Effect of Laparoscopic Cholecystectomy on 25- Hydroxyvitamin D Levels and Bone Mineral Density in Post Menopausal Women.

Background Laparoscopic cholecystectomy (LC) is the gold standard management for benign gallbladder diseases. It has been observed that there is alteration in vitamin D levels and bone mineral density after cholecystectomy due to altered enterohepatic circulation.With increase in average age expectancy of the population, low levels of vitamin D levels and osteoporosis after cholecystectomies might cause increased health care burden.Methods A prospective observational study was planned between 1st Jan 2022 to 30th Jun 2023 in the Department of General Surgery at PGIMER Chandigarh, a tertiary care hospital in north India. One hundred and three post-menopausal women who underwent LC and met the inclusion and exclusion criteria were included in the study. All participants underwent estimation of vitamin D and bone mineral density preoperatively and 3rdpost operative month (POM).Results The mean age of the patients was58.46 ± 7.44. Pain abdomen was present in 68(66%) patients, 18 had epigastric discomfort and 17 had dyspepsia. The mean levels of vit D decreased from21.92 at the baseline to 20.12 at 3rd POM(P < 0.001). There was significant change in t score Femoral Neck (-1.12 vs -1.15, P < 0.001) andLumbar spine L1-L4 -1.98 vs-1.98 (P = 0.033). z-Scores of the Femoral Neck were -0.34 vs -0.54 (p < 0.001) and of Lumbar spine L1-L4 were -0.95 vs 1.02 (P < 0.001). The decrease in fracture risk for the femoral neck(p= 0.344) and the lumbar spine (P = 0.223) were not statistically significant.Conclusion There is significant decrease in vitamin D and BMD level after LC in post-menopausal females.

Brazil nut-enriched diet modulates bone mineral density and body composition in an experimental model of chronic kidney disease.

OBJECTIVE: This study investigates the effects of a Brazil nut-enriched diet on body composition and bone parameters in CKD animal model. METHODS: Male Wistar rats were assigned to the following groups: Sham (n=8), Nx (n=6), nephrectomized rats, and NxBN (n=6), nephrectomized rats and an enricheddiet with 5% Brazil nut. Body composition parameters were obtained by dual-energy X- ray absorptiometry (DXA). Bioclin kits determined plasmatic calcium. The femurs werecollected to determine absolute mass and length, bone mineral density, and biomechanical tests. RESULTS: The NxBN group exhibited a higher total body bone mineral density (BMD) value than the Nx group (0.177±0.004g/cm2vs 0,169±0.003g/cm2; p=0.0397). No significant differences were observed regarding absolute mass, length, BMD, and biomechanical parameters in the femurs of the groups. Moreover, no significant differences were found in plasmatic calcium levels among the groups. CONCLUSIONS: Brazil-nut enriched diet modulated BMD in CKD experimental model, and further studies are demanded to understand the pathways involved in this finding.

Comparison of body composition measures assessed by bioelectrical impedance analysis versus dual-energy X-ray absorptiometry in the United Kingdom Biobank.

BACKGROUND: Bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) serves as common modalities for body composition assessment. This study was aimed to evaluate the agreement between BIA and DXA measures in UK Biobank. METHODS: UK Biobank participants with body fat mass (FM) and fat-free mass (FFM) estimates obtained through BIA (Tanita BC418MA) and DXA concurrently were included. Correlation between BIA and DXA-derived estimates were assessed with Lin's concordance correlation coefficients. Bland-Altman and Passing-Boblok analyses were performed to quantify the difference and agreement between BIA and DXA. Multivariable linear regression was used to identify predictors influencing the differences. Finally, prediction models were developed to calibrate BIA measures against DXA. RESULTS: The analysis included 34437 participants (female 51.4%, mean age 64.1 years at imaging assessment). BIA and DXA measurements were highly correlated (Lin's concordance correlation coefficient 0.94 for FM and 0.94 for FFM). BIA (Tanita BC418MA) underestimates FM overall by 1.84 kg (23.77 vs. 25.61, p < 0.01), and overestimated FFM overall by 2.56 kg (52.49 vs. 49.93, p < 0.01). The BIA-DXA differences were associated with FM, FFM, BMI and waist circumference. The developed prediction models showed overall good performance in calibrating BIA data. CONCLUSION: Our analysis exhibited strong correlation between BIA (Tanita BC418MA)- and DXA-derived body composition measures at a population level in UK Biobank. However, the BIA-DXA differences were observed at individual level and associated with individual anthropometric measures. Future studies may explore the use of prediction models to enhance the calibration of BIA measures for more accurate assessments in UK Biobank.

Exploring the Impact of Noise and Image Quality on Deep Learning Performance in DXA Images.

BACKGROUND AND OBJECTIVE: Segmentation of the femur in Dual-Energy X-ray (DXA) images poses challenges due to reduced contrast, noise, bone shape variations, and inconsistent X-ray beam penetration. In this study, we investigate the relationship between noise and certain deep learning (DL) techniques for semantic segmentation of the femur to enhance segmentation and bone mineral density (BMD) accuracy by incorporating noise reduction methods into DL models. METHODS: Convolutional neural network (CNN)-based models were employed to segment femurs in DXA images and evaluate the effects of noise reduction filters on segmentation accuracy and their effect on BMD calculation. Various noise reduction techniques were integrated into DL-based models to enhance image quality before training. We assessed the performance of the fully convolutional neural network (FCNN) in comparison to noise reduction algorithms and manual segmentation methods. RESULTS: Our study demonstrated that the FCNN outperformed noise reduction algorithms in enhancing segmentation accuracy and enabling precise calculation of BMD. The FCNN-based segmentation approach achieved a segmentation accuracy of 98.84% and a correlation coefficient of 0.9928 for BMD measurements, indicating its effectiveness in the clinical diagnosis of osteoporosis. CONCLUSIONS: In conclusion, integrating noise reduction techniques into DL-based models significantly improves femur segmentation accuracy in DXA images. The FCNN model, in particular, shows promising results in enhancing BMD calculation and clinical diagnosis of osteoporosis. These findings highlight the potential of DL techniques in addressing segmentation challenges and improving diagnostic accuracy in medical imaging.

Ectopic fat in muscle and poor glycemic control are negatively associated with trabecular bone score in type 2 diabetes.

INTRODUCTION: Type 2 Diabetes (T2D) is associated with fractures, despite preserved Bone Mineral Density (BMD). This study aimed to evaluate the relationship between BMD and trabecular bone score (TBS) with the reallocation of fat within muscle in individuals with eutrophy, obesity, and T2D. METHODS: The subjects were divided into three groups: eutrophic controls paired by age and sex with the T2D group (n = 23), controls diagnosed with obesity paired by age, sex, and body mass index with the T2D group (n = 27), and the T2D group (n = 29). BMD and body fat percentage were determined using dual-energy X-Ray absorptiometry. TBS was determined using TBS iNsight software. Intra and extramyocellular lipids in the soleus were measured using proton magnetic resonance spectroscopy. RESULTS: TBS was lower in the T2D group than in the other two groups. Glycated hemoglobin (A1c) was negatively associated with TBS. Body fat percentage was negatively associated with TBS and Total Hip (TH) BMD. TH BMD was positively associated with intramuscular lipids. A trend of negative association was observed between intramuscular lipids and TBS. CONCLUSION: This study showed for the first time that the reallocation of lipids within muscle has a negative association with TBS. Moreover, these results are consistent with previous studies showing a negative association between a parameter related to insulin resistance (intramuscular lipids) and TBS.

Differential impacts of fat and muscle mass on cardiovascular and non-cardiovascular mortality in individuals with type 2 diabetes.

BACKGROUND: The distribution of fat and muscle mass in different regions of the body can reflect different pathways to mortality in individuals with diabetes. Therefore, we investigated the associations between whole-body and regional body fat and muscle mass with cardiovascular disease (CVD) and non-CVD mortality in type 2 diabetes (T2D). METHODS: Within the National Health and Nutrition Examination Survey 1999-2006, 1417 adults aged ≥50 years with T2D were selected. Dual-energy X-ray absorptiometry was used to derive whole-body, trunk, arm, and leg fat mass and muscle mass indices (FMI and MMI). Mortality data until 31 December 2019 were retrieved from the National Death Index. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated from Cox proportional hazard models. RESULTS: A total of 1417 participants were included in this study (weighted mean age [standard error]: 63.7 [0.3] years; 50.5% female). Over a median follow-up of 13.6 years, 797 deaths were recorded (371 CVD-related and 426 non-CVD deaths). Higher FMI in the arm was associated with increased risk of non-CVD mortality (fourth quartile [Q4] vs. first quartile [Q1]: HR 1.82 [95% CI 1.13-2.94]), whereas higher FMI in the trunk or leg was not significantly associated with CVD or non-CVD mortality. Conversely, higher arm MMI was associated with a lower risk of both CVD (Q4 vs. Q1: HR 0.51 [95% CI 0.33-0.81]) and non-CVD (Q4 vs. Q1: HR 0.56 [95% CI 0.33-0.94]) mortality. There was a significant interaction between smoking status and arm FMI on non-CVD mortality (P for interaction = 0.007). Higher arm FMI was associated with a higher risk of non-CVD mortality among current or former smokers (Q4 vs. Q1: HR 2.67 [95% CI 1.46-4.88]) but not non-smokers (Q4 vs. Q1: HR 0.85 [95% CI 0.49-1.47]). CONCLUSIONS: Fat mass and muscle mass, especially in the arm, are differently associated with CVD and non-CVD mortality in people with T2D. Our findings underscore the predictive value of body compositions in the arm in forecasting mortality among older adults with T2D.

Regional variation in bone mineral density of the distal radius.

Objectives: This study investigates the regional variation in areal bone mineral density (aBMD) at the distal radius, a critical site for osteoporosis-related fractures. Understanding aBMD distribution is essential for accurate diagnosis and management of osteoporosis. Methods: The study involved 261 participants aged over 50. Using dual-energy X-ray absorptiometry (DXA) scans, aBMD was recorded across contiguous regions of the distal radius. Factors considered include age, sex, and hand dominance, providing a comprehensive view of aBMD distribution. Results: The findings indicated a consistent pattern in aBMD distribution along the radius, with a plateau around the one-third distance from the wrist. Notably, significant differences in aBMD were observed between age groups, especially among post-menopausal women. The study also recorded minor variations in aBMD between dominant and non-dominant forearms. Conclusions: The study's insights into aBMD variation at the distal radius have implications for osteoporosis research and clinical diagnosis. It highlights the importance of standardized region of interest placement in DXA scans for accurate assessment.

A Novel MRI-Based Paravertebral Muscle Quality (PVMQ) Score for Evaluating Muscle Quality and Bone Quality: A Comparative Study with the VBQ Score.

Purpose: This study aims to develop a novel MRI-based paravertebral muscle quality (PVMQ) score for assessing muscle quality and to investigate its correlation with the degree of fat infiltration (DFF) and the vertebral bone quality (VBQ) score of paravertebral muscles. Additionally, the study compares the effectiveness of the PVMQ score and the VBQ score in assessing muscle quality and bone quality. Methods: PVMQ scores were derived from the ratio of paravertebral muscle signal intensity (SI) to L3 cerebrospinal fluid SI on T2-weighted MRI. Image J software assessed paravertebral muscle cross-sectional area (CSA) and DFF. Spearman rank correlation analyses explored associations between PVMQ, VBQ scores, DFF, and T-scores in both genders. Receiver operating characteristic (ROC) curves compared PVMQ and VBQ scores' effectiveness in distinguishing osteopenia/osteoporosis and high paraspinal muscle DFF. Results: In this study of 144 patients (94 females), PVMQ scores were significantly higher in osteoporosis and osteopenia groups compared to normals, with variations observed between genders (P < 0.05). PVMQ showed stronger positive correlation with VBQ scores and DFF in females than males (0.584 vs 0.445, 0.579 vs 0.528; P < 0.01). ROC analysis favored PVMQ over VBQ for low muscle mass in both genders (AUC = 0.767 vs 0.718, 0.793 vs 0.718). VBQ was better for bone mass in males (0.737/0.865 vs 0.691/0.858), whereas PVMQ excelled for females (0.808/0.764 vs 0.721/0.718). Conclusion: The novel PVMQ score provides a reliable assessment of paravertebral muscle quality and shows a strong correlation with VBQ scores and DFF, particularly in females. It outperforms VBQ scores in evaluating muscle mass and offers valuable insights for assessing bone mass in females. These findings underscore the potential of the PVMQ score as a dual-purpose tool for evaluating both muscle and bone health, informing future research and clinical practice.

Effects of daily probiotic supplementation with Lactobacillus acidophilus on calcium status, bone metabolism biomarkers, and bone mineral density in postmenopausal women: a controlled and randomized clinical study.

Background: Menopause poses significant health risks for women, particularly an increased vulnerability to fractures associated with osteoporosis. Dietary interventions have emerged as promising strategies, focusing on mitigating the risk of osteoporosis rather than solely addressing the established disease. This 12-week randomized controlled trial aimed to analyze the effects of consuming Lactobacillus acidophilus probiotics on calcium levels, biomarkers of bone metabolism, and bone mineral density (BMD) profiles in postmenopausal women. Methods: Fifty-five participants were randomly assigned to receive either a placebo (n = 25) or the probiotic L. acidophilus UALa-01™ (n = 30) daily via oral intervention. Throughout the study, evaluations included body composition, blood biochemical parameters, serum calcium levels, and biomarkers of bone metabolism. Additionally, Dual-energy X-ray absorptiometry was used to measure BMD profiles. Results: The findings delineated that the probiotic group experienced a decrease in serum calcium levels compared to their initial levels. However, hair calcium levels and biomarkers related to bone metabolism showed no notable changes within this group. Consumption of probiotic L. acidophilus also seemed to prevent fluctuations in bone turnover markers. Moreover, there were no significant alterations in BMD levels at the lumbar spine, left femur, and total body in the probiotic group. Additionally, probiotic intake led to favorable outcomes by significantly reducing both body fat and visceral fat during the intervention period. Conversely, an adverse effect of consuming probiotic L. acidophilus was observed with a significant increase in glucose concentration. Conclusion: In conclusion, the consumption of L. acidophilus probiotics daily for 12 weeks among postmenopausal women does not affect the profile of BMD, but it may help in stabilizing bone turnover. It is important to note that most measured parameters were within the normal range for this population. However, it is worth noting that 3 months of probiotic supplementation could potentially disrupt calcium and glucose status in postmenopausal women.

Practical but Inaccurate? A-Mode Ultrasound and Bioelectrical Impedance Underestimate Body Fat Percentage Compared to Dual-Energy X-ray Absorptiometry in Male College Students.

Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, the agreement of these devices with the gold-standard method still requires investigation. The aim was to analyze the agreement between a gold-standard %BF assessment method with BIA and US devices. Twenty-three men (aged 30.1 ± 7.7 years, weighing 82.5 ± 14.9 kg, 1.77 ± 0.05 m tall) underwent dual-energy X-ray absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessments. Pearson and concordance correlations were analyzed. A T-test was used to compare the means of the methods, and Bland-Altman plots analyzed agreement and proportional bias. Alpha was set at <0.05. The Pearson coefficients of BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p < 0.001). The concordance coefficient was high for BIA (0.80) and moderate for US (0.49). The BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) was on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p < 0.001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US, they were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = 0.09) and US (p = 0.057) to present proportional bias and underestimate BF%. Despite the correlation, the mean differences between the methods were significant, and the agreement limits were very wide. This indicates that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

Mid- to long-term periprosthetic bone density changes after cementless short stem hip arthroplasty in elderly: A clinical and radiological analysis.

Introduction: Short stem prostheses were originally designed for younger and more active patients. In recent years, they have been increasingly offered to older patients. This study evaluates the mid-to long-term survival of a short stem prosthesis and the changes in periprosthetic bone density following implantation of a cementless short hip stem in patients over 60 years of age. Methods: 118 patients aged over 60 received short stem prostheses. Clinical examination included Harris Hip Score (HHS) and Hip Disability and Osteoarthritis Outcome Score (HOOS). 93 patients were followed clinically for at least five years. 53 patients underwent dual-energy x-ray absorptiometry (DXA) and radiographic evaluation. Follow-up intervals were preoperative and postoperative (t0), at approximately six months (t1), at approximately two years (t2), and at approximately five years or later (t3). Results: Over a mean 6.7-year observation period for all 118 patients, one stem revision occurred due to a traumatic periprosthetic stem fracture. The five-year survival rate for the endpoint survival of the Metha® stem in 95 at-risk patients is 99.2%. HHS improved significantly from t0 55.3 ± 11.5 (range 30-79) to t3 95.3 ± 8.6 (range 57-100) at a mean of 8.0 years (p < 0.001). HOOS improved significantly in each subscale (p < 0.001). Bone mineral density (BMD) was available for review in 53 patients after a mean of 7.1 years. BMD increased from t0 to t3 in region of interest (ROI) 3 (+0.4%) and ROI 6 (+2.9%) and decreased in ROI 1 (-10.3%), ROI 2 (-9.8%), ROI 4 (-5.3%), ROI 5 (-3.4%) and ROI 7 (-23.1%). Conclusions: The evaluated short stem prosthesis shows a remarkably high survival rate in elderly patients, accompanied by excellent clinical results. Load transfer measurements show a metaphyseal-diaphyseal pattern with a trend towards increased diaphyseal transfer over the period observed.

The life-course changes in muscle mass using dual-energy X-ray absorptiometry: The China BCL study and the US NHANES study.

BACKGROUND: Sarcopenia is an important indicator of ill health and is linked to increased mortality and a reduced quality of life. Age-associated muscle mass indices provide a critical tool to help understand the development of sarcopenia. This study aimed to develop sex- and age-specific percentiles for muscle mass indices in a Chinese population and to compare those indices with those from other ethnicities using the National Health and Nutrition Examination Survey (NHANES) data. METHODS: Whole-body and regional muscle mass was measured by dual-energy X-ray absorptiometry (DXA) in participants of the China Body Composition Life-course (BCL) study (17 203 healthy Chinese aged 3-60 years, male 48.9%) and NHANES (12 663 healthy Americans aged 8-59 years, male 50.4%). Age- and sex-specific percentile curves were generated for whole-body muscle mass and appendicular skeletal muscle mass using the Generalized Additive Model for Location Scale and Shape statistical method. RESULTS: Values of upper and lower muscle mass across ages had three periods: an increase from age 3 to a peak at age 25 in males (with the 5th and 95th values of 41.5 and 66.4 kg, respectively) and age 23 in females (with the 5th and 95th values of 28.4 and 45.1 kg, respectively), a plateau through midlife (30s-50s) and then a decline after their early 50s. The age at which muscle mass began to decline was 52 years in men with the 5th and 95th percentile values of 43.5 and 64.6 kg, and 51 years in women with the 5th and 95th percentile values of 31.6 and 46.9 kg. Appendicular skeletal muscle mass decreased earlier than whole body muscle mass, especially leg skeletal muscle mass, which decreased slightly after age 49 years in both sexes. In comparison with their US counterparts in the NHANES, the Chinese participants had lower muscle mass indices (all P < 0.001) and reached a muscle mass peak earlier with a lower muscle mass, with the exception of similar values compared with adult Mexican and White participants. The muscle mass growth rate of Chinese children decreased faster than that of other races after the age of 13. CONCLUSIONS: We present the sex- and age-specific percentiles for muscle mass and appendicular skeletal muscle mass by DXA in participants aged 3-60 from China and compare them with those of different ethnic groups in NHANES. The rich data characterize the trajectories of key muscle mass indices that may facilitate the clinical appraisal of muscle mass and improve the early diagnosis of sarcopenia in the Chinese population.

Potential non-invasive detection of lesions in broiler femur heads: application of the DXA imaging system.

Leg health is a significant economic and welfare concern for the poultry industry. Current methods of detection rely on visual assessment of the legs and gait scores and bone scoring during necropsy for full characterization. Additionally, the current scoring of femurs only examines the external surface of the femoral head. Through the use of the dual-energy X-ray absorptiometry (DXA) imaging system, we show the presence of a necrotic region in the femurs that would otherwise be considered healthy based on the current evaluation procedures. Importantly, these lesions were present in almost 60% (22 of 37) of femurs that scored normal for femoral head necrosis (FHN). Additionally, these femurs showed greater bone mineral content (BMC) relative to weight compared to their counterparts with no lucent lesions (6.95% ± 0.20% vs. 6.26% ± 0.25; p = 0.038). Identification of these lesions presents both a challenge and an opportunity. These subclinical lesions are likely to be missed in routine scoring procedures for FHN and can inadvertently impact the characterization of the disease and genetic selection programs. Furthermore, this imaging system can be used for in vivo, ex vivo, and embryonic (egg) studies and, therefore, constitutes a potential non-invasive method for early detection of bone lesions in chickens and other avian species.

Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models.

BACKGROUND AND AIMS: Measurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer. METHODS: Patients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion - alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass. RESULTS: Forty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m2) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA. CONCLUSIONS: Despite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.

Increased adiposity in juvenile idiopathic arthritis - A comparison of the bioelectrical impedance analysis and dual-energy X-ray absorptiometry for the assessment of body composition.

AIM: Higher adiposity and increased risk of cardiovascular diseases have been reported in juvenile idiopathic arthritis (JIA), but body composition measurements have produced inconsistent results. This controlled cross-sectional study assessed body composition with two methods to evaluate adiposity in children with JIA. METHODS: We measured body composition by dual- energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) from 79 JIA-patients in two Finish university hospitals in 2017-2019. Their age- and sex-matched controls (n = 79) were selected from the Physical Activity and Nutrition in Children- study and through National Registry. RESULTS: Body fat percentage measured by BIA was higher (mean, SD) in patients compared to controls (23.1 ± 9.3% vs. 20.1 ± 7.5%, p = 0.047). Also, using DXA, there was a tendency of higher body fat percentage in patients (27.1 ± 9.1% vs. 24.6 ± 8.6, p = 0.106). BIA and DXA showed strong correlation (r from 0.810 to 0.977) in all body composition variables. CONCLUSION: Increased adiposity was observed in patients with JIA. Evaluation of body composition should be included in the multidisciplinary care of JIA to reduce the possible risk of cardiovascular diseases in adulthood. BIA could be a useful tool for assessing body composition due to its clinical availability and safety.

Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis.

BACKGROUND: Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment. METHODS: We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis. RESULTS: The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively. CONCLUSIONS: The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.

Fat-free mass predictive equation using multifrequency bioelectrical impedance data in adolescent soccer athletes: development and cross-validation.

OBJECTIVES: This study aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using multifrequency bioelectrical impedance analysis (BIA) data in adolescent soccer athletes. METHODS: Male adolescent soccer athletes (n = 149; 13-19 y old) were randomly sorted using Excel and independently selected for development group (n = 100) or cross-validation group (n = 49). The FFM reference values were determined using dual-energy X-ray absorptiometry. Single-frequency BIA was used to plot tolerance ellipses. Multifrequency-BIA raw data were used as independent variables in regression models. Student's independent t-test was used to compare development and cross-validation groups. Stepwise multiple regression was used to develop the FFM predictive equation. Bland-Altman plots, Lin's concordance correlation coefficient, according to McBride criteria, precision, accuracy, and standard error of estimate (SEE) were calculated to evaluate the concordance and reliability of estimates. Bioelectrical impedance vector analysis was plotted to assess hydration status. RESULTS: No differences (P > 0.05) were observed between development and validation groups in chronological age, anthropometric data, bioelectrical impedance data, and FFM values obtained using dual-energy X-ray absorptiometry. Bioelectrical impedance vector analysis tolerance showed that all participants presented adequate hydration status compared to the reference population. The new FFM predictive equation developed and validated: FFM (kg) = -7.064 + 0.592 × chronological age (y) + 0.554 × weight (kg) + 0.365 × height²/resistance (cm²/Ω), presented R² = 0.95; SEE = 1.76 kg; concordance correlation coefficient = 0.95, accuracy = 0.98, and strength of concordance = 0.99. CONCLUSIONS: The present study developed and cross-validated an FFM predictive equation based on multifrequency bioelectrical data providing substantial FFM accuracy for male adolescent soccer athletes.

Validity and agreement between dual-energy X-ray absorptiometry, anthropometry and bioelectrical impedance in the estimation of fat mass in young adults.

Introduction: Assessment of fat mass has historically employed various methods like Dual-energy X-ray Absorptiometry (DXA), and bioelectrical impedance (BIA), and anthropometry with its set of formulas. However, doubts persist regarding their validity and interchangeability to evaluate fat mass. This research aimed to determine the validity of anthropometry, and BIA in estimating fat mass Vs DXA, considering the influence of sex and hydration status. Methods: A descriptive, cross-sectional study included 265 young adults (161 males and 104 females), assessed through DXA, BIA in a standing position, and anthropometry. A fat mass estimation formula with DXA, a fat mass estimation formula with BIA and 10 fat mass estimation formulas with anthropometry were calculated. Results: Significant differences were found across DXA, BIA and anthropometry in both kilograms and percentages for the overall sample (p<0.001), and when the covariable sex was included (p<0.001), with no significant effect of hydration status (p=0.332-0.527). Bonferroni-adjusted analyses revealed significant differences from DXA with anthropometry and BIA in most cases for the overall sample (p<0.001), as well as when stratified by sex (p<0.001-0.016). Lin's coefficient indicated poor agreement between most of the formulas and methods both in percentage and kilograms of fat mass (CCC=0.135-0.892). In the Bland-Altman analysis, using the DXA fat mass values as a reference, lack of agreement was found in the general sample (p<0.001-0.007), except for Carter's formula in kilograms (p=0.136) and percentage (p=0.929) and Forsyth for percentage (p=0.365). When separating the sample by sex, lack of agreement was found in males for all methods when compared with both percentage and kilograms calculated by DXA (p<0.001). In the female sample, all methods and formulas showed lack of agreement (p<0.001-0.020), except for Evans's in percentage (p=0.058). Conclusion: The formulas for fat mass assessment with anthropometry and BIA may not be valid with respect to the values reported with DXA, with the exception of Carter's anthropometry formula for general sample and Evans's anthropometry formula for female sample. BIA could also be an alternative if what is needed is to assess fat mass in women as a group.

Bone mineral density parameters and related nutritional factors in vegans, lacto-ovo-vegetarians, and omnivores: a cross-sectional study.

Introduction: The growing prevalence of vegetarianism determines the need for comprehensive study of the impact of these diets on health and particularly on bone metabolism. We hypothesized that significant dietary differences between vegans, lacto-ovo-vegetarians, and omnivores also cause significant differences in their nutrient status, which may affect bone health. Methods: The study assessed dual-energy X-ray absorptiometry parameters in lumbar spine and femoral neck, average nutrient intake, serum nutrient concentrations, serum PTH levels, and urinary pH among 46 vegans, 38 lacto-ovo-vegetarians, and 44 omnivores. Results: There were no differences in bone mineral density (BMD) between the groups. However, the parathyroid hormone (PTH) levels were still higher in vegans compared to omnivores, despite the same prevalence of hyperparathyroidism in all groups. These findings may probably be explained by the fact that each group had its own "strengths and weaknesses." Thus, vegans and, to a lesser extent, lacto-ovo-vegetarians consumed much more potassium, magnesium, copper, manganese, and vitamins B6, B9, and C. At the same time, the diet of omnivores contained more protein and vitamins D and B12. All the subjects consumed less vitamin D than recommended. More than half of vegans and omnivores had insufficiency or even deficiency of vitamin D in the blood. Low serum concentrations of manganese with its quite adequate intake are also noteworthy: its deficiency was observed in 57% of vegans, 79% of lacto-ovo-vegetarians, and 63% of omnivores. Discussion: Currently, it is no longer possible to conclude that lacto-ovo-vegetarians have lower BMD than omnivores, as our research supported. Vegans in our study also did not demonstrate lower BMD values, only higher PTH blood concentrations, compared to omnivores, however, a large number of studies, including recent, show the opposite view. In this regard, further large-scale research is required. Vegans and lacto-ovo-vegetarians now have a variety of foods fortified with vitamins D and B12, as well as calcium. There is also a great diversity of ethically sourced dietary supplements. The found low concentrations of manganese require further investigation.

A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture.

Hip fractures present a significant healthcare challenge, especially within aging populations, where they are often caused by falls. These fractures lead to substantial morbidity and mortality, emphasizing the need for timely surgical intervention. Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors. We propose a novel staged model that combines advanced imaging and clinical data to improve predictive performance. By using convolutional neural networks (CNNs) to extract features from hip DXA images, along with clinical variables, shape measurements, and texture features, our method provides a comprehensive framework for assessing fracture risk. The study cohort included 547 patients, with 94 experiencing hip fracture. A staged machine learning-based model was developed using two ensemble models: Ensemble 1 (clinical variables only) and Ensemble 2 (clinical variables and DXA imaging features). This staged approach used uncertainty quantification from Ensemble 1 to decide if DXA features are necessary for further prediction. Ensemble 2 exhibited the highest performance, achieving an Area Under the Curve (AUC) of 0.9541, an accuracy of 0.9195, a sensitivity of 0.8078, and a specificity of 0.9427. The staged model also performed well, with an AUC of 0.8486, an accuracy of 0.8611, a sensitivity of 0.5578, and a specificity of 0.9249, outperforming Ensemble 1, which had an AUC of 0.5549, an accuracy of 0.7239, a sensitivity of 0.1956, and a specificity of 0.8343. Furthermore, the staged model suggested that 54.49% of patients did not require DXA scanning. It effectively balanced accuracy and specificity, offering a robust solution when DXA data acquisition is not always feasible. Statistical tests confirmed significant differences between the models, highlighting the advantages of the advanced modeling strategies. Our staged approach offers a cost-effective holistic view of patients' health. It could identify individuals at risk with a high accuracy but reduce the unnecessary DXA scanning. Our approach has great promise to guide interventions to prevent hip fractures with reduced cost and radiation.