Search Results (430)

Introduction: Sarcopenia is a systemic condition linked to increased morbidity and mortality in older adults. Point-of-Care Ultrasound (POCUS) offers a rapid, bedside method to assess muscle mass. This study evaluates the diagnostic accuracy of POCUS compared to Dual-energy X-ray Absorptiometry (DXA), the gold standard method, and explores its prognostic value in old patients undergoing surgery for hip fractures. Patients and Methods: In this prospective, single-center study, 126 patients aged ≥ 70 years and hospitalized with hip fractures were included. Sarcopenia was defined according to the revised 2018 EWGSOP2 criteria. Muscle mass was assessed by the Appendicular Skeletal Muscle Mass Index (ASMI) using DXA and by the thickness of the rectus femoris (RF) muscle using POCUS. Results: Of the 126 included patients, 52 had both DXA and POCUS assessments, and 43% of them met the diagnostic criteria for sarcopenia or severe sarcopenia. RF muscle thickness measured by POCUS was significantly associated with ASMI (R² = 0.30; p < 0.001). POCUS showed a fair diagnostic accuracy in women (AUC 0.652) and an excellent accuracy in men (AUC 0.905). Optimal diagnostic thresholds according to Youden’s index were 5.7 mm for women and 9.3 mm for men. Neither RF thickness, ASMI, nor sarcopenia status predicted mortality or major postoperative complications. Conclusions: POCUS is a promising, accessible tool for diagnosing sarcopenia in old adults with hip fractures. Nonetheless, its prognostic utility remains uncertain and should be further evaluated in long-term studies. Full article

The aim of this study was to evaluate structural and micro-architectural changes in the mandible, parietal bone, femur, and tibia in OVX rats at different time periods after ovariectomy. Forty-two 11-month-old female Wistar rats were used. Six rats without surgery were euthanized to serve as a baseline. Eighteen rats were ovariectomized and fed with a calcium-deficient diet, and eighteen animals were used as controls (Ctrls) and fed with a standard diet. Six OVX rats and six Ctrls were euthanized at 3, 6, and 9 months. Qualitative histology and dual-energy X-ray absorptiometry (DXA) were performed. Histological evaluation of bones harvested from the OVX groups revealed trabecular bone reduction, while no significant differences in the cortical bone of OVX and Ctrls were observed. DXA measurements of (1) femoral diaphysis showed a significant decrease in the OVX group compared to the Ctrl groups at 3 (p = 0.041), 6 (p < 0.001), and 9 months (p < 0.001); (2) the proximal tibia showed a significant decrease in the OVX group compared to the Ctrl groups (p < 0.001); (3) parietal bone showed a significant difference between OVX and Ctrls at 6 months (p = 0.012); and (4) the mandible showed no significant differences between the OVX and Ctrl groups. OVX aged rats might present reductions in the density of the femoral diaphysis, proximal tibia, parietal bone, and mandible at different time points. These findings contribute to the field of biomimetics by providing more details for the understanding of age- and hormone-related bone changes in the osteoporotic-like rat model. Such data are critical for the development of biomimetic materials and structures that attempt to simulate natural bone adaptation and deterioration, especially in the context of postmenopausal or osteoporotic conditions. Full article

A novel composite patch osteosynthesis technique (CPT) has demonstrated promising ex vivo biomechanical performance in small tubular bones. To bridge the gap toward clinical evaluations, this study compared the stability of the CPT to a stainless-steel locking plate (LP) in an experimental in vivo ovine bilateral proximal phalanx fracture model. Eight sheep underwent a midline osteotomy with a 4.5 mm circular unicortical defect in the lateral proximal phalanx of both front limbs, treated with the CPT (n = 8) or the LP (n = 8). A half-limb walking cast, or a custom off-loading hoof shoe, was used for postoperative protection. Implant stability was assessed by post-surgery X-ray evaluations and post-euthanasia (16 weeks) dual-energy X-ray absorptiometry (DXA). At week one, all CPT implants demonstrated mechanical failure, while all LPs remained overall intact. Mean BMD was 0.45 g/cm² for CPT and 0.60 g/cm² for LP in the fracture area (p = 0.078), and 0.37 g/cm² vs. 0.41 g/cm² in the distal epiphysis (p = 0.016), respectively. In conclusion, the CPT demonstrated indications of inferior stability compared to the LP in this fracture model, which may limit its clinical applicability in weight-bearing or high-load scenarios and in non-compliant patients. Full article

Background: Sarcopenia is a progressive muscle disease that compromises mobility and quality of life in older adults. Although dual-energy X-ray absorptiometry (DXA) is the standard for assessing Appendicular Lean Mass Index (ALMI), it is costly and often inaccessible. This study aims to develop machine learning models using anthropometric measurements to predict low ALMI for the diagnosis of sarcopenia. Methods: A cross-sectional study was conducted on 183 Mexican adults (67.2% women and 32.8% men, ≥60 years old). ALMI was measured using DXA, and anthropometric data were collected following the International Society for the Advancement of Kinanthropometry (ISAK) protocols. Predictive models were developed using Logistic Regression (LR), Decision Trees (DTs), Random Forests (RFs), Artificial Neural Networks (ANNs), and LASSO regression. The dataset was split into training (70%) and testing (30%) sets. Model performance was evaluated using classification performance metrics and the area under the ROC curve (AUC). Results: ALMI indicated strong correlations with BMI, corrected calf girth, and arm relaxed girth. Among models, DT achieved the best performance in females (AUC = 0.84), and ANN indicated the highest AUC in males (0.92). Regarding the prediction of low ALMI, specificity values were highest in DT for females (100%), while RF performed best in males (92%). The key predictive variables varied depending on sex, with BMI and calf girth being the most relevant for females and arm girth for males. Conclusions: Anthropometry combined with machine learning provides an accurate, low-cost approach for identifying low ALMI in older adults. This method could facilitate sarcopenia screening in clinical settings with limited access to advanced diagnostic tools. Full article

The assessment of bone mineral density (BMD) is essential for osteoporosis diagnosis. Dual-energy X-ray Absorptiometry (DXA) is the current gold standard, but it has limitations in evaluating trabecular bone and is susceptible to different artifacts. In this study we evaluate whether Dual-Energy Computed Tomography (DECT) can be defined as an alternative method for the assessment of BMD in a sample of postmenopausal patients undergoing oncological follow-up. In this study a retrospective analysis was conducted on 41 patients who had both DECT and DXA within six months. BMD values were extracted from DECT using five different base material pairs (BMPs) and compared with DXA measurements at the femoral neck. The calcium–fat pairing showed the strongest correlation with DXA-derived BMD (Spearman’s ρ = 0.797) and excellent reproducibility (ICC = 0.983). There was a strong and significant association between the DXA results and the various BPM measurements. These findings support the possibility of DECT in the precise and opportunistic evaluation of BMD changes when employing particular BMPs. This study showed how this technique can be a useful and effective substitute for conventional DXA, particularly when patients are in oncological follow-up using DECT, minimizing additional radiation exposure. Full article

Objectives: The early detection of low bone mineral density (BMD) is essential for preventing osteoporosis and related complications. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its cost and limited availability restrict its use in large-scale screening. This study investigated whether raw bioelectrical impedance analysis (BIA) data combined with explainable machine learning (ML) models could accurately classify osteopenia in women aged 40 to 55. Methods: In a cross-sectional design, 138 women underwent same-day BIA and DXA assessments. Participants were categorized as osteopenic (T-score between −1.0 and −2.5; n = 33) or normal (T-score ≥ −1.0) based on DXA results. Overall, 24.1% of the sample were classified as osteopenic, and 32.85% were postmenopausal. Raw BIA outputs were used as input features, including impedance values, phase angles, and segmental tissue parameters. A sequential forward feature selection (SFFS) algorithm was employed to optimize input dimensionality. Four ML classifiers were trained using stratified five-fold cross-validation, and SHapley Additive exPlanations (SHAP) were applied to interpret feature contributions. Results: The neural network (NN) model achieved the highest classification accuracy (92.12%) using 34 selected features, including raw impedance measurements, derived body composition indices such as regional lean mass estimates and the edema index, as well as a limited number of categorical variables, including self-reported physical activity status. SHAP analysis identified muscle mass indices and fluid distribution metrics, features previously associated with bone health, as the most influential predictors in the current model. Other classifiers performed comparably but with lower precision or interpretability. Conclusions: ML models based on raw BIA data can classify osteopenia with high accuracy and clinical transparency. This approach provides a cost-effective and interpretable alternative for the early identification of individuals at risk for low BMD in resource-limited or primary care settings. Full article

Background/Objectives: Childhood obesity represents a growing public health concern. It is closely associated with obstructive sleep apnoea (OSA), which impairs nocturnal breathing and significantly affects neurocognitive and cardiovascular health. This review aims to analyse differences in fat distribution, anthropometric parameters, and instrumental assessments of paediatric OSA compared to adult OSA to improve the diagnostic characterisation of obese children. Methods: narrative review. Results: While adenotonsillar hypertrophy (ATH) remains a primary cause of paediatric OSA, the increasing prevalence of obesity has introduced distinct pathophysiological mechanisms, including fat accumulation around the pharynx, reduced respiratory muscle tone, and systemic inflammation. Children exhibit different fat distribution patterns compared to adults, with a greater proportion of subcutaneous fat relative to visceral fat. Nevertheless, cervical and abdominal adiposity are crucial in increasing upper airway collapsibility. Recent evidence highlights the predictive value of anthropometric and body composition indicators such as neck circumference (NC), neck-to-height ratio (NHR), neck-to-waist ratio (NWR), fat-to-muscle ratio (FMR), and the neck-to-abdominal-fat percentage ratio (NAF%). In addition, ultrasound assessment of lateral pharyngeal wall (LPW) thickness and abdominal fat distribution provides clinically relevant information regarding anatomical contributions to OSA severity. Among imaging modalities, dual-energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), and air displacement plethysmography (ADP) have proven valuable tools for evaluating body fat distribution. Conclusions: Despite advances in the topic, a validated predictive model that integrates these parameters is still lacking in clinical practice. Polysomnography (PSG) remains the gold standard for diagnosis; however, its limited accessibility underscores the need for complementary tools to prioritise the identification of children at high risk. A multimodal approach integrating clinical, anthropometric, and imaging data could support the early identification and personalised management of paediatric OSA in obesity. Full article

Background/Objectives: To investigate associations between Follistatin (FST) gene polymorphisms (SNPs) and baseline musculoskeletal traits, and their interactions with 16-week exercise interventions. Methods: A cohort of 470 untrained Northern Han Chinese adults (208 males, 262 females), sourced from the “Research on Key Technologies for an Exercise and Fitness Expert Guidance System” project, was analyzed. These participants were previously randomly assigned to one of four exercise groups (Hill, Running, Cycling, Combined) or a non-exercising Control group, and completed their respective 16-week protocols. Body composition, bone mineral content (BMC), bone mineral density (BMD), and serum follistatin levels were all assessed pre- and post-intervention. Dual-energy X-ray absorptiometry (DXA) was utilized for the body composition, BMC, and BMD measurements. FST SNPs (rs3797296, rs3797297) were genotyped using matrix assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-TOF MS) or microarrays. To elucidate the biological mechanisms, we performed in silico functional analyses for rs3797296 and rs3797297. Results: Baseline: In females only, the rs3797297 T allele was associated with higher muscle mass (β = 1.159, 95% confidence interval (CI): 0.202–2.116, P_{_adj} = 0.034) and BMC (β = 0.127, 95% CI: 0.039–0.215, P_{_adj} = 0.009), with the BMC effect significantly mediated by muscle mass. Exercise Response: Interventions improved body composition, particularly in females. Gene-Exercise Interaction: A significant interaction occurred exclusively in women undertaking hill climbing: the rs3797296 G allele was associated with attenuated muscle mass gains (β = −1.126 kg, 95% CI: −1.767 to −0.485, P_{_adj} = 0.034). Baseline follistatin correlated with body composition (stronger in males) and increased post-exercise (primarily in males, Hill/Running groups) but did not mediate SNP effects on exercise adaptation. Functional annotation revealed that rs3797297 is a likely causal variant, acting as a skeletal muscle eQTL for the mitochondrial gene NDUFS4, suggesting a mechanism involving muscle bioenergetics. Conclusions: Findings indicate that FST polymorphisms associate with musculoskeletal traits in Northern Han Chinese. Mechanistic insights from functional annotation reveal potential pathways for these associations, highlighting the potential utility of these genetic markers for optimizing training program design. Full article

Background: Sport plays an important role in the health promotion of people with cerebral palsy (CP). However, risk factors may impair sport performance and health in non-ambulatory athletes. Therefore, the aim of the present study was to explore body composition and bone health in a group of world-class Boccia players with CP. Methods: Five BC2-class players with CP, aged 15–42 years old, were assessed using Dual-Energy X-Ray Absorptiometry (DXA) for body composition and bone mineral density (BMD) and content (BMC). The fat mass index (kg/m²) was used to define obesity, and the BMD Z-score used to analyze bone health. A preliminary indicator of sarcopenia was considered using the appendicular lean mass index. Results: Players 1 and 3 exhibited similar body compositions (obesity class 1 and BMD Z-score are below the expected range for age). Player 5 exhibited multiple health-related risk factors. The results regarding youth players (Player 2 and Player 4) should be analyzed with caution. Conclusions: Overall, due to Boccia’s specific characteristics, players may benefit from close monitoring by multidisciplinary teams and supplementary strategies (e.g., strength training, individualized diet plans) to promote quality of life and performance. However, further research is needed to confirm the data, since these preliminary findings do not allow for broader generalizations. Full article

Background/Objectives: Recent data on long-term consequences of prematurity on bone health are conflicting. The aim of this study was to assess the metabolic bone profile and bone mineral density (BMD) in prepubertal children born prematurely and to examine possible associations between bone health parameters and perinatal morbidity factors. Methods: This cross-sectional observational study included 144 children of mean (SD) age 10.9 (1.6) years: 49 children born very preterm (≤32 gestational weeks), 37 moderate-to-late preterm (32⁺¹ to 36⁺⁶ gestational weeks), and 58 born at term (controls). Serum levels of calcium/Ca, phosphorus/P, alkaline phosphatase/ALP, 25-hydroxyvitamin D/25(OH)D, bone formation markers (osteocalcin/OC, procollagen type I C-terminal propeptide/PICP, and insulin growth factor-1/IGF-1), and bone resorption markers (serum tartrate-resistant acid phosphatase 5b/bone TRAP5band urinary calcium-to-creatinine ratio) were measured. Total-body and lumbar-spine BMD and BMD Z-scores were calculated using dual-energy X-ray absorptiometry/DXA. Results: Children born very preterm showed significantly higher ALP, OC, PICP, and bone TRAP5b levels compared to controls, as well as compared to children born moderate-to-late preterm. Total-body and lumbar-spine BMD Z-scores were significantly lower in the very preterm-born group compared to controls. Gestational diabetes, preeclampsia, and bronchopulmonary dysplasia were associated with lower total-body BMD in the very preterm-born population. Conclusions: Preterm birth is associated with impaired metabolic bone profile and lower total-body and lumbar-spine BMD in childhood. Moderate-to-late preterm-born children exhibit altered metabolic bone parameters compared to very preterm-born children. Further research in children might allow better insight into the long-term impact of preterm birth on bone health. Full article

Background/Objectives: Cerebral palsy (CP) is the most common cause of neurological disability in children and is frequently associated with low bone mineral density (BMD) and increased risk of fractures. This study aimed to assess BMD in children with CP, compare it with normative standards, and explore potential associations with anthropometric parameters and the clinical characteristics of children with CP. Methods: Thirty-six children with CP aging 6–15 years from both sexes with varying levels of Gross Motor Functional Classification System (GMFCS) and spasticity were evaluated. Areal BMD and Z-scores (total and subtotal) were measured using dual-energy X-ray absorptiometry (DXA). Regression analysis identified predictors of BMD. Results: Children with GMFCS levels III–V had significantly lower total and subtotal Z-scores compared to those with levels I–II (p = 0.001 and p = 0.02, respectively). Total Z-score was significantly predicted by weight (β = 1.02, p = 0.002), height (β = −0.72, p = 0.02), and sedentary time (β = −0.47, p = 0.005). “No walking” was the only significant predictor for subtotal Z-score (β = −0.50, p = 0.004). Conclusions: Children with moderate to severe CP exhibited significantly lower BMD, particularly those with limited ambulation and higher spasticity levels. These findings underscore the importance of early screening and targeted interventions to optimize bone health in this population. Full article

Background/Objectives: Rheumatoid arthritis (RA) is a chronic inflammatory disease frequently accompanied by comorbid conditions that contribute to disability and worsen long-term outcomes. Among these, malnutrition and osteosarcopenia remain under-recognised. This cross-sectional study aimed to assess the prevalence of malnutrition and osteosarcopenia among elderly women with RA and explore the clinical impact of these conditions. Methods: Sixty-five women over 65 years with RA were evaluated using Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and EWGSOP2-based assessments for sarcopenia; bone status was measured by dual-energy X-ray absorptiometry (DXA), trabecular bone score (TBS), and three-dimensional DXA (3D-DXA). Results: Malnutrition was identified in 49.2% and osteosarcopenia in 52.3% of participants. A significant bidirectional association was observed: malnourished patients had higher rates of osteosarcopenia (65.6% vs. 34.4%; p < 0.05), and osteosarcopenic patients were more frequently malnourished (61.8% vs. 39.1%; p < 0.05). Both conditions were associated with older age, lower body mass index (BMI), impaired muscle parameters, and reduced bone mineral density. Malnourished and osteosarcopenic patients reported worse fatigue and lower physical quality of life, despite similar inflammatory activity. Significant correlations were found between muscle mass indices and bone quality metrics assessed by 3D-DXA. These findings highlight a substantial burden of malnutrition and osteosarcopenia in elderly women with RA, even with well-controlled disease despite similar inflammatory activity (mean Disease Activity Score 28: 2.8 ± 1.0; 43.1% in remission. Conclusions: There is a substantial burden of malnutrition and osteosarcopenia in elderly women with RA that support the integration of systematic nutritional and musculoskeletal screening into routine care. Future studies should evaluate age- and disease-specific mechanisms and assess the benefit of multidisciplinary strategies to prevent frailty and improve long-term outcomes. Full article

Background/Objectives: The body mass index (BMI) is considered a key method for the classification of individuals’ weight status, according to cut-off points proposed by the World Health Organization (WHO); however, the use of this classification is still the subject of debate and criticism. We aimed to evaluate the accuracy of the WHO BMI classification in reflecting true adiposity in the Italian general population. Methods: This cross-sectional study included 1351 adults of mixed gender aged between 18 and 98 years, comprising 19 (1.4%) underweight individuals, 787 (58.3%) normal weight, 354 (26.2%) overweight, and 191 (14.1%) with obesity according to the WHO BMI. After that they were re-categorized according to adiposity based on body fat percentage (BF%) measured by dual-energy X-ray absorptiometry (DXA). The agreement between the two classification systems was tested using the kappa statistic (κ), with the system based on BF% being considered the gold standard. Results: According to the BMI classification, 78.1% of the individuals who were in the normal weight range were correctly classified. However, 53.4% of the overweight group and 68.4% of the underweight group were misclassified according to the BMI, as the majority of those misclassified fell within the normal weight range according to their BF%. Finally, regarding the obesity group, 34% who were classified as having obesity according to the BMI were misclassified, since they were revealed to be only affected by overweight according to adiposity status. Conclusions: Despite the fact that the BMI seems to be reliable in determining body weight status in the normal weight range, over a third of the general population was misclassified, as the current BMI classification appears to inflate the prevalence of underweight, overweight, and obesity among the general population. Accordingly, this may warrant consideration of revising the National Guidelines in Italy related to weight status classification. Healthcare practitioners should be advised not to rely solely on the BMI, and should integrate its use with adiposity measures (i.e., BF%) or alternative surrogate indicators (i.e., waist-based) in routine evaluations, especially in those with a BMI below or above 18.5 kg/m² or 25 kg/m². Full article

Objectives: The aim of this study was to develop AI-based predictive models to assess the risk of osteoporosis in postmenopausal women using panoramic radiographs (OPTs). Methods: A total of 301 panoramic radiographs (OPTs) from postmenopausal women were collected and labeled based on DXA-assessed bone mineral density. Of these, 245 OPTs from the Hospital of San Giovanni Rotondo were used for model training and internal testing, while 56 OPTs from the University of Parma served as an external validation set. A mandibular region of interest (ROI) was defined on each image. Predictive models were developed using classical radiomics, deep radiomics, and convolutional neural networks (CNNs), evaluated based on AUC, accuracy, sensitivity, and specificity. Results: Among the tested approaches, classical radiomics showed limited predictive ability (AUC = 0.514), whereas deep radiomics using DenseNet-121 features combined with logistic regression achieved the best performance in this group (AUC = 0.722). For end-to-end CNNs, ResNet-50 using a hybrid feature extraction strategy achieved the highest AUC in external validation (AUC = 0.786), with a sensitivity of 90.5%. While internal testing yielded high performance metrics, external validation revealed reduced generalizability, highlighting the challenges of translating AI models into clinical practice. Conclusions: AI-based models show potential for opportunistic osteoporosis screening from OPT images. Although the results are promising, particularly those obtained with deep radiomics and transfer learning strategies, further refinement and validation in larger and more diverse populations are essential before clinical application. These models could support the early, non-invasive identification of at-risk patients, complementing current diagnostic pathways. Full article

Osteogenesis imperfecta (OI) is a rare bone dysplasia that occurs with a frequency of 1/15,000–20,000 live births. It is characterized by increased susceptibility of bone fractures, skeletal deformities, low stature, and low bone mass. It results in impaired production of type I collagen. About 90% of people with OI have heterozygous mutations in the COL1A1 and COL1A2 genes. Fibroblast growth factor 23 (FGF23) is a protein involved in the regulation of phosphate and 1,25-dihydroxyvitamin D₃ metabolism on a negative feedback basis. FGF23 is secreted by osteocytes in response to increased serum calcitriol and phosphorus. The purpose of this study was to evaluate the concentration of FGF23 among children with osteogenesis imperfecta and the differences in reference values in a healthy population of children and adolescents. Then, this study sought to evaluate how the course of osteogenesis imperfecta, including type of disease, number of bone fractures, and bone mineral density, are related to FGF23 concentration. The study included 47 children aged 3 to 17 years with a diagnosis of osteogenesis imperfecta, confirmed by genetic tests. The patients were hospitalized at the Department from August 2019 to September 2020 and were treated with intravenous infusions of sodium pamidronate. The course of the disease was analyzed, including the number of bone fractures, clinical symptoms, and anthropometric parameters, and bone densitometry was performed by dual X-ray absorptiometry (DXA) in Total Body Less Head (TBLH) and Spine options with Z-score evaluation. FGF23 concentration was determined by the ELISA method. The study was prospective in nature. Results: The mean level of FGF23 in the study group of patients was 645.09 pg/mL and was within the reference values for the developmental age population. There was no significant correlation between FGF23 concentration and anthropometric measurements: body weight (p = 0.267), height (p = 0.429), gender (p = 0.291), or pubertal stage (p = 0.223) in the study group of patients. FGF23 levels were not related to the number of fractures (p = 0.749), the number of sodium pamidronate cycles administered (p = 0.580), bone mineral density parameters (Z-score), the form of osteogenesis imperfecta (p = 0.156), or the genetic test result (p = 0.573). FGF23 levels decrease with age (r = −0.32, p = 0.030) and BMI (r = −0.34, p = 0.020). The level of FGF23 in patients with osteogenesis imperfecta is lower among older children and those having a higher BMI. This index cannot be a diagnostic tool in this group of patients, for no differences were found between the concentrations in patients with osteogenesis imperfecta and the developmental age population. Full article