Feasibility of calculating rocuronium dosage by skeletal muscle weight in patients with obesity.

This study aimed to investigate the dose-response relationship of rocuronium administered based on skeletal muscle weight and to assess the feasibility of calculating rocuronium dosage by skeletal muscle weight in short surgeries for patients with obesity. This single-center, randomized controlled clinical trial included 71 patients with obesity aged 28-70 years, with body fat percentages (PBF) >20% in men and > 28% in women, ASA status I-III, scheduled for tracheoscopy. Patients were randomly allocated into two groups: skeletal muscle group (SM group) received rocuronium based on the skeletal muscle content (1.0 mg/kg, n = 31), and the conventional administration group (conventional group) received rocuronium based on total body weight (0.45 mg/kg, n = 30). General anesthesia was administered using the same protocol. Parameters recorded included patients' general condition, muscle relaxant usage, onset time of muscle relaxants, non-response time, clinical effect time, 75% recovery time, and recovery index. Additionally, occurrences of body movement, choking, and incomplete muscle relaxation during surgery were recorded. Compared to the conventional group, the SM group required significantly less rocuronium dosage, resulting in significantly lower non-response time, clinical effect time, 75% recovery time, and recovery index (p < 0.05), and the onset time is slightly longer. Neither group experienced body movement, choking, or incomplete muscle relaxation (p > 0.05). Utilizing skeletal muscle weight to calculate rocuronium dosage in short surgeries for patients with obesity can reduce dosage, shorten recovery time, and prevent residual muscle relaxation while achieving satisfactory muscle relaxation to meet surgical requirements.

Long-Term pemafibrate treatment exhibits limited impact on body fat mass in patients with hypertriglyceridemia accompanying NAFLD.

Aim: Short-term use of pemafibrate (PEM), a selective modulator of peroxisome proliferator-activated receptor alpha, has been reported to improve abnormal liver function in patients with nonalcoholic fatty liver disease with hypertriglyceridemia (HTG-NAFLD). This study aimed to clarify the effects and predictive factors of long-term 72-week PEM administration on body composition, and laboratory tests in HTG-NAFLD patients. Methods: Fifty-three HTG-NAFLD patients receiving a 72-week PEM regimen were retrospectively enrolled. Routine blood and body composition results were analyzed immediately before and at the end of the study period. Results: PEM treatment significantly improved liver enzyme levels such as aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase, and gamma-glutamyl transferase, along with lipid profiles including triglyceride, total cholesterol, and low-density lipoprotein cholesterol. PEM did not have any detectable impact on body composition parameters. The factors of female, higher AST (≥ 46 U/L) and fat mass (≥ 31.9%), as well as lower soft lean mass (< 61.6%), skeletal muscle mass (< 36%), and skeletal muscle mass index (< 6.9 kg/m2) were significantly associated with the treatment response status of a > 30% decrease in ALT. All patients completed the treatment without any adverse effects. Conclusions: Long-term PEM treatment had a positive impact on liver enzymes and lipid profiles, but it did not result in significant changes in body composition among HTG-NAFLD patients. In predicting the response to PEM treatment, the evaluation of AST and body composition may be useful.

CT-based muscle and adipose measurements predict prognosis in patients with digestive system malignancy.

The role of skeletal muscle and adipose tissue in the progression of cancer has been gradually discussed, but it needs further exploration. The objective of this study was to provide an in-depth analysis of skeletal muscle and fat in digestive malignancies and to construct novel predictors for clinical management. This is a retrospective study that includes data from Cancer Center, the First Hospital of Jilin University. Basic characteristic information was analyzed by T tests. Correlation matrices were drawn to explore the relationship between CT-related indicators and other indicators. Cox risk regression analyses were performed to analyze the association between the overall survivals (OS) and various types of indicators. A new indicator body composition score (BCS) was then created and a time-dependent receiver operating characteristic curve was plotted to analyze the efficacy of the BCS. Finally, a nomogram was produced to develop a scored-CT system based on BCS and other indicators. C-index and calibration curve analyses were performed to validate the predictive accuracy of the scored-CT system. A total of 575 participants were enrolled in the study. Cox risk regression model revealed that VFD, L3 SMI and VFA/SFA were associated with prognosis of cancer patients. After adjustment, BCS index based on CT was significantly associated with prognosis, both in all study population and in subgroup analysis according to tumor types (all study population: HR 2.036, P < 0.001; colorectal cancer: HR 2.693, P < 0.001; hepatocellular carcinoma: HR 4.863, P < 0.001; esophageal cancer: HR 4.431, P = 0.008; pancreatic cancer: HR 1.905, P = 0.016; biliary system malignancies: HR 23.829, P = 0.035). The scored-CT system was constructed according to tumor type, stage, KPS, PG-SGA and BCS index, and it was of great predictive validity. This study identified VFD, L3 SMI and VFA/SFA associated with digestive malignancies outcomes. BCS was created and the scored-CT system was established to predict the OS of cancer patients.

Influence of ear tags on the results of body composition analysis in mice.

BACKGROUND: The aim of this study was to investigate the influence of marking methods on the outcomes of body composition analysis and provide guidance for the selection of marking methods in mouse body composition analysis. METHODS: Male C57BL/6J mice aged 6 weeks were randomly assigned for pre- and post- ear tagging measurements. The body composition of the mice was measured using a small animal body composition analyzer, which provided measurements of the mass of fat, lean, and free fluid. Then, the mass of fat, lean and free fluid to body weight ratio was gained. Further data analysis was conducted to obtain the range and coefficient of variation in body composition measurements for each mouse. The distribution of fat and lean tissue in the mice was also analyzed by comparing the fat-to-lean ratio. RESULTS: (1) The mass of all body composition components in the ear tagging group was significantly lower than that in the control group. (2) There was a significant increase in the range and coefficient of variation of body composition measurements between the ear tagging group and the control group. (3) The fat-to-lean ratio in the ear tagging group was significantly lower than that in the control group. CONCLUSIONS: Ear tagging significantly lowered the results of body composition analysis in mice and higher the results of measurement error. Therefore, ear tagging should be avoided as much as possible when conducting body composition analysis experiments in mice.

A differentiated approach to the diagnosis of overweight and obesity in children based on bioimpedance analysis of body composition.

OBJECTIVE: Aim: The current study introduces a novel diagnostic algorithm employing bioimpedance analysis to comprehensively evaluate body composition in children, assessing fat content, skeletal muscle content, and fat distribution. PATIENTS AND METHODS: Materials and Methods: Bioelectrical impedance measurements were obtained using the TANITA MC-780 MA analyzer. Indicators such as body weight, BMI, total fat content, absolute limb muscle mass, skeletal muscle strength, and waist-to-hip ratio (WHR) were assessed. A sample of 101 children aged 9 to 14 were studied using the proposed algorithm, refining BMI-based classifications. RESULTS: Results: The algorithm comprises three steps, categorizing children based on fat content, presence of sarcopenia, and central fat distribution. It identified diverse somatotypes within the groups classified by BMI. Notably, it revealed prognostically unfavorable somatotypes, such as sarcopenic obesity with central fat distribution, highlighting potential health risks. Current BMI-centric diagnoses may misclassify cardiometabolic risks, making early detection challenging. The algorithm enables a detailed evaluation, unmasking metabolically unfavorable conditions like sarcopenic obesity. The incorporation of functional tests, such as a standardized hand-grip test, enhances diagnostic accuracy. The proposed WHR indicator for characterizing fat distribution provides a practical method for determining somatotypes in children. CONCLUSION: Conclusions: This comprehensive algorithm offers an alternative to BMI-based classifications, enabling early detection of obesity and associated risks. Further validation through large-scale epidemiological studies is essential to establish correlations between somatotypes and cardiometabolic risks, fostering a more nuanced and individualized approach to pediatric obesity management.

Body mass composition analysis as a predictor of overweight and obesity in children and adolescents.

Introduction: Body mass composition is directly related to health and its disorders are correlated with diseases such as obesity, diabetes, osteoporosis and sarcopenia. The purpose of this study was to analyze body mass composition among traditional elementary school students and ballet school students. Methods: A total of 340 students participated in the study, 95 of whom attended ballet school and 245 elementary school students. A Tanita BC-418 MA analyzer was used to analyze body mass composition. Such body composition indices as BMI (Body Mass Index), muscle mass, fat mass, lean body mass and water content were evaluated. Results: The results show statistical significance for BMI between high school ballet students and elementary school ballet students, as well between high school ballet students and elementary school students. Comparisons in relation to gender and schools BMI, statistical significance was obtained for: BHSw (ballet high school women) and EBSw (elementary ballet school women), BHSw and ESw (elementary school women), BHSm (ballet high school men) and EBSm (elementary ballet school men), and between BHSm and ESw. Comparing muscle mass index (kg) between ballet high school and elementary school, between ballet high school and elementary school, and between ballet high school and elementary school - statistical significance was obtained for all comparisons. Analyzing in pairwise comparisons by gender and school achieved a statistically significant difference for: BHSw and EBSw, BHSm and EBSw, EBSw and ESm. Comparing the fat mass index (kg), no significant differences were observed between the analyzed schools and the school and gender of the children studied. The value of the lean body mass index differed significantly between groups by school and gender. Comparing the water content index, statistically significant differences were obtained for school and gender. Discussion: The body mass composition of ballet school students differs from that of standard school students.

The Relationship Between Anti-Müllerian Hormone and Body Composition Components in Patients With Polycystic Ovary Syndrome of Reproductive Age.

To investigate and analyze the relationship between body composition components, including Body Mass Index (BMI), body fat percentage, waist-to-hip ratio, and visceral fat index, and Anti-Müllerian Hormone (AMH) levels in patients diagnosed with Polycystic Ovary Syndrome (PCOS), The study aims to provide a comprehensive understanding of how various aspects of body composition impact AMH levels. This study enrolled 167 women with PCOS of reproductive age. Serum AMH level and body composition were measured, and the correlation between body composition elements and AMH levels was analyzed. AMH level was negatively correlated with body weight, BMI, fat-free mass, body fat percentage, waist-hip ratio, and visceral fat level (P < 0.01). And negatively correlated with skeletal muscle ratio ( P = 0.003). AMH level remained significantly associated with BMI ( P = 0.028), body fat percentage ( P = 0.040), waist-hip ratio (P = 0.003), and visceral fat level ( P = 0.040) after age was included and a multiple linear regression model was established. After adjusting for age, BMI was still significantly associated with AMH (P = 0.029). At the same time, there was no obvious linear correlation between BSA and AMH. The results showed that AMH levels were significantly different among the three groups (9.53 ± 5.12 vs 6.98 ± 3.35 vs 6.38 ± 3.38, P < 0.001; ng/mL). The level of AMH in the non-central obesity group was higher than that in the central obesity group (9.68 ± 5.22vs7.09 ± 3.83, P < 0.001; ng/mL). In PCOS patients, those who are more obese have lower AMH levels, indicating poorer Ovarian Reserve. BMI may independently affect AMH levels, apart from age, BSA, and other factors. Ovarian function in centrally obese patients is poorer than in those with non-central obesity.

Explore the effect of pressure and time of compression on the risk of intraoperatively acquired pressure injury based on theoretical framework: A prospective study.

Surgery is a high risk factor for the occurrence of pressure injury (PI). On the basis of theoretical research, pressure and duration of pressure are key factors affecting PI. Pressure is affected by the individual pressure redistribution capacity. So our study aims to explore how the surgery time and pressure intensity affect the occurrence of PI and what are the risk factors. A prospective study. A total of 250 patients who underwent elective surgery in a grade-A general hospital from November 2021 to February 2023 were selected and divided into a group of 77 patients with IAPI (intraoperatively acquired pressure injury) and a group of 173 patients with no IAPI. Visual pressure inductive feedback system and body composition analysis technology were used to record the local pressure value and change of patients before and after anaesthesia. Relevant data of the patients were collected to explore the influencing factors. The maximum pressure and average pressure at the pressure site of the same patient changed before and after anaesthesia, and the pressure after anaesthesia was significantly higher than that before anaesthesia. There was no statistical difference in the average pressure after anaesthesia (p > 0.05), but the maximum pressure in the IAPI group was higher than that in the non-occurrence group (p < 0.05). The average pressure multiplied by the operation time in IAPI group is significantly higher than that in the non-IAPI group (p < 0.01). Multiple linear regression analysis (stepwise regression) showed that fat-free weight, age, waist circumference, body mass index (BMI) and gender were taken as independent variables into the regression model, affecting the maximum pressure. In addition, operation time ≥4 h may be a high risk factor for IAPI. In future studies, more objective research tools can be applied to improve the accuracy of predicting the risk of IAPI. In addition to gender and BMI, follow-up studies may consider including measures such as waist circumference and fat-free body weight in IAPI risk assessment to guide the clinical nursing work more scientifically.

Waistline to thigh circumference ratio as a predictor of MAFLD: a health care worker study with 2-year follow-up.

BACKGROUND: This study aimed to determine whether the waist-to-thigh ratio (WTTR) is associated with the incidence of metabolic-associated fatty liver disease (MAFLD) in health care workers. METHODS: There were 4517 health care workers with baseline data and results from 2 follow-up examinations. We divided the subjects into 3 groups according to baseline WTTR and used the Cox hazard regression model to estimate MAFLD risk. RESULTS: The WTTRs were categorized by tertiles at baseline using the values 1.58 and 1.66. Patients with higher WTTR tended to have significantly greater values for the following factors, body mass index (BMI), fasting blood glucose (FPG), systolic blood pressure, diastolic blood pressure, total cholesterol (TC), triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C) and neck circumference. The incidence of MAFLD significantly increased with increasing WTTR tertiles (5.74%, 12.75% and 22.25% for the first, second and third tertiles, respectively, P < 0.05 for trend). Kaplan-Meier(K-M) survival analysis revealed a significant tendency towards increased MAFLD risk with increasing WTTR tertile. In the fully adjusted model, the hazard ratios (95% CIs) for MAFLD in the second, third WTTR tertiles compared with the first quartile were 2.17(1.58,2.98), 3.63(2.70,4.89), respectively, third neck circumference tertiles compared with the first quartile were 2.84(1.89,4.25), 8.95(6.00,13.35), respectively. Compared with those of individuals with a BMI > 23 kg/m2, the associations between WTTR and MAFLD incidence were more pronounced in subjects with a BMI < 23 kg/m2. Similarly, the difference in neck circumference was more pronounced in these patients with a BMI < 23 kg/m2. CONCLUSIONS: Our results revealed that the WTTR is an independent risk factor for MAFLD, and there was a dose‒response relationship between the WTTR and MAFLD risk. The neck circumference was significantly different in subjects with a BMI < 23 kg/m2. This approach provides a new way to predict the incidence rate of MAFLD.

Longitudinal changes in bone mineral density may be associated with long-term survival in patients with cirrhosis: A proof of concept of study.

INTRODUCTION: The impact of longitudinal changes in different body components measured via body composition analysis (BCA) on liver-related outcomes in patients with cirrhosis is poorly understood. We evaluated the prognostic relevance of longitudinal changes in body composition over one year in patients with cirrhosis. METHODS: This was a follow-up study of a randomized controlled trial evaluating changes in bone density measured via dual energy X-ray absorptiometry (DEXA) upon vitamin D supplementation. Patients with available anthropometric indices, fat mass (FM), fat-free mass (FFM), bone-density at lumbar spine (LD) and left femur-neck (FD) (assessed by T score) at two time points one year apart were assessed for outcomes. The prognostic relevance of change in parameters such as ΔFM, ΔFFM, ΔLD and ΔFD over one year was assessed and compared with baseline model for end-stage liver disease (MELD) score. RESULTS: Patients with cirrhosis (n=112) (mean age 41.8±12 years, 58.5% males) were followed up for median duration of 5.7 years interquartile range [IQR 3.5-5.7], with five-year survival rate of 77%. On serial BCA, ΔLD (p=0.029) and ΔFD (p=0.003) emerged as significant predictors of survival, whereas ΔFM (p=0.479), ΔFFM (p=0.245) and ΔBMI (p=0.949) were not. The area under curve of ΔLD and MELD score for predicting survival was 0.636 (0.5-0.773) and 0.664 (0.555-0.773), respectively. ΔFD<0.1 over one year had sensitivity and specificity of 70.4% and 56.5% to predict poor survival. The combination of ΔFD, MELD and ascites predicted five-year survival with an optimism-corrected c-statistic of 0.785. CONCLUSION: Among body composition parameters, changes in bone mineral density correlate best with survival and have prognostic relevance similar to that of ascites and MELD score.

Nutrition to Enhance Metabolic-Bariatric Surgery Outcomes.

BACKGROUND: Gender-specific post-surgical goals for 12-month percent body fat (%BF) based on World Health Organization (WHO) obesity thresholds and for lean mass-sparing were published as preliminary body composition (BC) guidelines to address a knowledge gap in metabolic-bariatric surgery (MBS). Other studies' %BF outcomes inconsistently fell below obesity thresholds; none described nutrition practices. To help practitioners positively influence patients' BC and weight changes, this study describes the team-supported process of conducting serial body composition analysis (sBCA) concomitantly with the evidence-based nutrition practices applied to generate the preliminary guidelines. METHODS: Guidelines were generated using the cumulative outcomes of separate, original research board-approved Roux-en-Y Gastric Bypass and Sleeve Gastrectomy studies. One dietitian assessed BC using the same bioimpedance machine, educated patients, and collected data from patients aged 18 and older in a 532-bed nonprofit acute-care institution in Northeast Ohio, USA, from May, 2007, through November, 2016. Essential to pre- and postoperative education was the "Nutrition Goal Checklist," an evidence-based synopsis of imperative practices. Body composition was assessed on initial visit, presurgically, and postoperative months 3, 6, and 12, generating individual patient handouts of progressive weight and BC changes with coordinating %BF graphs. Serial assessment enabled intervention toward meeting BC goals. RESULTS: For genders in both surgeries, the described process influenced highly significant fat mass reduction, transitioning %BF below obesity thresholds. Lean mass-sparing outcomes supported the suggested preliminary guidelines. CONCLUSIONS: Utilizing sBCA with evidence-based nutrition practices consistently generated outcomes to formulate preliminary BC guidelines following MBS. Further research is needed to solidify formal guidelines.

Prognostic value of initial and longitudinal changes in body composition in metastatic pancreatic cancer.

BACKGROUND: Sarcopenia or visceral adipose tissue has been reported to be related to pancreatic cancer prognosis. However, clinical relevance of the comprehensive analysis of body compositions and their longitudinal changes is lacking. This study analysed the association between body composition changes after chemotherapy and survival in patients with metastatic pancreatic cancer. METHODS: We retrospectively included 456 patients (mean age ± standard deviation, 61.2 ± 10.0 years; 272 males and 184 females) with metastatic pancreatic cancer who received palliative chemotherapy from May 2011 to December 2019. Using deep learning-based, fully automated segmentation of contrast-enhanced computed tomography (CT) at the time of diagnosis, cross-sectional areas of muscle, subcutaneous adipose tissue and visceral adipose tissue were extracted from a single axial image of the portal venous phase at L3 level. Skeletal muscle index (SMI), visceral adipose tissue index (VATI), subcutaneous adipose tissue index (SATI) and mean skeletal muscle attenuation (MA) were calculated, and their effect on overall survival (OS) was analysed. Longitudinal changes in body composition and prognostic values were also analysed in a subgroup of patients with 2- and 6-month follow-up CT (n = 349). RESULTS: A total of 452 deaths occurred during follow-up in the entire cohort. The survival rate was 49.3% (95% confidence interval [CI], 44.9-54.2) at 1 year and 3.7% (95% CI, 2.0-6.8) at 5 years. In multivariable analysis, higher MA (≥44.4 HU in males and ≥34.8 HU in females) at initial CT was significantly associated with better OS in both males and females (adjusted hazard ratio [HR], 0.706; 95% CI, 0.538-0.925; P = 0.012 for males, and HR, 0.656; 95% CI, 0.475-0.906; P = 0.010 for females), whereas higher SATI (≥42.8 cm2/m2 in males and ≥65.8 cm2/m2 in females) was significantly associated with better OS in female patients only (adjusted HR, 0.568; 95% CI, 0.388-0.830; P = 0.003). In longitudinal analysis, SMI, VATI and SATI significantly decreased between initial and 2-month follow-up CT, whereas mean MA significantly decreased between 2- and 6-month follow-up CT. In multivariable Cox regression analysis of longitudinal changes, which was stratified by disease control state, SATI change was significantly associated with OS in male patients (adjusted HR, 0.513; 95% CI, 0.354-0.745; P < 0.001), while other body composition parameters were not. CONCLUSIONS: In patients with metastatic pancreatic cancer, body composition mostly changed during the first 2 months after starting chemotherapy, and the prognostic factors associated with OS differed between males and females. Initial and longitudinal changes of body composition are associated with OS of metastatic pancreatic cancer.

Body composition analysis: A snapshot across the perimenopause.

During the perimenopause, estrogen concentrations gradually decrease, and this is associated with changes to women's energy expenditure and intake. These changes result in weight gain and altered body fat distribution, with increased abdominal fat deposition and cardiometabolic risk via insulin resistance. Body composition analysis is a useful clinical tool in outpatient settings, as it is simple, not expensive and provides information on body mass index, skeletal mass, fat mass, fat percentage and basal metabolic rate. This review discusses body composition analysis as part of a health assessment for healthy women during the perimenopause and investigates the associations between body composition and cardiometabolic profile.

GA-Net: A geographical attention neural network for the segmentation of body torso tissue composition.

PURPOSE: Body composition analysis (BCA) of the body torso plays a vital role in the study of physical health and pathology and provides biomarkers that facilitate the diagnosis and treatment of many diseases, such as type 2 diabetes mellitus, cardiovascular disease, obstructive sleep apnea, and osteoarthritis. In this work, we propose a body composition tissue segmentation method that can automatically delineate those key tissues, including subcutaneous adipose tissue, skeleton, skeletal muscle tissue, and visceral adipose tissue, on positron emission tomography/computed tomography scans of the body torso. METHODS: To provide appropriate and precise semantic and spatial information that is strongly related to body composition tissues for the deep neural network, first we introduce a new concept of the body area and integrate it into our proposed segmentation network called Geographical Attention Network (GA-Net). The body areas are defined following anatomical principles such that the whole body torso region is partitioned into three non-overlapping body areas. Each body composition tissue of interest is fully contained in exactly one specific minimal body area. Secondly, the proposed GA-Net has a novel dual-decoder schema that is composed of a tissue decoder and an area decoder. The tissue decoder segments the body composition tissues, while the area decoder segments the body areas as an auxiliary task. The features of body areas and body composition tissues are fused through a soft attention mechanism to gain geographical attention relevant to the body tissues. Thirdly, we propose a body composition tissue annotation approach that takes the body area labels as the region of interest, which significantly improves the reproducibility, precision, and efficiency of delineating body composition tissues. RESULTS: Our evaluations on 50 low-dose unenhanced CT images indicate that GA-Net outperforms other architectures statistically significantly based on the Dice metric. GA-Net also shows improvements for the 95% Hausdorff Distance metric in most comparisons. Notably, GA-Net exhibits more sensitivity to subtle boundary information and produces more reliable and robust predictions for such structures, which are the most challenging parts to manually mend in practice, with potentially significant time-savings in the post hoc correction of these subtle boundary placement errors. Due to the prior knowledge provided from body areas, GA-Net achieves competitive performance with less training data. Our extension of the dual-decoder schema to TransUNet and 3D U-Net demonstrates that the new schema significantly improves the performance of these classical neural networks as well. Heatmaps obtained from attention gate layers further illustrate the geographical guidance function of body areas for identifying body tissues. CONCLUSIONS: (i) Prior anatomic knowledge supplied in the form of appropriately designed anatomic container objects significantly improves the segmentation of bodily tissues. (ii) Of particular note are the improvements achieved in the delineation of subtle boundary features which otherwise would take much effort for manual correction. (iii) The method can be easily extended to existing networks to improve their accuracy for this application.

The Effects of a Cinchona Supplementation on Satiety, Weight Loss and Body Composition in a Population of Overweight/Obese Adults: A Controlled Randomized Study.

Obesity is a risk factor for several diseases present worldwide. Currently, dietary changes and physical activity are considered the most effective treatment to reduce obesity and its associated comorbidities. To promote weight loss, hypocaloric diets can be supported by nutraceuticals. The aim of this study was to evaluate the effects of a hypocaloric diet associated with Cinchona succirubra supplementation on satiety, body weight and body composition in obese subjects. Fifty-nine overweight/obese adults, were recruited, randomized into two groups and treated for 2 months. The first group (32 adults) was treated with a hypocaloric diet plus cinchona supplementation (the T-group); the second one (27 adults) was treated with a hypocaloric diet plus a placebo supplementation (the P-group). Anthropometric-measurements as well as bioimpedance analysis, a Zung test and biochemical parameters were evaluated at baseline and after 60 days. T-group adults showed significant improvement in nutritional status and body composition compared to those at the baseline and in the P-group. Moreover, T-group adults did not show a reduction in Cholecystokinin serum levels compared to those of P-group adults. In conclusion, our data demonstrate that a hypocaloric diet associated with cinchona supplementation is effective in inducing more significant weight loss and the re-establishment of metabolic parameters than those obtained with a hypocaloric diet.

Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients.

OBJECTIVES: SARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool. MATERIALS: BCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off. RESULTS: Intermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%, p < 0.001) and maximum muscle decay of 5.48% (vs. 3.66%, p = 0.039) per day in non-survivors. The first available decay rate did not significantly differ between survival groups but showed significant associations with survival in Cox regression (p = 0.011). In ROC analysis, PMA loss averaged over the stay had the greatest discriminatory power (AUC = 0.777) for survival. A long-term PMA decline per day of 1.84% was defined as a threshold; muscle loss beyond this cut-off proved to be a significant BCA-derived predictor of mortality. CONCLUSION: Muscle wasting in critically ill COVID-19 patients is severe and correlates with survival. Intermittent BCA derived from clinically indicated CT scans proved to be a valuable monitoring tool, which allows identification of individuals at risk for adverse outcomes and has great potential to support critical care decision-making.

An analysis of phase angle and standard phase angle cut-off values and their association with survival in head and neck cancer patients undergoing radiotherapy.

OBJECTIVE: The objective of this study is to identify the cutoff values for phase angle (PA) and standard phase angle (SPA) parameters, as determined by bioelectrical impedance analysis (BIA), for predicting malnutrition and investigating their association with overall survival in head and neck cancer (HNC) patients undergoing radiotherapy. METHODS: In this study, nutritional assessment and follow-up of HNC patients undergoing radiotherapy (RT) between November 2017 and September 2022 were assessed. Nutritional assessment, body composition (BC), and PA results obtained from BIA (Tanita MC-980) were retrospectively evaluated. Statistical Package for Social Sciences (SPSS) version 25.0 (IBM Corp., Armonk, NY, USA) was used for statistical analysis. The results were evaluated at a confidence interval of 95% and a significance level of p ≤ 0.05. RESULTS: A total of 53 patients, including 37 (70%) men and 16 (30%) women, with a median age of 60 (23-87 years) were included. The median follow-up time was 51 (range 24-59) months. The mean PA of the patients was calculated as 4.99° (±0.92, 95% CI: 4.74-5.25). The PA of patients with malnutrition (4.66° ± 0.87) was lower than that of well-nourished patients (5.71° ± 0.56) (p < 0.001). As a result of the ROC analysis based on this finding, the ideal PA cut-off point for determining the presence of malnutrition was found to be 5.65, with a sensitivity of 85%, specificity of 79%, accuracy of 83%, and a model discrimination power of excellent level (AUC: 85%, p < 0.001). The median overall survival time of the patients was calculated as 51 months (24-59 months). The mortality rate during the follow-up period was 13%, while the 1-, 3-, and 5-year overall survival rates of the patients were 96.1%, 89.3%, and 86.8%, respectively. Patients with SPA values less than -1.65 had a 5-year overall survival rate of 77.4%, while those with SPA values greater than or equal to -1.65 had a 5-year overall survival rate of 100% (p = 0.030) CONCLUSION: Our study recommends using PA and SPA as standard criteria for detecting malnutrition in HNC patients undergoing RT, with cut-off points of 5.65 and -1.65 respectively, to prevent treatment interruptions and improve outcomes. Further research is needed to validate the SPA cut-off value and its relationship with clinical outcomes, as SPA may be a more effective predictor of malnutrition and overall survival than PA alone.

The relationship between computed tomography-derived body composition, systemic inflammation, and survival in patients with abdominal aortic aneurysm.

OBJECTIVE: Patient selection and risk stratification for elective repair of abdominal aortic aneurysm (AAA), either by open surgical repair or by endovascular aneurysm repair, remain challenging. Computed tomography (CT)-derived body composition analysis (CT-BC) and systemic inflammation-based scoring systems such as the systemic inflammatory grade (SIG) appear to offer prognostic value in patients with AAA undergoing endovascular aneurysm repair. The relationship between CT-BC, systemic inflammation, and prognosis has been explored in patients with cancer, but data in noncancer populations are lacking. The present study aimed to examine the relationship between CT-BC, SIG, and survival in patients undergoing elective intervention for AAA. METHODS: A total of 611 consecutive patients who underwent elective intervention for AAA at three large tertiary referral centers were retrospectively recruited for inclusion into the study. CT-BC was performed and analyzed using the CT-derived sarcopenia score (CT-SS). Subcutaneous and visceral fat indices were also recorded. SIG was calculated from preoperative blood tests. The outcomes of interest were overall and 5-year mortality. RESULTS: Median (interquartile range) follow-up was 67.0 (32) months, and there were 194 (32%) deaths during the follow-up period. There were 122 (20%) open surgical repair cases, 558 (91%) patients were male, and the median (interquartile range) age was 73.0 (11.0) years. Age (hazard ratio [HR]: 1.66, 95% confidence interval [CI]: 1.28-2.14, P < .001), elevated CT-SS (HR: 1.58, 95% CI: 1.28-1.94, P < .001), and elevated SIG (HR: 1.29, 95% CI: 1.07-1.55, P < .01) were independently associated with increased hazard of mortality. Mean (95% CI) survival in the CT-SS 0 and SIG 0 subgroup was 92.6 (84.8-100.4) months compared with 44.9 (30.6-59.2) months in the CT-SS 2 and SIG ≥2 subgroup (P < .001). Patients with CT-SS 0 and SIG 0 had 90% (standard error: 4%) 5-year survival compared with 34% (standard error: 9%) in patients with CT-SS 2 and SIG ≥2 (P < .001). CONCLUSIONS: Combining measures of radiological sarcopenia and the systemic inflammatory response offers prognostic value in patients undergoing elective intervention for AAA and may contribute to future clinical risk predication strategies.

A Deep Learning Based Geographic Attention Model for Body Composition Tissue Segmentation.

Measurement of body composition, including multiple types of adipose tissue, skeletal tissue, and skeletal muscle, on computed tomography (CT) images is practical given the powerful anatomical structure visualization ability of CT, and is useful for clinical and research applications related to health care and underlying pathology. In recent years, deep learning-based methods have contributed significantly to the development of automatic body composition analysis (BCA). However, the unsatisfactory segmentation performance for indistinguishable boundaries of multiple body composition tissues and the need for large-scale datasets for training deep neural networks still need to be addressed. This paper proposes a deep learning-based approach, called Geographic Attention Network (GA-Net), for body composition tissue segmentation on body torso positron emission tomography/computed tomography (PET/CT) images which leverages the body area information. The representation ability of GA-Net is significantly enhanced with the body area information as it strongly correlates with the target body composition tissue. This method achieves precise segmentation performance for multiple body composition tissues, especially for boundaries that are hard to distinguish, and effectively reduces the data requirements for training the network. We evaluate the proposed model on a dataset that includes 50 body torso PET/CT scans for segmenting 4 key bodily tissues - subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), skeletal muscle tissue (SMT), and skeleton (Sk). Experiments show that our proposed method increases segmentation accuracy, especially with a limited training dataset, by providing geographic information of target body composition tissues.