Bioelectrical impedance analysis in the assessment of sarcopenia

Variations in bioelectrical impedance devices impact raw measures comparisons and subsequent prediction of body composition using recommended estimation equations

BACKGROUND & AIMS

Bioelectrical impedance analysis (BIA) for body composition estimation is increasingly used in clinical and field settings to guide nutrition and training programs. Due to variations among BIA devices and the proprietary prediction equations used, studies have recommended the use of raw measures of resistance (R) and reactance (Xc) within population-specific equations to predict body composition.

OBJECTIVE

We compared raw measures from three BIA devices to assess inter-device variation and the impact of differences on body composition estimations.

METHODS

Raw R, Xc, impedance (Z) parameters were measured on a calibrated phantom and athletes using tetrapolar supine (BIASUP4), octapolar supine (BIASUP8), and octapolar standing (BIASTA8) devices. Measures of R and Xc were compared across devices and graphed using BIA vector analysis (BIVA) and raw parameters were entered into recommended athlete-specific equations for predicting fat-free mass (FFM) and appendicular lean soft tissue (ALST). Whole-body FFM and regional ALST were compared across devices and to a criterion five-compartment (5C) model and dual energy X-ray absorptiometry for ALST.

RESULTS

Data from 73 (23.2 ± 4.8 y) athletes were included in the analyses. Technical differences were observed between Z (range 12.2-50.1Ω) measures on the calibrated phantom. Differences in whole-body impedance were apparent due to posture (technological) and electrode placement (biological) factors. This resulted in raw measures for all three devices showing greater dehydration on BIVA compared to published norms for athletes using a separate BIA device. Compared to the 5C FFM, significant differences (p < 0.05) were observed on all three equations for BIASUP8 and BIASTA8, with constant error (CE) from -2.7 to -4.6 kg; no difference was observed for BIASUP4 or when device-specific algorithms were used. Published equations resulted in differences as large as 8.8 kg FFM among BIA devices. For ALST, even after a correction in the error of the published empirical equation, all three devices showed significant (p < 0.01) CE from -1.6 to -2.9 kg.

CONCLUSIONS

Raw bioimpedance measurements differ among devices due to technical, technological, and biological factors, limiting interchangeability of data across BIA systems. Professionals should be aware of these factors when purchasing systems, comparing data to published reference ranges, or when applying published empirical body composition prediction equations.

Validity of equations for estimating fat-free mass in people living with the human immunodeficiency virus

BACKGROUND & AIMS

Equations estimating fat-free mass (FFM) in people living with the human immunodeficiency virus (HIV) show differences in the validation process. The current study aimed to verify the validity of FFM estimation equations derived from bioelectrical impedance (BIA) in people living with HIV aged 40 years and older.

METHODS

A cross-sectional study was conducted with 68 participants evaluated using dual-energy X-ray absorptiometry (DXA) and by two BIA devices (Analyzer and Biodynamics). The study aimed to determine the validity of six different FFM equations from four different studies by Lukaski and Bolonchuk (1987), Kotler et al. (1996), Beraldo et al. (2015) and Hegelund et al. (2017). Comparisons were made using the t-test or Wilcoxon test. To verify the validity between DXA and two BIA devices, the following statistical analyses were performed: Lin's concordance correlation coefficient, intraclass correlation coefficient, coefficient of determination, standard error of the estimate, differences in the limits of agreement by Bland and Altman analysis, correlation between the average and the differences of the methods by Pearson or Spearman correlation.

RESULTS

Only equation 2 of Kotler et al. (1996) for males by Biodynamics BIA showed no difference in FFM. The Lin's concordance correlation coefficient was excellent (0.96), irrespective of sex, for Equation 2 of Kotler et al. (1996) by BIA Analyzer. All equations were reproducible (>0.85). The coefficient of determination ranged from 68% to 92%, and the standard error of the estimates ranged from 1.8 kg to 5.0 kg. The differences between the limits of agreement ranged from 7.2 kg to 14.9 kg, and the correlations between the average and the differences of the methods showed differences in FFM for three equations (p < 0.01).

CONCLUSION

The choice of equations must consider the equipment used and the sex of the sample investigated. Only Equation 2 of Kotler et al. (1996) was considered valid, irrespective of sex, to estimate the FFM by BIA Analyzer.

Appendicular Skeletal Muscle Mass in Older Adults Can Be Estimated With a Simple Equation Using a Few Zero-Cost Variables

BACKGROUND AND PURPOSE

Assessing appendicular skeletal muscle (ASM) mass is crucial for the diagnosis of numerous pathologies related to the decline of muscle mass in old age, such as sarcopenia, malnutrition, or cachexia. The dual-energy X-ray absorptiometer (DEXA) radiological technique, which is the gold standard for its assessment, is particularly costly and not routinely used in clinical practice. The aim of this study was to derive computationally simple equations capable of estimating the DEXA-measured ASM at zero cost in older adult populations.

METHODS

We used the cross-sectional data collected by the National Health and Nutrition Examination Survey (NHANES) over 7 years (1999-2006). The study sample included 16,477 individuals aged 18 years and over, of which 4401 were over 60 years old. We considered 38 nonlaboratory variables. For the derivation of the equations, we employed the Brain Project, an innovative artificial intelligence tool that combines genetic programming and neural networks. The approach searches simultaneously for the mathematical expression and the variables to use in the equation. The derived equations are useful to estimate the DEXA-measured ASM.

RESULTS AND DISCUSSION

A simple equation that includes the body weight of the patient as the sole variable can estimate the outcome of DEXA with an accuracy equivalent to previously published equations. When used to identify individuals over 60 years old with muscle mass loss, it achieved an area under the curve (AUC) value of 0.85 for both males and females. The inclusion of sex and anthropometric data (thigh and arm circumference) improved the accuracy for male individuals (AUC 0.89). The model is also suitable to be applied to the general adult population of 18 years of age or older. Using more than 3 variables does not lead to better accuracy.

CONCLUSIONS

The newly proposed equations have better diagnostic accuracy than previous equations for the estimation of DEXA-measured ASM. They are readily applicable in clinical practice for the screening of muscle mass loss in the over 60-year-old population with nearly zero-cost variables. The most complex model proposed in this study requires only the inspection of a simple diagnostic chart to estimate the status of muscle mass loss.

Comparison of different MRI-based unsupervised segmentation algorithms in predicting sarcopenia

PURPOSE

To compare the performance of MRI-based Gaussian mixture model (GMM), K-means clustering, and Otsu unsupervised algorithms in predicting sarcopenia and to develop a combined model by integrating clinical indicators.

METHODS

Retrospective analysis was conducted on clinical and lumbar MRI data from 118 patients diagnosed with sarcopenia and 222 patients without the sarcopenia. All patients were randomly divided into training and validation groups in a 7:3 ratio. Regions of interest (ROI), specifically the paravertebral muscles at the L3/4 intervertebral disc level, were delineated on axial T2-weighted images (T2WI). The Gaussian mixture model (GMM), K-means clustering, and Otsu's thresholding algorithms were employed to automatically segment muscle and adipose tissues at both the cohort and case levels. Subsequently, the mean signal intensity, volumes, and percentages of these tissues were calculated and compared. Logistic regression analyses were conducted to construct models and identify independent predictors of sarcopenia. An combined model was developed by combining the optimal magnetic resonance imaging (MRI) model and clinical predictors. The performance of the constructed model was assessed using receiver operating characteristic (ROC) curve analysis.

RESULTS

Age, BMI, and serum albumin were identified as independent clinical predictors of sarcopenia. The cohort-level GMM demonstrated the best predictive performance both in the training group (AUC=0.840) and validation group (AUC=0.800), while the predictive performance of the other models was lower than that of the clinical model both in the training and validation groups. After combining the cohort-level GMM with the independent clinical predictors, the AUC of the training and validation groups increased to 0.871 and 0.867, respectively.

CONCLUSION

The cohort-level GMM shows potential in predicting sarcopenia, and the incorporation of independent clinical predictors further increased the performance.

Preoperative body composition measured by bioelectrical impedance analysis can predict pancreatic fistula after pancreatic surgery

BACKGROUND

Postoperative pancreatic fistula (POPF) remains one of the most severe complications after pancreatic surgery. The methods for predicting pancreatic fistula are limited. We aimed to investigate the predictive value of body composition parameters measured by preoperative bioelectrical impedance analysis (BIA) on the development of POPF.

METHODS

A total of 168 consecutive patients undergoing pancreatic surgery from March 2022 to December 2022 at our institution were included in the study and randomly assigned at a 3:2 ratio to the training group and the validation group. All data, including previously reported risk factors for POPF and parameters measured by BIA, were collected. Risk factors were analyzed by univariable and multivariable logistic regression analysis. A prediction model was established to predict the development of POPF based on these parameters.

RESULTS

POPF occurred in 41 of 168 (24.4%) patients. In the training group of 101 enrolled patients, visceral fat area (VFA) (odds ratio [OR] = 1.077, P = 0.001) and fat mass index (FMI) (OR = 0.628, P = 0.027) were found to be independently associated with POPF according to multivariable analysis. A prediction model including VFA and FMI was established to predict the development of POPF with an area under the receiver operating characteristic curve (AUC) of 0.753. The efficacy of the prediction model was also confirmed in the internal validation group (AUC 0.785, 95% CI 0.659-0.911).

CONCLUSIONS

Preoperative assessment of body fat distribution by BIA can predict the risk of POPF after pancreatic surgery.

Body composition and associated factors among 5-7-year-old children with moderate acute malnutrition in Jimma town in southwest Ethiopia: A comparative cross-sectional study

Acute malnutrition affects not only the growth and development but also the body composition of children. However, its specific effects have not yet been characterized. This study aims to compare the body composition of 5-7-year-old children with moderate acute malnutrition (MAM) to that of their well-nourished (WN) peers and identify associated factors. A school-based comparative cross-sectional study was conducted from June to July 2022 in Jimma town, southwest Ethiopia. The study participants were selected from eight kindergartens and eight primary schools using a simple random sampling technique based on the proportional allocation of the sample to the size of the population in the respective school. Descriptive statistics and multivariable linear regression analyses were used to assess the mean differences and associations between variables and isolate independent predictors of body composition, respectively. The statistical significance was determined using ß-coefficients with 95% confidence intervals and a p value of ≤ 0.05. Data were captured from 388 (194 MAM and 194 WN) children with a response rate of 97.9%. The mean fat-free mass of WN children was significantly higher compared with those with MAM (p < 0.001). The mean (SD) of fat mass of MAM children was 4.23 ± 0.72 kg, 4.36 ± 0.88 kg and 4.08 ± 0.89 kg for 5, 6 and 7-year-olds, respectively. For WN children, the mean (SD) of fat mass was 4.92 ± 0.88 kg for 5 years old, 5.64 ± 1.01 kg for 6 years old and 5.75 ± 1.26 kg for 7 years old (p < 0.001). On the multivariable linear regression analysis after controlling for background variables, WN children exhibited 1.51 times higher fat-free mass compared with MAM children (β = 1.51, p = 0.003). A unit increase in age of the study participants was associated with a 1.37 increment in fat-free mass (β = 1.37, p  < 0.001). WN children had 1.07 times higher fat mass compared with children with MAM (β = 1.07, p < 0.001). A unit increase in the age of the child resulted in 0.15 times increment in fat mass (β = 0.15, p = 0.020), and being female was associated with a 0.37 increase in fat mass (β = 0.37, p < 0.001). The results showed that the mean fat mass and fat-free mass were significantly lower among moderately acute malnourished children than in WN children showing the loss of both body compartments due to malnutrition. The body mass index for age, age of the child and sex of the child were significantly linked to both fat-free mass and fat mass.

Frontiers in sarcopenia: Advancements in diagnostics, molecular mechanisms, and therapeutic strategies

The onset of sarcopenia is intimately linked with aging, posing significant implications not only for individual patient quality of life but also for the broader societal healthcare framework. Early and accurate identification of sarcopenia and a comprehensive understanding of its mechanistic underpinnings and therapeutic targets paramount to addressing this condition effectively. This review endeavors to present a cohesive overview of recent advancements in sarcopenia research and diagnosis. We initially delve into the contemporary diagnostic criteria, specifically referencing the European Working Group on Sarcopenia in Older People (EWGSOP) 2 and Asian Working Group on Sarcopenia (AWGS) 2019 benchmarks. Additionally, we elucidate comprehensive assessment techniques for muscle strength, quantity, and physical performance, highlighting tools such as grip strength, chair stand test, dual-energy X-ray Absorptiometry (DEXA), bioelectrical impedance analysis (BIA), gait speed, and short physical performance battery (SPPB), while also discussing their inherent advantages and limitations. Such diagnostic advancements pave the way for early identification and unequivocal diagnosis of sarcopenia. Proceeding further, we provide a deep-dive into sarcopenia's pathogenesis, offering a thorough examination of associated signaling pathways like the Myostatin, AMP-activated protein kinase (AMPK), insulin/IGF-1 Signaling (IIS), and the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways. Each pathway's role in sarcopenia mediation is detailed, underscoring potential therapeutic target avenues. From a mechanistic perspective, the review also underscores the pivotal role of mitochondrial dysfunction in sarcopenia, emphasizing elements such as mitochondrial oxidative overload, mitochondrial biogenesis, and mitophagy, and highlighting their therapeutic significance. At last, we capture recent strides made in sarcopenia treatment, ranging from nutritional and exercise interventions to potential pharmacological and supplementation strategies. In sum, this review meticulously synthesizes the latest scientific developments in sarcopenia, aiming to enhance diagnostic precision in clinical practice and provide comprehensive insights into refined mechanistic targets and innovative therapeutic interventions, ultimately contributing to optimized patient care and advancements in the field.

Is phase angle associated with visceral adiposity and cardiometabolic risk in cardiology outpatients?

BACKGROUND/OBJECTIVES

Phase angle (PhA) serves as a prognostic marker in various clinical scenarios, reflecting oxidative stress and cellular damage. Despite its clinical relevance, its connection with adiposity and cardiovascular risk markers remains underexplored. Hence, our study sought to investigate the relationship between PhA and metabolic, adiposity, and cardiovascular risk parameters among outpatients with cardiology diagnosis.

SUBJECTS/METHODS

Adults aged between 26 and 59 years, under the care of a cardiology unit, were included. Ultrasound imaging was used to assess visceral adipose tissue (VAT). Single-frequency bioelectrical impedance analysis (BIA) [50 kHz] was employed to calculate PhA, from BIA's resistance and reactance measurements. Muscle strength, body mass index, waist circumference, and waist-to-height ratio were also evaluated. Framingham's risk score was calculated to estimate the cardiovascular risk events. Metabolic blood samples' results were obtained from medical records.

RESULTS

One hundred and five participants were included in our study. Low PhA was observed in 29.5% of our sample. Higher PhA values were independently and inversely associated with both higher VAT and cardiovascular risk (adjusted OR: 0.79 [95% CI 0.69;0.91], OR: 0.74 [95% CI 0.60;0.89], respectively). Lower PhA values (≤5.59) were goodly associated with high VAT (AUC: 0.82 p < 0.001). Lower PhA values (≤5.06) were fairly associated with higher cardiovascular risk (AUC: 0.70 p = 0.003).

CONCLUSION

Our study provides evidence that PhA is independently and inversely associated with elevated VAT and cardiovascular risk. These findings underscore the potential of PhA as a valuable complementary marker in assessing cardiometabolic health.

Machine-learning classifier models for predicting sarcopenia in the elderly based on physical factors

AIM

As the size of the elderly population gradually increases, musculoskeletal disorders, such as sarcopenia, are increasing. Diagnostic techniques such as X-rays, computed tomography, and magnetic resonance imaging are used to predict and diagnose sarcopenia, and methods using machine learning are gradually increasing. This study aimed to create a model that can predict sarcopenia using physical characteristics and activity-related variables without medical diagnostic equipment, such as imaging equipment, for the elderly aged 60 years or older.

METHODS

A sarcopenia prediction model was constructed using public data obtained from the Korea National Health and Nutrition Examination Survey. Models were built using Logistic Regression, Support Vector Machine (SVM), XGBoost, LightGBM, RandomForest, and Multi-layer Perceptron Neural Network (MLP) algorithms, and the feature importance of the models trained with the algorithms, except for SVM and MLP, was analyzed.

RESULTS

The sarcopenia prediction model built with the LightGBM algorithm achieved the highest test accuracy, of 0.848. In constructing the LightGBM model, physical characteristic variables such as body mass index, weight, and waist circumference showed high importance, and activity-related variables were also used in constructing the model.

CONCLUSIONS

The sarcopenia prediction model, which consisted of only physical characteristics and activity-related factors, showed excellent performance. This model has the potential to assist in the early detection of sarcopenia in the elderly, especially in communities with limited access to medical resources or facilities. Geriatr Gerontol Int 2024; 24: 595-602.

Standardized phase angle: relationship with functionality, muscle mass and postoperative outcomes in surgical cancer patients

To evaluate the association of standardized phase angle (SPA) with nutritional status, functional parameters, and postoperative outcomes in surgical cancer patients. This prospective study includes 59 cancer patients from Pelotas (Brazil) admitted for elective cancer surgery. We obtained the phase angle through Bioelectrical Impedance Analysis (BIA) and standardized it according to the population's reference values. We estimated the muscle mass using BIA for later calculation of the Skeletal Muscle Index (SMI) and performed handgrip strength (HGS) and gait speed (GS) tests. We used the Patient-Generated Subjective Global Assessment (PG-SGA) to assess the nutritional status. Postoperative complications and duration of hospital stay were evaluated as the outcomes. The prevalence of malnutrition in the sample was 28.8%, according to ASG-PPP. SPA was statistically lower in patients with malnutrition, with lower HGS and reduced GS. For postoperative outcomes, patients with severe complications and those with prolonged hospitalization also had lower SPA values. The greater the number of functional alterations in patients, the lower the SPA value, mainly when associated with reduced muscle mass assessed by BIA, suggesting that muscle mass reduction plays an important role in the association between functional alterations and phase angle in patients with cancer. According to the parameters used in this study, low SPA value was associated with impaired nutritional and functional status and negative outcomes in the analyzed sample.

Comparison of bioelectrical impedance analysis and computed tomography for the assessment of muscle mass in patients with gastric cancer

BACKGROUND

Low muscle mass was significantly correlated with poor clinical outcomes in cancer patients. This study aimed to compare the differences between bioelectrical impedance analysis (BIA) and computed tomography (CT) in measuring skeletal muscle mass and detecting low muscle mass in patients with gastric cancer (GC).

METHOD

This cross-sectional study included a total of 302 consecutive patients diagnosed with GC at our institution from October 2021 to March 2023. CT images were analyzed at the L3 level to obtain the cross-sectional area of skeletal muscle, which was subsequently used for calculating whole-body skeletal muscle mass via the Shen equation and skeletal muscle tissue density. BIA was utilized to measure skeletal muscle mass using the manufacturer's proprietary algorithms. Skeletal muscle mass (kg) was divided by height squared (m2) to obtain skeletal muscle index (SMI, kg/m2). Pearson's correlation coefficient was performed to assess the correlation between SMI measured by BIA and CT. The agreement between the two methods was assessed using Bland-Altman analyses. The clinically acceptable agreement was defined as the 95% limits of agreement (LOA) for the percentage bias falling within ± 10%. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of BIA in identifying low muscle mass.

RESULTS

A total of 59 patients (19.5%) were identified as having low muscle mass based on CT analysis, whereas only 19 patients (6.3%) met the criteria for low muscle mass according to BIA analysis. BIA-measured SMI showed a strong positive correlation with CT-measured SMI in all patients (r = 0.715, P < 0.001). With Bland-Altman analysis, there was a significant mean bias of 1.18 ± 0.96 kg/m2 (95% CI 1.07-1.29, P < 0.001) between SMI measured by BIA and CT. The 95% LOA for the percentage bias ranged from -7.98 to 33.92%, which exceeded the clinically acceptable range of ± 10%. A significant difference was observed in the mean bias of SMI measured by BIA and CT between patients with and without GLIM malnutrition (1.42 ± 0.91 kg/m2 versus 0.98 ± 0.96 kg/m2, P < 0.001). The cut-off values for BIA-measured SMI in identifying low muscle mass using CT as the reference were 10.11 kg/m2 for males and 8.71 kg/m2 for females (male: AUC = 0.840, 95% CI: 0.772-0.908; female: AUC = 0.721, 95% CI: 0.598-0.843).

CONCLUSIONS

Despite a significant correlation, the values of skeletal muscle mass obtained BIA and CT cannot be used interchangeably. The BIA method may overestimate skeletal muscle mass in GC patients compared to CT, especially among those with GLIM malnutrition, leading to an underestimation of low muscle mass prevalence.

Calculation of trunk muscle mass and trunk muscle quality indices for walking independence in asian patients with hip fractures

BACKGROUND & AIMS

This study aimed to investigate the association between trunk muscle mass and muscle quality, as evaluated by bioelectrical impedance analysis (BIA), and the ability to walk independently in patients with hip fractures. Cutoff values for quantitative and qualitative indicators of the trunk muscles were also calculated.

METHODS

This study included 181 patients with hip fractures who were admitted to a convalescent rehabilitation ward. Trunk muscle mass and phase angle of the participants were evaluated on admission. The phase angle in this study was defined as the trunk muscle quality index (TMQI). Patients were classified into the independent (functional independence measure [FIM]-walk score ≥6; n = 101) and non-independent (FIM-walk score ≤5; n = 80) walking groups according to the FIM mobility scores at discharge.

RESULTS

The independent group had a higher FIM gain than the non-independent group (37.0 ± 13.6 vs. 27.1 ± 13.5, p < 0.001). Logistic regression analysis showed that the trunk muscle mass index (TMI) and TMQI were associated with the ability to walk independently. Furthermore, cutoff values of TMI and TMQI for male and female to estimate the ability to walk independently were 6.5 kg/m2 and 5.7 kg/m2, and 4.5° and 3.4°, respectively.

CONCLUSION

TMI and TMQI are related to the ability to walk independently in patients with hip fractures. These results suggest the importance of improving trunk muscle mass and muscle quality during rehabilitation of patients with hip fractures.

Conflicting Associations among Bioelectrical Impedance and Cardiometabolic Health Parameters in Young White and Black Adults

PURPOSE

The purpose of this cross-sectional evaluation was to determine the associations between raw bioelectrical impedance and cardiometabolic health parameters in a sample of young non-Hispanic White and African American adults.

METHODS

A total of 96 (female: 52, male: 44) non-Hispanic White ( n = 45) and African American adults ( n = 51) between the ages of 19 and 37 yr (22.7 ± 3.83 yr) completed several fasted assessments including resting systolic blood pressure (rSBP), blood glucose (FBG), blood lipids, and bioelectrical impedance spectroscopy. Bioelectrical impedance spectroscopy-derived measurements included phase angle, bioimpedance index (BI), impedance ratio (IR), reactance index (XCi), fat-free mass (FFM), FFM index (FFMi), and absolute (a) and relative (%) total body water (TBW) and extracellular (ECF) and intracellular fluid (ICF). All bioelectric variables were collected at 50 kHz other than IR (250 kHz/5 kHz). Multiple regressions were conducted and adjusted for sex, age, and body mass index.

RESULTS

rSBP was positively, and HDL was inversely, associated with all bioelectrical impedance and absolute hydration variables (all P ≤ 0.050) other than XCi for rSBP and XCi and FFMi for HDL. rSBP ( P < 0.001) was inversely, and HDL ( P = 0.034) was positively, associated with IR. FBG was positively associated with BI, XCi, FFM, TBWa, and ECFa (all P < 0.050). Metabolic syndrome severity was positively associated with BI, FFM, TBWa, and ECFa for women (all P ≤ 0.050) and with ICFa for African American women ( P = 0.016).

CONCLUSIONS

Given the rapid increase in the prevalence of cardiometabolic health risks among young adults and the broad use of bioelectrical impedance in practice, the conflicting associations we observed in this age group suggest that bioelectrical impedance parameters should be used with caution in the context of cardiometabolic health risks and age.

One-Year Changes in Bioelectrical Impedance Data in Adolescent Athletes

Raw bioelectrical impedance (BI) data and vector analysis (BIVA) have been used to evaluate fat-free mass (FFM) cross-sectionally in adolescent athletes; however, there have been no longitudinal studies about it. This study aimed to assess the magnitude of changes in raw BI data (resistance [R], reactance [Xc], and phase angle [PhA]), BIVA, and FFM in adolescent athletes (n = 137, 40% female). BI data were collected using a single-frequency device at baseline and after one year of sports practice. Baseline chronological age categorized the participants (11, 12, or 13 years [y]). In females, Xc/H increased (13 to 14 y, p = 0.04) while R/H decreased in all age groups (p = 0.001). PhA (11 to 12 y, p = 0.048) and FFM (11 to 12 y and 12 to 13 y groups p = 0.001) increased and showed the lowest magnitude of changes in the 13 to 14 y group (p = 0.05). In males, Xc/H decreased (11 to 12 and 12 to 13 y groups, p = 0.001) with a higher magnitude of changes in the 13 to 14 y group (p = 0.004); R/H decreased (p = 0.001); FFM increased in all groups (p = 0.001); however, no magnitude of changes was observed. PhA increased in the 13 to 14 y group (p = 0.004). BIVA showed no differences among ellipse distances in females. In males, a high distance was observed in the 11 to 12 y group. "Time interval" influenced PhA and Xc/H in the female group and R/H and Xc/H in the male group. "Initial age" and "time interval" influenced the increase in PhA in the male group. Raw BI data and BIVA patterns can detect the magnitude of the changes in a sex-dependent manner.

Development of Continuous Assessment of Muscle Quality and Frailty in Older Patients Using Multiparametric Combinations of Ultrasound and Blood Biomarkers: Protocol for the ECOFRAIL Study

BACKGROUND

Frailty resulting from the loss of muscle quality can potentially be delayed through early detection and physical exercise interventions. There is a demand for cost-effective tools for the objective evaluation of muscle quality, in both cross-sectional and longitudinal assessments. Literature suggests that quantitative analysis of ultrasound data captures morphometric, compositional, and microstructural muscle properties, while biological assays derived from blood samples are associated with functional information.

OBJECTIVE

This study aims to assess multiparametric combinations of ultrasound and blood-based biomarkers to offer a cross-sectional evaluation of the patient frailty phenotype and to track changes in muscle quality associated with supervised exercise programs.

METHODS

This prospective observational multicenter study will include patients aged 70 years and older who are capable of providing informed consent. We aim to recruit 100 patients from hospital environments and 100 from primary care facilities. Each patient will undergo at least two examinations (baseline and follow-up), totaling a minimum of 400 examinations. In hospital environments, 50 patients will be measured before/after a 16-week individualized and supervised exercise program, while another 50 patients will be followed up after the same period without intervention. Primary care patients will undergo a 1-year follow-up evaluation. The primary objective is to compare cross-sectional evaluations of physical performance, functional capacity, body composition, and derived scales of sarcopenia and frailty with biomarker combinations obtained from muscle ultrasound and blood-based assays. We will analyze ultrasound raw data obtained with a point-of-care device, along with a set of biomarkers previously associated with frailty, using quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay. Additionally, we will examine the sensitivity of these biomarkers to detect short-term muscle quality changes and functional improvement after a supervised exercise intervention compared with usual care.

RESULTS

At the time of manuscript submission, the enrollment of volunteers is ongoing. Recruitment started on March 1, 2022, and ends on June 30, 2024.

CONCLUSIONS

The outlined study protocol will integrate portable technologies, using quantitative muscle ultrasound and blood biomarkers, to facilitate an objective cross-sectional assessment of muscle quality in both hospital and primary care settings. The primary objective is to generate data that can be used to explore associations between biomarker combinations and the cross-sectional clinical assessment of frailty and sarcopenia. Additionally, the study aims to investigate musculoskeletal changes following multicomponent physical exercise programs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05294757; https://clinicaltrials.gov/ct2/show/NCT05294757.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/50325.

Early detection and assessment of intensive care unit-acquired weakness: a comprehensive review

Intensive care unit-acquired weakness (ICU-AW) is a serious complication in critically ill patients. Therefore, timely and accurate diagnosis and monitoring of ICU-AW are crucial for effectively preventing its associated morbidity and mortality. This article provides a comprehensive review of ICU-AW, focusing on the different methods used for its diagnosis and monitoring. Additionally, it highlights the role of bedside ultrasound in muscle assessment and early detection of ICU-AW. Furthermore, the article explores potential strategies for preventing ICU-AW. Healthcare providers who manage critically ill patients utilize diagnostic approaches such as physical exams, imaging, and assessment tools to identify ICU-AW. However, each method has its own limitations. The diagnosis of ICU-AW needs improvement due to the lack of a consensus on the appropriate approach for its detection. Nevertheless, bedside ultrasound has proven to be the most reliable and cost-effective tool for muscle assessment in the ICU. Combining the Sequential Organ Failure Assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation (APACHE) II score assessment, and ultrasound can be a convenient approach for the early detection of ICU-AW. This approach can facilitate timely intervention and prevent catastrophic consequences. However, further studies are needed to strengthen the evidence.

Skeletal muscle gauge prediction by a machine learning model in patients with colorectal cancer

OBJECTIVES

Skeletal muscle gauge (SMG) was recently introduced as an imaging indicator of sarcopenia. Computed tomography is essential for measuring SMG; thus, the use of SMG is limited to patients who undergo computed tomography. We aimed to develop a machine learning algorithm using clinical and inflammatory markers to predict SMG in patients with colorectal cancer.

METHODS

The least absolute shrinkage and selection operator regression model was applied for variable selection and predictive signature building in the training set. The predictive accuracy of the least absolute shrinkage and selection operator model, defined as linear predictor (LP)-SMG, was compared using the area under the receiver operating characteristic curve and decision curve analysis in the test set.

RESULTS

A total of 1094 patients with colorectal cancer were enrolled and randomly categorized into training (n = 656) and test (n = 438) sets. Low SMG was identified in 142 (21.6%) and 90 (20.5%) patients in the training and test sets, respectively. According to multivariable analysis of the test sets, LP-SMG was identified as an independent predictor of low SMG (odds ratio = 1329.431; 95% CI, 271.684-7667.996; P < .001). Its predictive performance was similar in the training and test sets (area under the receiver operating characteristic curve = 0.846 versus 0.869; P = .427). In the test set, LP-SMG had better outcomes in predicting SMG than single clinical variables, such as sex, height, weight, and hemoglobin.

CONCLUSIONS

LP-SMG had superior performance than single variables in predicting low SMG. This machine learning model can be used as a screening tool to detect sarcopenic status without using computed tomography during the treatment period.

Response to Ustekinumab Therapy Is Associated with an Improvement of Nutritional Status in Patients with Crohn's Disease

The presence of sarcopenia has been associated with the worst outcome of Crohn's disease (CD). At present, no studies have evaluated the impact of ustekinumab (UST) in terms of its effects on body composition. The aim of this prospective study was to evaluate whether UST treatment could modify the parameters of body composition as assessed by bioelectrical impedance assay (BIA) in patients with CD. We prospectively enrolled consecutive patients with CD treated with UST, evaluating the therapeutic outcome at week 48 in terms of clinical remission and mucosal healing. BIA was performed at baseline and at week 48, assessing body cellular mass, total body water, phase angle, and body mass index. Out of 44 patients enrolled, 26 (59%) were in clinical remission and 22 (50%) achieved mucosal healing at the end of follow up. No significant differences were observed at baseline in all the BIA parameters between responders and non-responders. Phase angle increased over time in responders, while this was not observed in non-responders (test for the interaction between time and outcome, p-value = 0.009 and 0.007 for clinical remission and mucosal healing, respectively). The same differential increase was observed for body cellular mass (test for the interaction between time and outcome, p-value = 0.03 and 0.05 for clinical remission and mucosal healing, respectively). Total body water and BMI increased homogenously over time regardless of the outcomes (tests for the association with time, p-values of 0.01). To conclude, responsiveness to UST therapy seems to be associated with body composition modifications in patients with CD. In particular, the increase in phase angle in responders suggests that a significant improvement of nutritional status occurred in these patients.

Assessment of body composition in adults hospitalized with acute COVID-19: a scoping review

Introduction

Body composition (BC) assessment can supply accurate information for in-hospital nutritional evaluation. The aim of this study was to explore in the literature how the studies assessed BC, for what purpose, and investigate the role of BC findings in COVID-19 hospitalized patients' outcomes.

Methods

A scoping review was conducted according to the methodology available on the Joanna Briggs Institute website. We used the PCC acronym for the systematic search (population: adults with COVID-19, concept: assessment of BC, context: hospital setting) and performed it on PubMed, Scopus, and the Web of Science on 16 September 2022. Eligibility criteria consisted of the utilization of BC assessment tools in COVID-19 patients. Studies in which BC was solely measured with anthropometry (perimeters and skinfolds) were excluded. No language restriction was applied.

Results

Fifty-five studies were eligible for the review. Out of the 55 studies, 36 used computed tomography (CT), 13 used bioelectrical impedance (BIA), and 6 used ultrasound (US). No studies with D3-creatinine, 24  h urine excretion, dual-energy X-ray absorptiometry, or magnetic resonance were retrieved. BC was mainly assessed to test associations with adverse outcomes such as disease severity and mortality.

Discussion

Studies assessing BC in hospitalized patients with COVID-19 used mainly CT and BIA and associated the parameters with severity and mortality. There is little evidence of BC being assessed by other methods, as well as studies on BC changes during hospitalization.

Machine and deep learning-based clinical characteristics and laboratory markers for the prediction of sarcopenia

BACKGROUND

Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In this study, we aimed to develop a machine learning model for sarcopenia diagnosis using clinical characteristics and laboratory indicators of aging cohorts.

METHODS

We developed models of sarcopenia using the baseline data from the West China Health and Aging Trend (WCHAT) study. For external validation, we used the Xiamen Aging Trend (XMAT) cohort. We compared the support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGB), and Wide and Deep (W&D) models. The area under the receiver operating curve (AUC) and accuracy (ACC) were used to evaluate the diagnostic efficiency of the models.

RESULTS

The WCHAT cohort, which included a total of 4057 participants for the training and testing datasets, and the XMAT cohort, which consisted of 553 participants for the external validation dataset, were enrolled in this study. Among the four models, W&D had the best performance (AUC = 0.916 ± 0.006, ACC = 0.882 ± 0.006), followed by SVM (AUC =0.907 ± 0.004, ACC = 0.877 ± 0.006), XGB (AUC = 0.877 ± 0.005, ACC = 0.868 ± 0.005), and RF (AUC = 0.843 ± 0.031, ACC = 0.836 ± 0.024) in the training dataset. Meanwhile, in the testing dataset, the diagnostic efficiency of the models from large to small was W&D (AUC = 0.881, ACC = 0.862), XGB (AUC = 0.858, ACC = 0.861), RF (AUC = 0.843, ACC = 0.836), and SVM (AUC = 0.829, ACC = 0.857). In the external validation dataset, the performance of W&D (AUC = 0.970, ACC = 0.911) was the best among the four models, followed by RF (AUC = 0.830, ACC = 0.769), SVM (AUC = 0.766, ACC = 0.738), and XGB (AUC = 0.722, ACC = 0.749).

CONCLUSIONS

The W&D model not only had excellent diagnostic performance for sarcopenia but also showed good economic efficiency and timeliness. It could be widely used in primary health care institutions or developing areas with an aging population.

TRIAL REGISTRATION

Chictr.org, ChiCTR 1800018895.

Raw bioelectrical impedance measurements are not different between White and Black adults when matched for sex, age, BMI, and other physical characteristics

Raw bioelectrical impedance measurements are often used as a prognosticator of health status because of their association with disease states and malnutrition. Although studies consistently show the effect of physical characteristics on bioelectrical impedance, few investigations describe the effect of race, particularly for Black adults, and many bioelectrical impedance standards were produced from primarily White adults almost 2 decades ago. Therefore, this study sought to evaluate the racial differences in bioelectrical impedance measurements using bioimpedance spectroscopy between non-Hispanic White and non-Hispanic Black adults matched for age, sex, and body mass index. We hypothesized that Black adults would have a lower phase angle from higher resistance and lower reactance compared with White adults. One hundred non-Hispanic White (n = 50) and non-Hispanic Black (n = 50) males (n = 34) and females (n = 66) matched for sex, age, and body mass index completed this cross-sectional study. Participants underwent several anthropometric assessments, including height, weight, waist circumference, hip circumference, bioimpedance spectroscopy, and dual-energy X-ray absorptiometry. Bioelectrical impedance measures of resistance, reactance, phase angle, and impedance were all collected at frequencies of 5, 50, and 250 kHz and bioelectrical impedance vector analysis was performed using 50-kHz data. There were no significant differences for any anthropometric variable between Black and White participants in the total sample or by sex groups. In addition, there were no significant racial differences for any bioelectrical impedance assessment, including bioelectrical impedance vector analysis. Differences in bioelectrical impedance are likely not a function of race between Black and White adults and concerns regarding its utility should not be based on this characteristic.

Rheumatoid sarcopenia: loss of skeletal muscle strength and mass in rheumatoid arthritis

Sarcopenia, a disorder that involves the generalized loss of skeletal muscle strength and mass, was formally recognized as a disease by its inclusion in the International Classification of Diseases in 2016. Sarcopenia typically affects older people, but younger individuals with chronic disease are also at risk. The risk of sarcopenia is high (with a prevalence of ≥25%) in individuals with rheumatoid arthritis (RA), and this rheumatoid sarcopenia is associated with increased likelihood of falls, fractures and physical disability, in addition to the burden of joint inflammation and damage. Chronic inflammation mediated by cytokines such as TNF, IL-6 and IFNγ contributes to aberrant muscle homeostasis (for instance, by exacerbating muscle protein breakdown), and results from transcriptomic studies have identified dysfunction of muscle stem cells and metabolism in RA. Progressive resistance exercise is an effective therapy for rheumatoid sarcopenia but it can be challenging or unsuitable for some individuals. The unmet need for anti-sarcopenia pharmacotherapies is great, both for people with RA and for otherwise healthy older adults.

The alterations in multiple neurophysiological procedures are associated with frailty phenotype in older adults

Background

Older adults oftentimes suffer from the conditions in multiple physiologic systems, interfering with their daily function and thus contributing to physical frailty. The contributions of such multisystem conditions to physical frailty have not been well characterized.

Methods

In this study, 442 (mean age = 71.4 ± 8.1 years, 235 women) participants completed the assessment of frailty syndromes, including unintentional weight loss, exhaustion, slowness, low activity, and weakness, and were categorized into frail (≥3 conditions), pre-frail (1 or 2 conditions), and robust (no condition) status. Multisystem conditions including cardiovascular diseases, vascular function, hypertension, diabetes, sleep disorders, sarcopenia, cognitive impairment, and chronic pain were assessed. Structural equation modeling examined the interrelationships between these conditions and their associations with frailty syndromes.

Results

Fifty (11.3%) participants were frail, 212 (48.0%) were pre-frail, and 180 (40.7%) were robust. We observed that worse vascular function was directly associated with higher risk of slowness [standardized coefficient (SC) = −0.419, p &lt; 0.001], weakness (SC = −0.367, p &lt; 0.001), and exhaustion (SC = −0.347, p &lt; 0.001). Sarcopenia was associated with both slowness (SC = 0.132, p = 0.011) and weakness (SC = 0.217, p = 0.001). Chronic pain, poor sleep quality, and cognitive impairment were associated with exhaustion (SC = 0.263, p &lt; 0.001; SC = 0.143, p = 0.016; SC = 0.178, p = 0.004, respectively). The multinomial logistic regression showed that greater number of these conditions were associated with increased probability of being frail (odds ratio&gt;1.23, p &lt; 0.032).

Conclusion

These findings in this pilot study provide novel insights into how multisystem conditions are associated with each other and with frailty in older adults. Future longitudinal studies are warranted to explore how the changes in these health conditions alter frailty status.

Body composition, physical activity, and quality of life in pediatric patients with inflammatory bowel disease on anti-TNF therapy-an observational follow-up study

BACKGROUND

Poor outcome of inflammatory bowel disease (IBD) is associated with malnutrition. Our aim was to compare body composition (BC) and physical activity (PA) between patients with IBD and healthy controls, and to assess the changes in BC, PA and health related quality of life (HRQoL) in children with IBD during anti-TNF therapy.

METHODS

32 children with IBD (21 with Crohn's disease (CD), (age: 15.2 ± 2.6 years, 9 male) and 11 with ulcerative colitis (UC), (age: 16.4 ± 2.2 years, 5 male) participated in this prospective, observational follow up study conducted at Semmelweis University, Hungary. As control population, 307 children (age: 14.3 ± 2.1) (mean ± SD) were included. We assessed BC via bioelectric impedance, PA and HRQoL by questionnaires at initiation of anti-TNF therapy, and at two and six months later. The general linear model and Friedman test were applied to track changes in each variable.

RESULTS

During follow-up, the fat-free mass Z score of children with CD increased significantly (-0.3 vs 0.1, p = 0.04), while the BC of patients with UC did not change. PA of CD patients was lower at baseline compared to healthy controls (1.1 vs. 2.4), but by the end of the follow up the difference disappeared.

CONCLUSIONS

The fat-free mass as well as PA of CD patients increased during the first six months of anti-TNF treatment. As malnutrition and inactivity affects children with IBD during an important physical and mental developmental period, encouraging them to engage in more physical activity, and monitoring nutritional status should be an important goal in patient care.

Serum creatinine/cystatin C ratio is a predictor of all-cause mortality for older adults over 80 years

Objective

Sarcopenia is a prevalent condition in the senior population and has been related to adverse outcomes. This study aimed to investigate the performance of the serum creatinine/cystatin C ratio (Cr/CysC) in predicting all-cause mortality in elders over 80 years.

Methods

A total of 486 older patients over 80 were enrolled in this study. Calf circumference (CC) and handgrip strength (HGS) were carried out for each patient. All the participants accepted serum creatinine and cystatin C test. The primary clinical outcome was all-cause mortality during an over-4-year follow-up.

Results

During an over 4-year follow-up, 200 participants died. The non-survivors had a significantly lower baseline Cr/CysC level than the survivors (62.6 ± 13.1 vs. 71.4 ± 14.5 P < 0.001). The lowest Cr/CysC quartile group (Q1) had a significantly higher mortality rate than their counterparts (Q1 vs. Q2-4, 62.8% vs. 33.2%, P < 0.001). The Cr/CysC level was positively correlated with CC (R² = 0.17, P < 0.001) and HGS (R² = 0.19, P < 0.001). Moreover, survival curve was significantly worse in the lowest Cr/CysC quartile (Log-rank test χ² = 21.09, P < 0.001). After adjustment for potential confounders, age (HR, 1.10; 95% CI, 1.06-1.14, P < 0.001), coronary heart disease (HR, 1.49; 95% CI, 1.01-2.21, P = 0.045), and lowest Cr/CysC (HR, 1.59; 95% CI, 1.12-2.24, P = 0.009) were independent factors of all-cause mortality during the over-4-year follow-up.

Conclusion

Cr/CysC, also known as Sarcopenia Index, could be used as a predictor of all-cause mortality in older adults over 80 years.

Anthropometric equations to estimate appendicular muscle mass from dual-energy X-ray absorptiometry (DXA): A scoping review

BACKGROUND

Appendicular skeletal muscle mass (ASM) obtained from dual-energy x-ray absorptiometry (DXA) is recommended to quantify sarcopenia, but has limited availability in disadvantaged-income countries, moreover in an epidemiological context. Predictive equations are easier and less costly to apply, but a review of all available models is still lacking in the scientific literature. The objective of this work is to map, with a scoping review, the different proposed anthropometric equations to predict ASM measured by DXA.

METHODS

Six databases were searched without restriction on publication date, idiom, and study type. A total of 2,958 studies were found, of which 39 were included. Eligibility criteria involved ASM measured by DXA, and equations proposed to predict ASM.

RESULTS

predictive equations (n = 122) were gathered for 18 countries. The development phase involves sample size, coefficient of determination (r²), and a standard error of estimative (SEE) varying between 15 and 15,239 persons, 0.39 and 0.98, 0.07 and 3.38 kg, respectively. The validation phase involves a sample size, accuracy, and a SEE between 15 and 3,003 persons, 0.61 and 0.98, 0.09 and 3.65 kg, respectively.

CONCLUSIONS

The different proposed predictive anthropometric equations of ASM DXA were mapped, including validated pre-existing equations, offering an easy-to-use referential article for clinical and research applications. It is necessary to propose more equations for other continents (Africa and Antarctica) and specific health-related conditions (e.g., diseases), once the equations can only have sufficient validity and accuracy to predict ASM generally when applied to the same population.

Muscle strength trajectories and their association with postoperative health-related quality of life in patients undergoing coronary artery bypass grafting surgery: a prospective cohort study

BACKGROUND

Patients with sarcopenia have a higher risk of poor recovery after coronary artery bypass grafting (CABG). Little is known about the impact of changes in muscle strength (the primary indicator for sarcopenia) on health-related quality of life (HR-QoL). This study aimed to (1) identify subgroups with different muscle strength trajectories, (2) identify differences in preoperative risk factors among trajectory group membership, and (3) explore their prognostic value on postoperative HR-QoL in patients undergoing CABG.

METHODS

In this prospective observational study 131 patients undergoing elective CABG completed grip strength tests and HR-QoL questionnaires. Latent Class Growth Mixture Modelling (LCGMM) was used to identify clinically relevant trajectories (> 5% of study population) for weight-normalised grip strength, measured at admission, 3 days, and 6 months after surgery. Differences between trajectory group membership at baseline were evaluated. The impact of trajectory group membership on postoperative HR-QoL was evaluated with multiple linear regression models.

RESULTS

Due to low numbers (n = 15), female patients were excluded from LCGMM and subsequent statistical analyses. In males (n = 116), we identified two main weight-normalised grip strength trajectories: a "stable average" trajectory with a slight decline immediately post-surgery and recovery to preoperative levels (n = 85) and a "high" trajectory with a considerable immediate decline after surgery but followed towards a higher level of recovery compared to preoperative level (n = 27). The "stable average" patients were older (68 vs. 57 years; P = 0.003), had more diabetes (27% vs. 4%; P = 0.01) and had a higher BMI (27.8 vs. 24.8; P = 0.005) compared to the "high" group. After correction for age, diabetes, and baseline HR-QoL, group trajectory membership was not associated with postoperative HR-QoL, yet an increase in individual change scores of weight-normalised grip strength was associated with a better postoperative HR-QoL. We also identified one small trajectory group (n = 4, ≤ 5%).

CONCLUSIONS

This study showed two relevant weight-normalised grip strength trajectories in male patients undergoing CABG, varying in important preoperative risk factors. While change scores of grip strength per weight did predict postoperative HR-QoL, the trajectory subgroups could not predict postoperative HR-QoL. Future research should focus on female patients, reacting potentially different on CABG and/or rehabilitation treatment. Trial registration NCT03774342, 12-12-2018.

Sarcopenia and COVID-19 Outcomes

Coronavirus disease 2019 (COVID-19) spread rapidly and became a severe global public health threat. Older adults have a high risk of COVID-19 and its associated mortality. Sarcopenia has emerged as a predictor of poor outcomes in COVID-19 patients, including lengthy hospital stays, mortality, intensive care unit admission, need for invasive mechanical ventilation, and poor rehabilitation outcomes. Chronic inflammation, immune dysfunction, respiratory muscle dysfunction, and swallowing dysfunction may underlie the association between sarcopenia and the poor outcomes of COVID-19 patients. Interleukin 6 receptor blockers (tocilizumab or sarilumab) are recommended for treating patients with severe COVID-19, and their therapeutic effects on sarcopenia are of great interest. This review aimed to analyze the current reports on the association between sarcopenia and COVID-19 and provide an update on the contribution of sarcopenia to the severity and adverse outcomes of COVID-19 and its underlying mechanisms. We also aimed to explore the different screening tools for sarcopenia concurrent with COVID-19, and advocate for early diagnosis and treatment of sarcopenia. Given that the fight against the COVID-19 pandemic may be long-term, further research into understanding the effects of sarcopenia in patients infected with the Omicron variant is necessary.

Comparison of four screening methods for sarcopenia among community-dwelling older adults: A diagnostic accuracy study

This study aimed to compare the diagnostic values of SARC-F (strength, assistance with walking, rising from a chair, climbing stairs, and falls), SARC-Calf (SARC-F combined with calf circumference), CC (calf circumference), and the Yubi-wakka (finger-ring) test for screening for sarcopenia in community-dwelling older adults. The Asian Working Group for Sarcopenia (AWGS) 2019 criteria were used as a standard reference. A total of 209 participants were enrolled, and 40.7% were identified as sarcopenia. The sensitivity, specificity, and AUC were respectively 54.1%, 70.2%, and 0.687 for SARC-F; 76.5%, 73.4% and 0.832 for SARC-calf, 86.7%, 82.4%, and 0.906 for CC in men, and 85.5%, 63.3%, and 0.877 for CC in women. Relative to the "bigger," a significant association between sarcopenia and the Yubi-wakka test ("just fits" OR: 4.1, 95% CI: 1.57-10.98; "small" OR: 27.5, 95% CI: 10.14-74.55) was observed. The overall accuracy of CC was better than SARC-Calf for sarcopenia screening.

Ultrasound and magnetic resonance imaging as diagnostic tools for sarcopenia in immune-mediated rheumatic diseases (IMRDs)

Sarcopenia is characterized by loss of muscle mass, altered muscle composition, fat and fibrous tissue infiltration, and abnormal innervation, especially in older individuals with immune-mediated rheumatic diseases (IMRDs). Several techniques for measuring muscle mass, strength, and performance have emerged in recent decades. The portable dynamometer and gait speed represent the most frequently used tools for the evaluation of muscle strength and physical efficiency, respectively. Aside from dual-energy, X-ray, absorptiometry, and bioelectrical impedance analysis, ultrasound (US) and magnetic resonance imaging (MRI) techniques appear to have a potential role in evaluating muscle mass and composition. US and MRI have been shown to accurately identify sarcopenic biomarkers such as inflammation (edema), fatty infiltration (myosteatosis), alterations in muscle fibers, and muscular atrophy in patients with IMRDs. US is a low-cost, easy-to-use, and safe imaging method for assessing muscle mass, quality, architecture, and biomechanical function. This review summarizes the evidence for using US and MRI to assess sarcopenia.

Between-devices agreement in obtaining raw bioelectrical parameters after a lifestyle intervention targeting weight loss in former athletes

It is unclear if different bioelectrical impedance (BI) devices provide similar results regarding raw parameters [Resistance (R), Reactance (Xc), Phase Angle (PhA), and Impedance (Z)] for the same population/individual undergoing a weight loss intervention. The aim was to evaluate the cross-sectional and longitudinal agreement of raw data obtained by two BI devices in former athletes with overweight/obesity. Fifty-nine participants [mean (SD): 43.5 (9.2) years, 30.5 (4.0) kg/m², 42% females] were included. All the assessments were performed before and after a 4-months lifestyle intervention targeting weight loss (WL). BI parameters were assessed at 50 kHz by two devices: a BI spectroscopy (Xitron Technologies, 4200B, San Diego, USA) and a phase-sensitive single-frequency device (RJL/Akern Systems, BIA-101, Italy). Cross-sectionally, BIS provided lower mean values for all parameters (0.4% for R, 1.6% for Xc, 1.0% for PhA and 0.4% for Z, p <0.001) compared to SF-BIA. In individuals with a WL≥2.5% (n =18), no longitudinal differences were found in any of the raw parameters between devices (p≥0.128) and there was no proportional bias (p≥0.408). Despite small baseline differences in raw BI parameters, both devices agreed in tracking changes over time at the group level but interpretation should be careful at the individual level.

Psoas muscle index predicts time to rehospitalization in liver cirrhosis: An observational study

Sarcopenia is frequent in liver cirrhosis (LC) where it is associated with morbidity and mortality. However, prognostic scores such as model for end-stage liver disease (MELD), MELD-sodium (MELD-Na), or Child-Turcotte-Pugh (CTP) do not contain sarcopenia as a variable. For this study, we utilized psoas muscle index (PMI) to objectively determine sarcopenia in hospitalized LC patients, and evaluated it as a predictor of time between discharge and readmission in LC. Abdominal computed tomography and magnetic resonance imaging scans of 65 consecutive LC patients were retrospectively examined to determine PMI. MELD, MELD-Na, and CTP were calculated from clinical data. PMI was then combined with CTP to form an experimental score: CTP sarcopenia (CTPS). For PMI alone and for each score, correlation with time between discharge and readmission for liver-related complications was calculated. PMI was also tested for correlation with sex, body mass index (BMI), MELD, MELD-Na, and CTP. CTPS was most closely correlated with time to readmission (R = 0.730; P < .001), followed by CTP (R = 0.696; P < .001), MELD-Na (R = 0.405; P = .009), and PMI alone (R = 0.388; P = .01). Correlation with MELD (R = 0.354; P = .05) was lowest. Additionally, there were significant differences in PMI between male and female individuals (5.16 vs 4.54 cm2/m2; P = .04) and in BMI between sarcopenic and nonsarcopenic individuals (29.63 vs 25.88 kg/m2; P = .009). Sarcopenia is an independent short-term prognostic factor in LC. By combining data on sarcopenia with CTP, we created an experimental score that predicts time to readmission better than MELD, MELD-Na, or CTP.

Determination gender-based hybrid artificial intelligence of body muscle percentage by photoplethysmography signal

BACKGROUND AND OBJECTIVE

Muscle mass is one of the critical components that ensure muscle function. Loss of muscle mass at every stage of life can cause many adverse effects. Sarcopenia, which can occur in different age groups and is characterized by a decrease in muscle mass, is a critical syndrome that affects the quality of life of individuals. Aging, a universal process, can also cause loss of muscle mass. It is essential to monitor and measure muscle mass, which should be sufficient to maintain optimal health. Having various disadvantages with the ordinary methods used to estimate muscle mass increases the need for the new high technology methods. This study aims to develop a low-cost and trustworthy Body Muscle Percentage calculation model based on artificial intelligence algorithms and biomedical signals.

METHODS

For the study, 327 photoplethysmography signals of the subject were used. First, the photoplethysmography signals were filtered, and sub-frequency bands were obtained. A quantity of 125 time-domain features, 25 from each signal, have been extracted. Additionally, it has reached 130 features in demographic features added to the model. To enhance the performance, the spearman feature selection algorithm was used. Decision trees, Support Vector Machines, Ensemble Decision Trees, and Hybrid machine learning algorithms (the combination of three methods) were used as machine learning algorithms.

RESULTS

The recommended Body Muscle Percentage estimation model have the perfomance values for all individuals R=0.95, for males R=0.90 and for females R=0.90 in this study.

CONCLUSION

Regarding the study results, it is thought that photoplethysmography-based models can be used to predict body muscle percentage.

Guidance for assessment of the muscle mass phenotypic criterion for the Global Leadership Initiative on Malnutrition diagnosis of malnutrition

The Global Leadership Initiative on Malnutrition (GLIM) provides consensus criteria for the diagnosis of malnutrition that can be widely applied. The GLIM approach is based on the assessment of three phenotypic (weight loss, low body mass index, and low skeletal muscle mass) and two etiologic (low food intake and presence of disease with systemic inflammation) criteria, with diagnosis confirmed by any combination of one phenotypic and one etiologic criterion fulfilled. Assessment of muscle mass is less commonly performed than other phenotypic malnutrition criteria, and its interpretation may be less straightforward, particularly in settings that lack access to skilled clinical nutrition practitioners and/or to body composition methodologies. In order to promote the widespread assessment of skeletal muscle mass as an integral part of the GLIM diagnosis of malnutrition, the GLIM consortium appointed a working group to provide consensus-based guidance on assessment of skeletal muscle mass. When such methods and skills are available, quantitative assessment of muscle mass should be measured or estimated using dual-energy x-ray absorptiometry, computerized tomography, or bioelectrical impedance analysis. For settings where these resources are not available, then the use of anthropometric measures and physical examination are also endorsed. Validated ethnic- and sex-specific cutoff values for each measurement and tool are recommended when available. Measurement of skeletal muscle function is not advised as surrogate measurement of muscle mass. However, once malnutrition is diagnosed, skeletal muscle function should be investigated as a relevant component of sarcopenia and for complete nutrition assessment of persons with malnutrition.

Molecular Mechanisms of Inflammation in Sarcopenia: Diagnosis and Therapeutic Update

Sarcopenia is generally an age-related condition that directly impacts the quality of life. It is also related to chronic diseases such as metabolic dysfunction associated with diabetes and obesity. This means that everyone will be vulnerable to sarcopenia at some point in their life. Research to find the precise molecular mechanisms implicated in this condition can increase knowledge for the better prevention, diagnosis, and treatment of sarcopenia. Our work gathered the most recent research regarding inflammation in sarcopenia and new therapeutic agents proposed to target its consequences in pyroptosis and cellular senescence. Finally, we compared dual X-ray absorptiometry (DXA), magnetic resonance imaging (MRI), and ultrasound (US) as imaging techniques to diagnose and follow up on sarcopenia, indicating their respective advantages and disadvantages. Our goal is for the scientific evidence presented here to help guide future research to understand the molecular mechanisms involved in sarcopenia, new treatment strategies, and their translation into clinical practice.

Regional Lean Soft Tissue and Intracellular Water Are Associated with Changes in Lower-Body Neuromuscular Performance: A Pilot Study in Elite Soccer Players

The assessment of body composition over a competitive season provides valuable information that can help sports professionals to evaluate the efficacy of training and nutritional strategies, as well as monitoring athletes’ health status. The purpose of this study was to examine the association of changes in body composition and hydration status with changes in lower-body neuromuscular performance in soccer. Twenty-two male professional soccer players (mean ± SD; age: 26.4 ± 4.8 years; height: 184.3 ± 5.7 cm; body mass: 81.1 ± 6.5 kg; body fat: 11.6 ± 1.5%) took part in the study, for which they were tested at the initial and final stage of the competitive season. Total (whole body) and regional (arms and legs) lean soft tissue (LST) were estimated to obtain the body composition profile. Total body water (TBW) content, including extracellular (ECW) and intracellular (ICW) water, was obtained to monitor players’ hydration status. Countermovement jump (CMJ) height, power, and strength were used to derive players’ lower-body neuromuscular performance. The results showed that changes in legs LST and ICW significantly (p < 0.01) explained (r2 = 0.39) the improvements in CMJ height, power, and strength from the initial to the final stage of the season. Given the high demand imposed on the lower limbs during a soccer season, being more susceptible to change compared to whole-body LST, assessing regional LST and ICW would be more appropriate to provide extended information on players’ readiness.

Bibliometric Analysis of the Knowledge Base and Future Trends on Sarcopenia from 1999–2021

Sarcopenia is characterized by progressive loss of muscle mass and function, and it is becoming a serious public health problem with the aging population. However, a comprehensive overview of the knowledge base and future trends is still lacking. The articles and reviews with “sarcopenia” in their title published from 1999 to 2021 in the SCIE database were retrieved. We used Microsoft Excel, VOSviewer, and CiteSpace to conduct a descriptive and bibliometric analysis. A total of 3582 publications were collected, from 4 published in 2000 increasing dramatically to 850 documents in 2021. The USA was the most productive country, with the most citations. The Catholic University of the Sacred Heart and Landi F were the most influential organization and author in this field, respectively. The core journal in this field was the Journal of Cachexia Sarcopenia and Muscle. According to the analysis of keywords and references, we roughly categorized the main research areas into four domains as follows: 1. Definition and diagnosis; 2. Epidemiology; 3. Etiology and pathogenesis; 4. Treatments. Comparing different diagnostic tools and the epidemiology of sarcopenia in different populations are recent hotspots, while more efforts are needed in the underlying mechanism and developing safe and effective treatments. In conclusion, this study provides comprehensive insights into developments and trends in sarcopenia research that can help researchers and clinicians better manage and implement their work.

Deep Learning-Based Muscle Segmentation and Quantification of Full-Leg Plain Radiograph for Sarcopenia Screening in Patients Undergoing Total Knee Arthroplasty

Sarcopenia, an age-related loss of skeletal muscle mass and function, is correlated with adverse outcomes after some surgeries. Here, we present a deep-learning-based model for automatic muscle segmentation and quantification of full-leg plain radiographs. We illustrated the potential of the model to predict sarcopenia in patients undergoing total knee arthroplasty (TKA). A U-Net-based deep learning model for automatic muscle segmentation was developed, trained and validated on the plain radiographs of 227 healthy volunteers. The radiographs of 403 patients scheduled for primary TKA were reviewed to test the developed model and explore its potential to predict sarcopenia. The proposed deep learning model achieved mean IoU values of 0.959 (95% CI 0.959-0.960) and 0.926 (95% CI 0.920-0.931) in the training set and test set, respectively. The fivefold AUC value of the sarcopenia classification model was 0.988 (95% CI 0.986-0.989). Of seven key predictors included in the model, the predicted muscle volume (PMV) was the most important of these features in the decision process. In the preoperative clinical setting, wherein laboratory tests and radiographic imaging are available, the proposed deep-learning-based model can be used to screen for sarcopenia in patients with knee osteoarthritis undergoing TKA with high sarcopenia screening performance.

Two-megahertz impedance index prediction equation for appendicular lean mass in Korean older people

Background

Whole-body bioelectrical impedance analysis (BIA) has been accepted as an indirect method to estimate appendicular lean mass (ALM) comparable to dual-energy X-ray absorptiometry (DXA). However, single or limited frequencies currently used for these estimates may over or under-estimate ALM. Accordingly, there is a need to measure the impedance parameter with appendicular lean-specific across multiple frequencies to more accurately estimate ALM. We aimed to validate muscle-specific frequency BIA equation for ALM using multifrequency BIA (MF-BIA) with DXA as the reference.

Methods

195 community-dwelling Korean older people (94 men and 101 women) aged 70 ~ 92y participated in this study. ALM was measured by DXA and bioimpedance measures at frequencies of 5 kHz ~ 3 MHz were assessed for independent predictive variables. Regression analyses were used to find limb-specific frequencies of bioimpedance, to develop the ALM equations and to conduct the internal cross-validation. The six published equations and the final equation of MF-BIA were externally cross-validated.

Results

195 participants completed the measurements of MF-BIA and DXA. Using bivariate regression analysis, the 2 MHz impedance index explained R² = 91.5% of variability (P < 0.001) in ALM and predictive accuracy of standard error of estimate (SEE) was 1.0822 kg ALM (P < 0.001). Multiple stepwise regression analysis obtained in the development group had an adjusted R² of 9.28% (P < 0.001) and a SEE of 0.97 kg ALM. The cross-validation group had no significant difference between the measured ALM and the predicted ALM (17.8 ± 3.9 kg vs. 17.7 ± 3.8 kg, P = .486) with 93.1% of R² (P < 0.001) and 1.00 kg ALM of total error. The final regression equation was as follows: ALM = 0.247ZI_@2 MHz + 1.254SEX_M1F0 + 0.067Xc_@5 kHz + 1.739 with 93% of R² (P < 0.001), 0.97 kg ALM of SEE (Subjective Rating as “excellent” for men and “very good” for women). In the analysis of the diagnostic level for sarcopenia of the final regression, the overall agreement was 94.9% (k = 0.779, P < 0.001) with 71.4% of sensitivity, 98.8% of specificity, 91.3 of positive prediction value and 95.3% of negative prediction value.

Conclusion

The newly developed appendicular lean-specific high-frequency BIA prediction equation has a high predictive accuracy, sensitivity, specificity, and agreement for both individual and group measurements. Thus, the high-frequency BIA prediction equation is suitable not only for epidemiological studies, but also for the diagnosis of sarcopenia in clinical settings.

Bioelectrical Impedance Analysis for the Assessment of Body Composition in Sarcopenia and Type 2 Diabetes

Sarcopenia is emerging as a severe complication in type 2 diabetes (T2DM). On the other hand, it has been documented that nutritional aspects, such as insufficient protein or total energy intake, increase sarcopenia risk. The analysis of body composition is a relevant approach to assess nutritional status, and different techniques are available. Among such techniques, bioelectrical impedance analysis (BIA) is particularly interesting, since it is non-invasive, simple, and less expensive than the other techniques. Therefore, we conducted a review study to analyze the studies using BIA for body composition analysis in T2DM patients with sarcopenia or at risk of catching it. Revised studies have provided important information concerning relationships between body composition parameters (mainly muscle mass) and other aspects of T2DM patients’ conditions, including different comorbidities, and information on how to avoid muscle mass deterioration. Such relevant findings suggest that BIA can be considered appropriate for body composition analysis in T2DM complicated by sarcopenia/muscle loss. The wide size of the patients’ cohort in many studies confirms that BIA is convenient for clinical applications. However, studies with a specific focus on the validation of BIA, in the peculiar population of patients with T2DM complicated by sarcopenia, should be considered.

Guidance for assessment of the muscle mass phenotypic criterion for the Global Leadership Initiative on Malnutrition (GLIM) diagnosis of malnutrition

The Global Leadership Initiative on Malnutrition (GLIM) provides consensus criteria for the diagnosis of malnutrition that can be widely applied. The GLIM approach is based on the assessment of three phenotypic (weight loss, low body mass index, and low skeletal muscle mass) and two etiologic (low food intake and presence of disease with systemic inflammation) criteria, with diagnosis confirmed by any combination of one phenotypic and one etiologic criterion fulfilled. Assessment of muscle mass is less commonly performed than other phenotypic malnutrition criteria, and its interpretation may be less straightforward, particularly in settings that lack access to skilled clinical nutrition practitioners and/or to body composition methodologies. In order to promote the widespread assessment of skeletal muscle mass as an integral part of the GLIM diagnosis of malnutrition, the GLIM consortium appointed a working group to provide consensus-based guidance on assessment of skeletal muscle mass. When such methods and skills are available, quantitative assessment of muscle mass should be measured or estimated using dual-energy x-ray absorptiometry, computerized tomography, or bioelectrical impedance analysis. For settings where these resources are not available, then the use of anthropometric measures and physical examination are also endorsed. Validated ethnic- and sex-specific cutoff values for each measurement and tool are recommended when available. Measurement of skeletal muscle function is not advised as surrogate measurement of muscle mass. However, once malnutrition is diagnosed, skeletal muscle function should be investigated as a relevant component of sarcopenia and for complete nutrition assessment of persons with malnutrition.

Accuracy of Estimated Bioimpedance Parameters with Octapolar Segmental Bioimpedance Analysis

The validity of the impedance parameters of the five body segments estimated using octapolar segmental bioelectrical impedance analysis (OS-BIA) has not been confirmed. This study aimed to verify the accuracy of the resistance (R), reactance (Xc), and phase angle of each five-body segment. The accuracy of the OS-BIA at 50 kHz was measured based on the direct tetrapolar segmental BIA. The differences in the estimated impedance parameters of the five body segments were compared to those measured from the OS-BIA in elderly men (N = 73) and women (N = 63). The estimated 50 kHz-R (Ω) was significantly higher than the measured 50 kHz-R in the right and left arms, and lower than the measured 50 kHz-R of the trunk, right leg, and left leg (all, p < 0.05). The estimated 50 kHz-phase angles in all the five body segments were significantly lower than the measured ones (all, p < 0.05). The findings suggest that the estimated impedance parameters, R, Xc, and phase angle of the trunk, were remarkedly underestimated, limiting the assessment of the physiological state of the organs in the body. Therefore, further intensive research is needed in the field of estimated segmental BIA in the future.

Low muscle mass is an independent risk factor for postoperative blood transfusion in total knee arthroplasty: a retrospective, propensity score-matched cohort study

Background

Sarcopenia, an age-related loss of skeletal muscle mass and function, is correlated with adverse outcomes after some surgeries. This study examined the characteristics of sarcopenic patients undergoing primary total knee arthroplasty (TKA), and identified low muscle mass as an independent risk factor for postoperative TKA complications.

Methods

A retrospective cohort study examined 452 patients who underwent TKA. The skeletal muscle index (SMI) was obtained via bioelectrical impedance analysis (BIA), along with demographics, the Charlson Comorbidity Index, and medication, laboratory and operative data for 2018–2021. Patients were categorized into normal (n = 417) and sarcopenic (n = 35) groups using the SMI cut-off suggested by the Asian Working Group for Sarcopenia 2019 (males, < 7.0 kg/m²; females, < 5.7 kg/m²). Three postoperative complications were analysed: blood transfusion, delirium, and acute kidney injury (AKI). Baseline characteristics were propensity score-matched to address potential bias and confounding factors.

Results

The proportion of sarcopenic patients in primary TKA was 7.7% (35/452). The sarcopenic group had a lower preoperative haemoglobin (12.18 ± 1.20 vs. 13.04 ± 1.73 g/dL, p = 0.004) and total protein (6.73 ± 0.42 vs. 7.06 ± 0.44 mg/dL, p = 0.001). Propensity scoring matching and logistic regression showed that more patients in the sarcopenic group received postoperative blood transfusions (OR = 6.60, 95% CI: 1.57–45.5, p = 0.021); there was no significant difference in AKI or delirium. Univariate receiver operating characteristic curve analysis of the propensity-matched group, to determine the predictive value of SMI for postoperative transfusion, gave an AUC of 0.797 (0.633–0.96) and SMI cut-off of 5.6 kg/m².

Conclusions

Low muscle mass determined by BIA was an independent risk factor for postoperative transfusion in TKA. Multifrequency BIA can serve as a screening tool for sarcopenia that may influence the orthopaedic decision-making process or treatment planning in patients with sarcopenia undergoing primary TKA.

Level of evidence

III, retrospective cohort study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02903-0.

Different combinations of the GLIM criteria for patients awaiting a liver transplant: Poor performance for malnutrition diagnosis but a potentially useful prognostic tool

BACKGROUND & AIMS

Studies using the Global Leadership Initiative on Malnutrition (GLIM) criteria for patients with liver cirrhosis are limited. This study aimed to assess the impact of malnutrition according to the GLIM criteria on the outcomes of patients awaiting a liver transplant (LTx) and compare these criteria with Subjective Global Assessment (SGA).

METHODS

This retrospective observational study included adult patients awaiting LTx. Patient clinical data, nutritional status according to various tools including SGA, and resting energy expenditure were assessed. The distinct phenotypic and etiologic criteria provided 36 different GLIM combinations. The GLIM criteria and SGA were compared using the kappa coefficient. The variables associated with mortality before and after the LTx and with a longer length of stay (LOS) after LTx (≥18 days) were assessed by Cox regression and logistic regression analyses, respectively.

RESULTS

A total of 152 patients were included [median age 52.0 (interquartile range: 46.5-59.5) years; 66.4% men; 63.2% malnourished according to SGA]. The prevalence of malnutrition according to the GLIM criteria ranged from 0.7% to 30.9%. The majority of the GLIM combinations exhibited poor agreement with SGA. Independent predictors of mortality before and after LTx were presence of ascites or edema (p = 0.011; HR:2.58; CI95%:1.24-5.36), GLIM 32 (PA-phase angle + MELD) (p = 0.026; HR:2.08; CI95%:1.09-3.97), GLIM 33 (PA + MELD-Na≥12) (p = 0.018; HR:2.17; CI95%:1.14-4.13), and GLIM 34 (PA + Child-Pugh) (p = 0.043; HR:1.96; CI95%:1.02-3.77). Malnutrition according to GLIM 28 (handgrip strength + Child-Pugh) was independently associated with a longer LOS (p = 0.029; OR:7.21; CI95%:1.22-42.50).

CONCLUSION

The majority of GLIM combinations had poor agreement with SGA, and 4 of the 36 GLIM combinations were independently associated with adverse outcomes.

Impact of Different Operational Definitions of Sarcopenia on Prevalence in a Population-Based Sample: The Salus in Apulia Study

Background: In 2010, the European Working Group on Sarcopenia in Older People (EWGSOP1) issued its first operational definition to diagnose sarcopenia. This was updated in 2019 with a revised sequence of muscle mass and muscle strength (EWGSOP2). The aim of the study was to investigate the impact of these different operational definitions on sarcopenia prevalence in a representative population-based sample. Methods: For each algorithm, the prevalence of sarcopenia-related categories was calculated and related to sociodemographic and lifestyle variables, anthropometric parameters, and laboratory biomarkers. The present analysis used data from the Salus in Apulia Study (Italy, 740 subjects, mean age 75.5 ± 5.9 years, 54% women). Results: The application of the EWGSOP1 adapted algorithm resulted in 85% [95% confidence intervals (CI): 82–88%] non-sarcopenic subjects, 10% (95% CI: 8–12%) pre-sarcopenic subjects, and 5% (95% CI: 3–7%) sarcopenic/severe sarcopenic subjects. The sarcopenia-related categories were inversely related to weight and body mass index (BMI), particularly in overweight/obese subjects, and these categories showed favorable metabolic biomarkers. The EWGSOP2 algorithm yielded 73% (95% CI: 69–76%) non-sarcopenic subjects, 24% (95% CI: 21–27%) probably sarcopenic subjects, and 4% (95% CI: 2–5%) sarcopenic subjects. Conclusions: The present study identified BMI as a potential confounder of the prevalence estimates of sarcopenia-related categories in population-based settings with different EWGSOP operational definitions.