ALM in older noninstitutionalized South Americans. Further external validation, though, is required to verify the reproducibility of our findings.

Developing a screening tool for sarcopenia in hospitalized geriatric patients: Estimation of appendicular skeletal muscle mass using bioelectrical impedance

BACKGROUND & AIMS

Sarcopenia is now a billable ICD-10 geriatric condition characterized by low appendicular skeletal muscle mass (ASMM) and low function. There is an increasing need for portable, provider-friendly, cost-effective methods for estimating ASMM. The overall goal of this project was to create and validate a regression model for obtaining ASMM from Bioelectrical Impedance Analysis (BIA) measurements using Dual-energy X-ray Absorptiometry (DXA) as the reference.

METHODS

Geriatric patients (≥65 years of age) were enrolled during an acute hospitalization. Body composition measurements were obtained through DXA and BIA devices. The ASMM prediction model was derived using stepwise multiple regression modeling. The model was 10 fold validated and tested as a screening tool (sensitivity, specificity, positive and negative predictive values) using the Foundation for the NIH Sarcopenia Project (FNIH) definition.

RESULTS

The following variables were selected by stepwise regression modeling: sex, body mass index, max grip strength, and fat mass derived by BIA. The model was internally validated with 10 fold cross validation. Using the FNIH definition, the model was found to have a sensitivity of 80%, a specificity of 91%, a positive predictive value of 73% and a negative predictive value of 93%.

CONCLUSIONS

We have developed a screening tool that can be easily used in geriatric patients to screen for sarcopenia. Once validated with a larger sample, the developed prediction model can be used to estimate ASMM using provider-friendly measurements and can be easily implemented as a sensitive screening tool for identifying patients at risk for sarcopenia. Those identified at risk would undergo further functional testing for diagnosis and treatment of sarcopenia.

Consequences of applying the new EWGSOP2 guideline instead of the former EWGSOP guideline for sarcopenia case finding in older patients

INTRODUCTION

we examined the consequences of applying the new EWGSOP2 algorithm for sarcopenia screening instead of the former EWGSOP algorithm (EWGSOP1) in geriatric inpatients.

METHODS

the dataset of our formerly published Sarcopenia in Geriatric Elderly (SAGE) study includes 144 geriatric inpatients (86 women, 58 men, mean age 80.7±5.6 years) with measurements of gait speed, handgrip strength and appendicular muscle mass by dual x-ray absorptiometry (DXA). We analysed the agreement between EWGSOP and EWGSOP2 algorithms in identifying patients as sarcopenic/non-sarcopenic. Differences in the distribution sarcopenic vs. non-sarcopenic were assessed by Chi²-test.

RESULTS

sarcopenia prevalence according to EWGSOP1 (41 (27.7%)) was significantly higher than with EWGSOP2 (26(18.1%), p<0.05). The sex-specific sarcopenia prevalence was 22.1% (EWGSOP1) and 17.4% (EWGSOP2), respectively, for women (difference not significant) and 37.9% vs. 19.4% for men (p<0.05%). The overall agreement in classifying subjects as sarcopenic/non-sarcopenic was 81.25% (81.4% for women, 81.0% for men). However, among the 41 sarcopenia cases identified by EWGSOP1, only 20 (48.8%) were diagnosed with sarcopenia by EWGSOP2 (9/19 w (47.4%), 11/22 m (50.0%)). Ten of 19 women (52.6%) and 11 of 22 men (50.0%) diagnosed with sarcopenia by EWGSOP1 were missed by EWGSOP2, while 6 of 15 women (40.0%) and 0 of 11 men (0.0%) were newly diagnosed.

DISCUSSION

there is a substantial mismatch in sarcopenia case finding according to EWGSOP1 and EWGSOP2. The overall prevalence and the number of men diagnosed with sarcopenia are significantly lower in EWGSOP2. While the absolute number of women identified as sarcopenic remains relatively constant, the overlap of individual cases between the two definitions is low.

Bridging the gap between the laboratory and the clinic for patients with sarcopenia

Sarcopenia-the age-related loss of skeletal muscle mass and strength-is a major public health issue. Sarcopenia is associated with an increased risk of falls, disability, dependency, institutionalization, hospital stay and early death. Finding interventions to stabilize, reverse or prevent sarcopenia is therefore a key goal for clinical ageing research. If patients are to eventually benefit from discovery science on ageing skeletal muscle, we need to build a translational pipeline that facilitates progress from laboratory science and epidemiology, through feasibility testing to early-phase, and eventually late-phase clinical trials. A number of barriers need to be overcome to make this pipeline work-in particular challenges around identifying people with sarcopenia in routine clinical practice, ensuring that we study patients with clearly defined sarcopenia rather than related conditions such as functional impairment, developing capacity to run trials for older people, and selecting trial outcomes of relevance to older people with multimorbidity. A further key point is that interventions should ideally have pleiotropic actions-i.e. beneficial actions across multiple organ systems, rather than treating sarcopenia alone. Such pleiotropic interventions may be the only way to avoid the perils of polypharmacy and drug interactions that bedevil care for many older people. Maximising the potential for scientific discoveries in the biology of ageing muscle to improve health requires that discovery scientists, translational clinical scientists and clinicians come together to exchange findings and shape each others ideas within a shared culture.