Estimation Of Muscle Mass Research Articles

Appendicular Skeletal Muscle Mass (ASMM) and Fat-Free Mass (FFM) DXA–BIA Estimations for the Early Identification of Sarcopenia/Low Muscle Mass in Middle-Aged Women

Background/Objectives: Sarcopenia involves the loss of muscle mass along with a decrease in muscle strength and physical performance. The aim of this paper was to compare the already published BIA equations for the estimation of Appendicular Skeletal Muscle Mass (ASMM) and Fat-Free Mass (FFM) with dual X-ray densitometer DXA estimations in order to determine whether Bioelectrical Impedance Analysis (BIA) could be a feasible application on a general population for the detection of low muscle mass and sarcopenia. Methods: Seventy-nine healthy women aged 40–70 years were included. Assessments involved BIA and DXA evaluations and anthropometric measurements. Results: DXA and BIA estimations showed great agreement, particularly the ones introduced by Scafoglieri et al. (2017) for ASMM (mean difference 1.81 kg) and Kanellakis et al. (2020) equation for FFM (mean difference 0.52 kg) resulted in the best fit for the cohort in analysis. BIA could intercept a low muscle mass condition which can be linked to sarcopenia. Conclusions: This study showed how the use of BIA represents an effective and reliable method in the evaluation of sarcopenia.

Skeletal muscle size and quality in healthy kidney donors, normal range and clinical associations

The gold standard to estimate muscle mass and quality is computed tomography (CT) scan. Lower mass and density (intramuscular fat infiltration) of skeletal muscles are markers of sarcopenia, associated with increased mortality risk, impaired physical function, and poorer prognosis across various populations and medical conditions. We aimed to describe standard reference values in healthy population, prospective kidney donors, and correlate clinical parameters to muscle mass and density. Included in the cohort 384 consecutive kidney donors. Mean age was 44.6 ± 11.5 (range 18.4–74.2), 46% were female and mean BMI was 25.6 ± 3.8 kg/m2. Our quantified reference values for psoas cross -sectional area (CSA) index at L3 level (males/females respectively) were 6.3 ± 1.8 and 4.8 ± 1.9 cm2 /m2, and density was 46.1 ± 5 and 41 ± 5 HU at that level. Older age (standardized beta coefficient − 0.12, p = 0.04), sex (− 0.32, p < 0.001) and BMI (0.17, p = 0.002) were significantly associated with CSA index of psoas at L3. Density, however, was associated with triglycerides level (− 0.21, p < 0.001), in addition to age (− 0.22, p < 0.0001), sex (− 0.27, p < 0.001) and BMI (− 0.1, p = 0.05). Our study validates the normative values of psoas muscle mass and density in healthy individuals and suggests correlations with clinical parameters. We demonstrate the significance of measuring not only the mass of the muscle, but also its density, as it has a valid association with metabolic parameters, including BMI and lipid level, even in healthy individuals and in the normal range of the tests.

Accelerated muscle mass estimation from CT images through transfer learning

BackgroundThe cost of labeling to collect training data sets using deep learning is especially high in medical applications compared to other fields. Furthermore, due to variances in images depending on the computed tomography (CT) devices, a deep learning based segmentation model trained with a certain device often does not work with images from a different device.MethodsIn this study, we propose an efficient learning strategy for deep learning models in medical image segmentation. We aim to overcome the difficulties of segmentation in CT images by training a VNet segmentation model which enables rapid labeling of organs in CT images with the model obtained by transfer learning using a small number of manually labeled images, called SEED images. We established a process for generating SEED images and conducting transfer learning a model. We evaluate the performance of various segmentation models such as vanilla UNet, UNETR, Swin-UNETR and VNet. Furthermore, assuming a scenario that a model is repeatedly trained with CT images collected from multiple devices, in which is catastrophic forgetting often occurs, we examine if the performance of our model degrades.ResultsWe show that transfer learning can train a model that does a good job of segmenting muscles with a small number of images. In addition, it was confirmed that VNet shows better performance when comparing the performance of existing semi-automated segmentation tools and other deep learning networks to muscle and liver segmentation tasks. Additionally, we confirmed that VNet is the most robust model to deal with catastrophic forgetting problems.ConclusionIn the 2D CT image segmentation task, we confirmed that the CNN-based network shows better performance than the existing semi-automatic segmentation tool or latest transformer-based networks.

Reliability of calf circumference and mid-upper arm circumference as estimates of muscle mass

Reliability of calf circumference and mid-upper arm circumference as estimates of muscle mass

The POISE Study: POcus for Identification of Sarcopenia in Emergency departments

Abstract Background Sarcopenia is a progressive loss of muscle mass and strength, primarily affecting older adults, with a prevalence of up to 20% in &amp;gt;65-year-olds. It is associated with poor outcomes such as fractures, falls, loss of independence and mortality. Recent studies into the use of ultrasonography for sarcopenia diagnosis have yielded promising results, with good validity to estimate muscle mass when compared to DXA, CT or MRI. While point-of-care ultrasound (POCUS) is a commonly used technique in Emergency Medicine, its applicability to sarcopenia diagnosis in an ED setting has not been investigated. Methods This was a prospective, cross-sectional, observational pilot study. Patients &amp;gt;65 years were recruited sequentially from the ED triage list. Each subject had a POCUS scan of their thighs, to visualise and measure the thickness of the femoral quadriceps. Subjects’ handgrip was then measured using a digital grip strength dynamometer. Subjects’ gait speed was measured in metres per second using a standard 6 metre walk test. Data was then analysed to examine any correlation between muscle thickness on POCUS and functional measures of sarcopenia. Results 60 patients were recruited into this pilot study. Of these, 50% had evidence of sarcopenia on functional assessment. There was a statistically significant correlation between muscle thickness on POCUS and performance on functional assessment. Conclusion This pilot study demonstrates a possible new application for POCUS in the ED. This could guide therapy for falls prevention and may prevent further morbidity in this vulnerable population. Further research is needed to confirm the results of this pilot study within a wider population. Additional research examining the correlation between POCUS findings, Clinical Frailty Scale, and BMI would also be of benefit.

Estimation equation of limb lean soft tissue mass in Asian athletes using bioelectrical impedance analysis.

The lean soft tissue mass (LSTM) of the limbs is approximately 63% of total skeletal muscle mass. For athletes, measurement of limb LSTM is the basis for rapid estimation of skeletal muscle mass. This study aimed to establish the estimation equation of LSTM in Asian athletes using bioelectrical impedance analysis (BIA). A total of 198 athletes (121 males, 77 females; mean age 22.04 ± 5.57 years) from different sports in Taiwan were enrolled. A modeling group (MG) of 2/3 (n = 132) of subjects and a validation group (VG) of 1/3 (n = 68) were randomly assigned. Using the InBody S-10, resistance and reactance were measured at 50 kHz from the right palm to the right sole while the participant was in the supine position. Predictor variables were height (h), weight (W), age, Sex, Xc, resistance index (RI; RI = h2 / R). LSTM of arms and legs measured by dual-energy X-ray absorptiometry (DXA) was the response variable. Multivariate stepwise regression analysis method was used to establish BIA estimation equations as ArmsLSTMBIA-Asian and LegsLSTMBIA-Asian. Estimation equations performance was confirmed by cross-validation. Estimation equation "ArmsLSTMBIA-Asian = 0.096 h2/R- 1.132 Sex + 0.030 Weight + 0.022 Xc- 0.022 h + 0.905, r2 = 0.855, SEE = 0.757 kg, n = 132" and "LegsLSTMBIA Asian = 0.197h2/R" + 0.120 h- 1.242 Sex + 0.055 Weight- 0.052 Age + 0.033 Xc -16.136, r2 = 0.916, SEE = 1.431 kg, n = 132" were obtained from MG. Using DXA measurement results of VG for correlation analysis and Limit of Agreement (LOA) of Bland-Altman Plot, ArmsLST is 0.924, -1.53 to 1.43 kg, and LegsLST is 0.957, -2.68 to 2.90 kg. The established single-frequency BIA hand-to-foot (whole body) estimation equation quickly and accurately estimates LSTM of the arms and legs of Asian athletes.

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

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. 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. 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). 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.

Unraveling the enigma of sarcopenia and sarcopenic obesity in Indian adults with type 2 diabetes – a comparative cross-sectional study

BackgroundSarcopenia and sarcopenic obesity are growing concerns associated with increasing diabetes incidence, but data from Indian diabetic cohorts are limited. This study examined the prevalence and clinical factors associated with sarcopenia and sarcopenic obesity.MethodsIn this cross-sectional study, 750 participants aged 35–70 years were recruited by systematic stratification and a fixed quota sampling technique from medical camps and categorized into diabetic (n = 250), nondiabetic (n = 250), and obese nondiabetic (n = 250) groups. The assessments included questionnaires, muscle mass estimation by bioimpedance analysis, and blood tests. Sarcopenia was defined using the Asian Working Group consensus, and sarcopenic obesity was defined as sarcopenia with a BMI ≥ 25 kg/m2. Logistic regression was used to analyze risk factors.ResultsSarcopenia affected 60% of diabetic patients, 28% of nondiabetic patients, and 38% of nonobese nondiabetic patients (p < 0.001). The prevalence of sarcopenic obesity was 40%, 11%, and 30%, respectively (p < 0.001). Diabetes was associated with 2.3-fold greater odds (95% CI 1.1–4.7) of sarcopenia and 2.4-fold greater odds (1.1-5.0) of sarcopenic obesity after adjustment. A duration greater than 10 years, uncontrolled diabetes, age greater than 65 years, low physical activity, hypertension, and dyslipidemia also independently increased the odds.ConclusionIndian adults with type 2 diabetes have a high burden of sarcopenia and sarcopenic obesity. Early optimization of diabetes care and lifestyle changes are vital for preserving muscle health.

Relationship between muscle stiffness derived from fatigue and estimated muscle mass

Relationship between muscle stiffness derived from fatigue and estimated muscle mass

Fully-automated CT derived body composition analysis reveals sarcopenia in functioning adrenocortical carcinomas

Determination of body composition (the relative distribution of fat, muscle, and bone) has been used effectively to assess the risk of progression and overall clinical outcomes in different malignancies. Sarcopenia (loss of muscle mass) is especially associated with poor clinical outcomes in cancer. However, estimation of muscle mass through CT scan has been a cumbersome, manually intensive process requiring accurate contouring through dedicated personnel hours. Recently, fully automated technologies that can determine body composition in minutes have been developed and shown to be highly accurate in determining muscle, bone, and fat mass. We employed a fully automated technology, and analyzed images from a publicly available cancer imaging archive dataset (TCIA) and a tertiary academic center. The results show that adrenocortical carcinomas (ACC) have relatively sarcopenia compared to benign adrenal lesions. In addition, functional ACCs have accelerated sarcopenia compared to non-functional ACCs. Further longitudinal research might shed further light on the relationship between body component distribution and ACC prognosis, which will help us incorporate more nutritional strategies in cancer therapy.

Coronal Plane Assessment for Levator Trauma.

Levator avulsion is a major etiological factor of pelvic organ prolapse (POP) and is primarily diagnosed on tomographic axial plane imaging. Two-dimensional imagingcan also image the levator. The objective was to test reproducibility and validity of coronal plane assessment for diagnosis of levator trauma by assessing the coronal plane obtained on tomographic ultrasound imaging. A retrospective study of women who had undergone an interview, POPQ and four-dimensional translabial ultrasound at a tertiary urogynecological unit. Post-processing of archived volume data was performed for assessment; and levator muscle area and estimate of remnant muscle mass in the coronal plane. Interobserver reproducibility of the latter two measures and associations between various measures of levator trauma and POP were tested. Interobserver agreement was good for percentage estimates (ICC 0.743), but fair for area measurements (ICC 0.482). Six hundred and twenty four women were seen, 468 (75%) had significant clinical prolapse. Full levator avulsions were diagnosed in 137 (22%). Mean TTS was 2.7 (range 0-12). On coronal plane assessment average muscle area was 1.47 (SD 0.76) cm2 and 1.55 (SD 0.74) cm2 on the right and left, respectively (P = .005). It was 76% and 79% for average estimates of muscle mass (P = .021). Both measures were strongly associated with POP; however, they were not superior to TTS in predicting POP. Coronal plane assessment in volume data is reproducible and valid for evaluation of levator trauma. Muscle mass estimate may be a better measure than muscle area.

#2796 Divergent associations between mortality and different measures of renal function after adjustment for body composition: results from the UK Biobank

Abstract Background and Aims There is data suggesting estimated glomerular filtration rate using Cystatin-C (eGFRCystatin-C) is superior to the creatinine-based (eGFRCreat) method when assessing associations between renal function and mortality (Lees et al. 2019). Given cystatin-C is derived from all nucleated cells and creatinine from skeletal muscle, there remains a need to understand how controlling for multimorbidity, inflammation and estimates of muscle mass will affect the association between mortality and these different measures of renal function. Method An observational study was conducted using the UK Biobank cohort. Adults were recruited between 2007-2010 at 22 UK centres. MM was estimated using bioimpedance defined whole body fat-free mass (BI-FFM: Tanita BC418). The primary outcome was all-cause mortality (ACM—data from NHS Information Centre [England / Wales] and NHS Central Registry [Scotland]). Follow up was defined as the period between the first visit date to either date of death / the latest date for central registry downloads (December 2021). Estimated GFRCreat or eGFRCystatin-C were calculated using the CKD-EPI 2009 equation without ethnicity correction. Albuminuria was defined as a urine albumin / creatinine ratio of &amp;gt;3 mg/mmol. Participants were excluded if they were on dialysis, died from SARS-CoV-2 infection or withdrew consent. Sequences of regressions analyses (SoRA), a graphical Markov modelling technique which assesses complex direct and indirect pathways of association between blocks of variables which are ordered a-priori to reflect postulated directions of association, were constructed for both eGFRCreat and eGFRCystatin-C. Results There were 500,589 participants eligible for analysis (272,623 females / 227,966 males). There were 10,299 and 21,319 participants with eGFRCreat and eGFRCystatin-C &amp;lt; 60 ml/min/1.73 m2 respectively, and 25,308 with a urine albumin/creatinine ratio &amp;gt; 3 mg/mmol. There were 33,755 deaths over a median follow up period of 12.58 (IQR 11.85-13.30) yrs. Higher eGFRCreat was associated with higher odds of ACM in men (OR 1.012, 95% CI 1.004-1.020) and women (OR 1.010, 95% CI 1.001-1.018) in the presence of an interaction with weight in both sexes. Higher eGFRCystatin-C was associated with lower odds of ACM in men (OR 0.978, 95% CI 0.968-0.988) and women (Fig. 1: OR 0.986, 95% CI 0.984-0.987). In men there was an interaction between eGFRCystatin-C and weight observed but no such interaction was observed in women. Interaction plots showed that weight had less influence on the association between ACM and renal function in the eGFRCystatin-C compared to the eGFRCreat sub-models. Conclusion Higher eGFRCreat is associated with higher odds of ACM when controlling for FFM and weight, whereas higher eGFRCystatin-C is associated with lower odds of ACM. This suggests eGFRCystatin-C is more resilient to the effects of variable body composition when compared with eGFRCreat, providing a potential explanation for the stronger association between eGFRCystatin-C and mortality in patients with long term conditions including in chronic kidney disease (CKD). In this model, eGFRCreat should be viewed as a FFM surrogate.

Bioelectrical Impedance Analysis Detects Body Fat Changes After Surgical Subcutaneous Fat Removal.

Background: The risk and metabolic effects of obesity are determined by the distribution of fat throughout the body. It has been proposed that the distribution of abdominal fat is more closely related to the metabolic risks of obesity. High prevalence of overweight and obesity has thereby contributed to an increased uptake of surgical subcutaneous fat removal (SSFR) procedures. The goal of this study was to determine whether bioelectrical impedance analysis (Tanita system) can be used to detect the removal of excess abdominal subcutaneous fat tissue during SSFR when studying the metabolic effects of such procedures. Methods: Study population comprised patients who received body contouring procedures at the Hamad General Hospital's plastic surgery department between November 2020 and December 2022. To evaluate the factors of interest, subjects were prospectively followed up at two time points: within 1 week before the surgery and within 1-2 weeks thereafter. The following factors were measured: body weight, body fat percentage, body fat mass, body mass index (BMI), fat-free mass, estimated muscle mass, total body water, visceral fat score, and basal metabolic rate. Results: In total, 22 patients were included in the study. The two visits' medians for height, weight, BMI, fat percent (fat%), fat mass, visceral fat rating, and Doi's weighted average glucose (dwAG) were compared. Only in the case of Tanita fat% and fat mass, were the preoperative and postoperative medians significantly different. Furthermore, there was no association between these Tanita measures and dwAG or homeostatic model assessment (HOMA; insulin resistance [IR]) changes (before and after surgery). Tanita measures overestimated fat loss, as seen by the mountain plot and Bland-Altman plot agreement methods. Conclusions: Our findings indicated that the only two Tanita measures exhibited meaningful early associations with the amount of tissue excised which were fat mass and fat% differences. Although dwAG and HOMA-IR are not impacted immediately postsurgery, a trend was seen that suggested improvements in those parameters, even though the changes are not clinically significant.

Prevalence of low calf circumference in hospitalized patients classified by raw or body mass index-adjusted values.

Adiposity can influence the estimation of muscle mass using calf circumference (CC) and underestimate the frequency of low CC. An adjustment for CC using body mass index (BMI) was proposed to reduce this effect. We aimed to compare the low CC frequency in hospitalized patients when considering raw and BMI-adjusted values and explore data by sex, age, and race (white and non-white). Secondary analysis from two cohort studies conducted with adult hospitalized patients using BMI and CC data collected in the first 72 h after hospital admission. We classified low CC by two approaches: (1) raw CC; (2) BMI-adjusted CC for patients with BMI ≥ 25. Cutoff values for low CC were ≤34 cm (men) and ≤33 cm (women). Among 1272 patients (54.1 ± 15.3 years old; 51.7% women; 82.1% White race), low CC frequency was 30.6% and low BMI-adjusted CC was 68.9%. For all elevated BMI categories, the low CC frequency was higher when considering BMI-adjusted values (P < 0.001). Low CC was more frequent (P < 0.001) in older adults (38.7% by raw; 79.1% by BMI-adjusted value) than in younger adults (27.6% by raw; 65.2% by BMI-adjusted value) and it was not associated with race. Low CC by raw values was more frequent in men than in women (35.0% versus 26.4%; P = 0.001), but did not differ between sexes when classified by BMI-adjusted values (70.7% versus 67.1%; P = 0.184). Low CC BMI adjusted was 2.2 times more frequent in comparison with raw CC values, and it was identified in >60% of patients with BMI ≥ 25.

The agreement of different techniques for muscle measurement in diagnosing sarcopenia: a systematic review and meta-analysis.

The measurement or estimation of muscle mass plays an important role in the diagnosis of sarcopenia. Beside dual-energy X-ray absorptiometry (DXA), several modalities, including bioelectrical impedance analysis (BIA), ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI), have helped to provide imaging or electrical biomarkers for muscle mass. This study was aimed at summarizing the diagnostic performance of different techniques on muscle assessment for sarcopenia. Studies on the assessment of muscle mass by different techniques (compared with DXA), published from inception to 12 October, 2023 were retrieved from 4 electronic databases: the Cochrane Library, Embase, PubMed, and Web of Science. The quality assessment of included studies was conducted using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The sensitivity, specificity, Cohen's kappa coefficient (κ), and Pearson correlation coefficient (r) with 95% confidence intervals (CIs) were pooled and presented via forest plots. The area under the curve (AUC) with 95% CI was pooled and presented via summary receiver operating characteristic (sROC) curve. A total of 28 studies involving 4,926 participants were included. Compared with DXA, the pooled sensitivity and specificity, AUC, and Cohen's κ were 0.79 (95% CI: 0.71-0.86, P<0.001), 0.95 (95% CI: 0.82-0.99, P<0.001), and 0.88 (95% CI: 0.85-0.90), and 0.61 (95% CI: 0.51-0.72) for BIA. The pooled r value between DXA and BIA or US or MRI was 0.94 (95% CI: 0.92-0.96, P<0.001), 0.69 (95% CI: 0.54-0.80, P<0.001), and 0.96 (95% CI: 0.95-0.97, P=0.21), respectively. No qualified original study in relation to CT was included. BIA, US, and MRI would provide acceptable diagnostic accuracy for sarcopenia by evaluating muscle mass in terms of sensitivity, specificity, accuracy, and their higher correlations with DXA. Further investigation is required to elucidate the value of CT in diagnosing sarcopenia.

Association between nutrition intake and muscle mass in adult inpatients receiving nutrition support: A prospective cohort study.

The present study aimed to evaluate the association between muscle mass variation, estimated by different equations, during hospitalization with the energy and protein intake and clinical and nutrition outcomes of patients using nutrition support. A prospective observational study with patients older than 18 years in use of enteral and/or parenteral nutrition therapy and monitored by the Nutritional Therapy Committee between December 14, 2021, and December 14, 2022. Data were collected from the electronic records and were applied in 11 equations to estimate the four different portions of muscle mass of patients receiving nutrition support at the beginning and the end of hospitalization. A total of 261 patients were evaluated, with a median age of 61.0 (49.0-69.75) years, and 106 were women (40.6%). According to the nutrition diagnosis, several participants had severe malnutrition (39.5%). The most muscle mass estimation equations indicated a reduction of muscle mass during hospitalization. All patients presented negative energy and protein balances during hospitalization, but greater protein intake increased the lean soft tissue. Also, the greater the number of infections, metabolic complications, and scheduled diet interruption, the greater was the chance of losing muscle mass. There can be an association between the variation in muscle mass and energy and protein intake during hospitalization of patients using nutrition support. In addition, variation in muscle mass was associated with complications from nutrition support. The results emphasize the importance of anthropometric measurements to estimate muscle mass when other methods are not available.

Bioimpedance-assessed muscle wasting and its relation to nutritional intake during the first week of ICU: a pre-planned secondary analysis of Nutriti Study

BackgroundMuscle mass evaluation in ICU is crucial since its loss is related with long term complications, including physical impairment. However, quantifying muscle wasting with available bedside tools (ultrasound and bioimpedance analysis) must be more primarily understood. Bioimpedance analysis (BIA) provides estimates of muscle mass and phase angle (PA).The primary aim of this study was to evaluate muscle mass changes with bioimpedance analysis during the first 7 days after ICU admission. Secondary aims searched for correlations between muscular loss and caloric and protein debt.MethodsPatients with an expected ICU-stay ≥ 72 h and the need for artificial nutritional support were evaluated for study inclusion. BIA evaluation of muscle mass and phase angle were performed at ICU admission and after 7 days. Considering the difference between ideal caloric and protein targets, with adequate nutritional macronutrients delivered, we calculated the caloric and protein debt. We analyzed the potential correlation between caloric and protein debt and changes in muscle mass and phase angle.Results72 patients from September 1st to October 30th, 2019 and from August 1st to October 30th, 2021 were included in the final statistical analysis. Median age was 68 [59–77] years, mainly men (72%) admitted due to respiratory failure (25%), and requiring invasive mechanical ventilation for 7 [4–10] days. Median ICU stay was 8 [6–12] days. Bioimpedance data at ICU admission and after 7 days showed that MM and PA resulted significantly reduced after 7 days of critically illness, 34.3 kg vs 30.6 kg (p < 0.0001) and 4.90° vs 4.35° (p = 0.0004) respectively. Mean muscle loss was 3.84 ± 6.7 kg, accounting for 8.4% [1–14] MM reduction. Correlation between caloric debt (r = 0.14, p = 0.13) and protein debt (r = 0.18, p = 0.13) with change in MM was absent. Similarly, no correlation was found between caloric debt (r = -0.057, p = 0.631) and protein debt (r = -0.095, p = 0.424) with changes in PA.Conclusionsbioimpedance analysis demonstrated that muscle mass and phase angle were significantly lower after 7 days in ICU. The total amount of calories and proteins does not correlate with changes in muscle mass and phase angle.

Sarcopenia diagnosed by ultrasound-assessed quadriceps muscle thickness and handgrip strength predicts mortality in patients on hemodialysis.

Estimation of muscle mass is a pivotal component in the diagnosis of protein-energy wasting and sarcopenia. While bioimpedance spectroscopy is a widely accepted technique for the assessment of lean tissue related to the diagnosis of sarcopenia, to date skeletal muscle ultrasound (US) has not gained full acceptance for this purpose. The aim of this study was to assess the predictive value for mortality of the indexed thickness of the quadriceps vastus intermedius, as measured by US, compared to lean tissue index as estimated by bioimpedance spectroscopy, both combined with handgrip strength in a group of patients with end-stage kidney disease (ESKD) on maintenance hemodialysis (HD). The cut-off values for low handgrip strength were < 27kg for males and < 16kg for females. The cut-off value for low lean tissue index was obtained from an age-matched healthy control group, with low lean tissue index being defined as values below the 10th percentile of the distribution of healthy subjects. The cut-off values for low quadriceps vastus intermedius thickness index were < 3.44mm/m2 for males and < 3.52mm/m2 for females. Ultrasound and bioimpedance spectroscopy were performed in 99 patients, and handgrip strength was assessed in 64 patients, all on maintenance HD. After a median follow-up of 28months (interquartile range 19-41months) 38 patients died. Lean tissue index was not associated with mortality, while low quadriceps vastus intermedius thickness index and low handgrip strength were associated with an increased hazard of death. In the fully adjusted model, only the combination of low handgrip strength and low quadriceps vastus intermedius thickness index was significantly associated with higher mortality. When combined with low handgrip strength, low quadriceps muscle US outperformed low lean tissue index as assessed by bioimpedance spectroscopy in predicting mortality in a cohort of patients on maintenance HD. Ultrasound may be a useful and convenient technique for the assessment of sarcopenia and protein-energy wasting in this patient population.

Agreement and differences between the equations for estimating muscle and bone mass using the anthropometric method in recreational strength trainees.

The interest in estimating muscle mass (MM) and bone mass (BM) has grown in the sporting arena, and more specifically in recreational strength trainees, leading to the creation of different strategies to assess them. The aims were: 1) to investigate the agreement between different MM and BM formulas, and the muscle-bone index (MBI), and to establish the differences between them, in a healthy young adult population; and 2) to analyze if there are differences between males and females in the comparison of MM, BM and MBI formulas. This study followed a descriptive cross-sectional design. A total of 130 adult active recreational strength trainees were evaluated according to the procedures described by the International Society for the Advancement in Kinanthropometry (ISAK). Estimations were made in kilograms of MM and BM by following the equations by different authors. The results showed significant differences between the values obtained by all the MM and BM formulas in the general sample (p < 0.001), and by the majority of formulas for male and female samples. In the general sample, Lin's coefficient indicated a strong agreement between Kerr, Lee, and Poortmans' MM estimation equations (concordance correlation coefficient (CCC) = 0.96-0.97). However, when stratifying by sex, this agreement persisted only in males (CCC = 0.90-0.94), in contrast with a lack of agreement observed in females (CCC < 0.90). Discrepancies in bone mass agreement were noted both in the general sample (CCC < 0.15) and when stratified by sex (CCC < 0.12). In general, differences were found between the values reported by the MM and BM formulas in recreational strength trainees, without an agreement between them. Sex was shown to significantly influence the differences found. The practical implications are that when comparing an individual with reference tables, other studies, or if analyzing an individual's evolution, the same estimation equation should be used, as they are not interchangeable.

PHASE ANGLE AS A PREDICTOR OF MUSCLE MASS IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE.

Malnutrition/sarcopenia is frequent in patients with inflammatory bowel diseases (IBD), and results in muscle catabolism, impacting treatment response, postoperative complications, and quality of life. This study aims to assess whether the phase angle (PhA) is a parameter for predicting reduced muscle mass in patients with IBD. Adult patients with IBD were included in this cross-sectional study. For the estimation of muscle mass and the calculation of the PhA, we used bioelectrical impedance analysis (BIA). Crohn's disease (CD) and ulcerative colitis (UC) activity scores were defined using the Harvey-Bradshaw index and partial Mayo score, respectively. The area under the ROC curve was calculated to identify the PhA cut-off point for reduced muscle mass. The sample consisted of 145 patients, with 39 (26.9%) with IBD in the active phase. There was a correlation of the PhA with skeletal muscle mass (SMM) (rs 0.35, P<0.001) and with the skeletal muscle mass index (SMI) (rs 0.427, P<0.001), and the associations remained in the most active form (moderate or severe) of IBD. The ROC curve analysis indicated that the cut-offs points of the PhA ≤5.042 for female and PhA ≤6.079 for male can be used to predict muscle mass reduction. The PhA can be considered a predictor of muscle mass reduction in IBD patients, and we can use it for screening and monitoring the evolution of malnutrition. • This study aims to assess whether the phase angle is a parameter for predicting reduced muscle mass in patients with inflammatory bowel disease. • There was a correlation of the phase angle with skeletal muscle mass and the associations remained in disease activity. • The ROC curve analysis indicated that the cut-off point of the PhA ≤5.042° for women and PhA ≤6,079° for men can be used to predict muscle mass reduction. • The phase angle can be considered a predictor of muscle mass reduction in inflammatory bowel disease.