Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques.

Background: As the population ages, the rates of hip diseases and fragility fractures are increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly patients. With the increasing number of THA surgeries and diverse surgical methods, there is a need for standard evaluation protocols. This study aimed to use deep learning algorithms to classify THA videos and evaluate the accuracy of the labelling of these videos. Methods: In our study, we manually annotated 7 phases in THA, including skin incision, broaching, exposure of acetabulum, acetabular reaming, acetabular cup positioning, femoral stem insertion, and skin closure. Within each phase, a second trained annotator marked the beginning and end of instrument usages, such as the skin blade, forceps, Bovie, suction device, suture material, retractor, rasp, femoral stem, acetabular reamer, head trial, and real head. Results: In our study, we utilized YOLOv3 to collect 540 operating images of THA procedures and create a scene annotation model. The results of our study showed relatively high accuracy in the clear classification of surgical techniques such as skin incision and closure, broaching, acetabular reaming, and femoral stem insertion, with a mean average precision (mAP) of 0.75 or higher. Most of the equipment showed good accuracy of mAP 0.7 or higher, except for the suction device, suture material, and retractor. Conclusions: Scene annotation for the instrument and phases in THA using deep learning techniques may provide potentially useful tools for subsequent documentation, assessment of skills, and feedback.

Precise individual muscle segmentation in whole thigh CT scans for sarcopenia assessment using U-net transformer.

The study aims to develop a deep learning based automatic segmentation approach using the UNETR(U-net Transformer) architecture to quantify the volume of individual thigh muscles(27 muscles in 5 groups) for Sarcopenia assessment. By automating the segmentation process, this approach improves the efficiency and accuracy of muscle volume calculation, facilitating a comprehensive understanding of muscle composition and its relationship to Sarcopenia. The study utilized a dataset of 72 whole thigh CT scans from hip fracture patients, annotated by two radiologists. The UNETR model was trained to perform precise voxel-level segmentation and various metrics such as dice score, average symmetric surface distance, volume correlation, relative absolute volume difference and Hausdorff distance were employed to evaluate the model's performance. Additionally, the correlation between Sarcopenia and individual thigh muscle volumes was examined. The proposed model demonstrated superior segmentation performance compared to the baseline model, achieving higher dice scores (DC = 0.84) and lower average symmetric surface distances (ASSD = 1.4191 ± 0.91). The volume correlation between Sarcopenia and individual thigh muscles in the male group. Furthermore, the correlation analysis of grouped thigh muscles also showed negative associations with Sarcopenia in the male participants. This thesis presents a deep learning based automatic segmentation approach for quantifying individual thigh muscle volume in sarcopenia assessment. The results highlights the associations between Sarcopenia and specific individual muscles as well as grouped thigh muscle regions, particularly in males. The proposed method improves the efficiency and accuracy of muscle volume calculation, contributing to a comprehensive evaluation of Sarcopenia. This research enhances our understanding of muscle composition and performance, providing valuable insights for effective interventions in Sarcopenia management.

A machine learning model for prediction of sarcopenia in patients with Parkinson's Disease.

OBJECTIVE: Patients with Parkinson's disease (PD) have an increased risk of sarcopenia which is expected to negatively affect gait, leading to poor clinical outcomes including falls. In this study, we investigated the gait patterns of patients with PD with and without sarcopenia (sarcopenia and non-sarcopenia groups, respectively) using an app-derived program and explored if gait parameters could be utilized to predict sarcopenia based on machine learning. METHODS: Clinical and sarcopenia profiles were collected from patients with PD at Hoehn and Yahr (HY) stage ≤ 2. Sarcopenia was defined based on the updated criteria of the Asian Working Group for Sarcopenia. The gait patterns of the patients with and without sarcopenia were recorded and analyzed using a smartphone application. The random forest model was applied to predict sarcopenia in patients with PD. RESULTS: Data from 38 patients with PD were obtained, among which 9 (23.7%) were with sarcopenia. Clinical parameters were comparable between the sarcopenia and non-sarcopenia groups. Among various clinical and gait parameters, the average range of motion of the hip joint showed the highest association with sarcopenia. Based on the random forest algorithm, the combined difference in knee and ankle angles from standing still before walking to the maximum angle during walking (Kneeankle_diff), the difference between the angle when standing still before walking and the maximum angle during walking for the ankle (Ankle_dif), and the min angle of the hip joint (Hip_min) were the top three features that best predict sarcopenia. The accuracy of this model was 0.949. CONCLUSIONS: Using smartphone app and machine learning technique, our study revealed gait parameters that are associated with sarcopenia and that help predict sarcopenia in PD. Our study showed potential application of advanced technology in clinical research.

Quality of life in sarcopenia measured with the SarQoL questionnaire: A meta-analysis of individual patient data.

Age-related sarcopenia, resulting from a gradual loss in skeletal muscle mass and strength, is pivotal to the increased prevalence of functional limitation among the older adult community. The purpose of this meta-analysis of individual patient data is to investigate the difference in health-related quality of life between sarcopenic individuals and those without the condition using the Sarcopenia Quality of Life (SarQoL) questionnaire. A protocol was published on PROSPERO. Multiple databases and the grey literature were searched until March 2023 for studies reporting quality of life assessed with the SarQoL for patients with and without sarcopenia. Two researchers conducted the systematic review independently. A two-stage meta-analysis was performed. First, crude (mean difference) and adjusted (beta coefficient) effect sizes were calculated within each database; then, a random effect meta-analysis was applied to pool them. Heterogeneity was measured using the Q-test and I2 value. Subgroup analyses were performed to investigate the source of potential heterogeneity. The strength of evidence of this association was assessed using GRADE. From the 413 studies identified, 32 were eventually included, of which 10 were unpublished data studies. Sarcopenic participants displayed significantly reduced health-related quality of life compared with non-sarcopenic individuals (mean difference = -12.32; 95 % CI = [-15.27; -9.37]). The model revealed significant heterogeneity. Subgroup analyses revealed a substantial impact of regions, clinical settings, and diagnostic criteria on the difference in health-related quality of life between sarcopenic and non-sarcopenic individuals. The level of evidence was moderate. This meta-analysis of individual patient data suggested that sarcopenia is associated with lower health-related quality of life measured with SarQoL.

Hip Fractures in Centenarians: Functional Outcomes, Mortality, and Risk Factors from a Multicenter Cohort Study.

Background: Increasing longevity has caused the very old population to become the fastest-growing segment. The number of centenarians (over 100 years old) is increasing rapidly. Fractures in the elderly lead to excessive medical costs and decreased quality of life with socioeconomic burdens. However, little research has thoroughly examined the functional outcomes and mortality of hip fractures in centenarians. Methods: This is a retrospective observational study. Sixty-eight centenarian hip fracture patients were admitted to the 10 institutions from February 2004 to December 2019. Fifty-six patients with 1-year follow-up were finally included. The following data were obtained: sex, age, body mass index, Charlson comorbidity index value on the operation day, Koval's classification for ambulatory ability, type of fracture, the time interval from trauma to surgery, American Society of Anesthesiologists grade, surgery-related complications, and duration of hospital stay. Postoperative Koval's classification (at 1 year after surgery) and information about death were also collected. Multivariate analysis was performed to analyze the risk factors affecting mortality 1 year after surgery. Results: Mortality rates were 26.8% at 6 months and 39.3% at 1 year. The 90-day mortality was 19.6%, and one of them (2.1%) died in the hospital. The 1-year mortality rates for the community ambulatory and non-community ambulatory groups were 29% and 52%, respectively. Only 9 (16.1%) were able to walk outdoors 1 year after surgery. The remaining 47 patients (83.9%) had to stay indoors after surgery. Multivariate analysis demonstrated that the pre-injury ambulatory level (adjusted hazard ratio, 2.884; p = 0.034) was associated with the risk of mortality. Conclusions: We report a 1-year mortality rate of 39.3% in centenarian patients with hip fractures. The risk factor for mortality was the pre-injury ambulatory status. This could be an important consideration in the planning of treatment for centenarian hip fracture patients.

Effectiveness and Usefulness of Bone Turnover Marker in Osteoporosis Patients: A Multicenter Study in Korea.

BACKGROUND: This study aimed to investigate real-world data of C-terminal telopeptide (CTX), propeptide of type I collagen (P1NP), and osteocalcin through present multicenter clinical study, and retrospectively analyze the usefulness of bone turnover markers (BTMs) in Koreans. METHODS: The study focused on pre- and post-menopausal patients diagnosed with osteoporosis and excluded patients without certain test results or with test intervals of over 1 year. The demographic data and 3 BTMs (CTX, P1NP, and osteocalcin) were collected. The patients were classified by demographic characteristics and the BTM concentrations were analyzed by the group. RESULTS: Among women with no history of fractures, the levels of P1NP (N=2,100) were 43.544±36.902, CTX (N=1,855) were 0.373 ±0.927, and osteocalcin (N=219) were 10.81 ±20.631. Among men with no history of fractures, the levels of P1NP (N=221) were 48.498±52.892, CTX (N=201) were 0.370±0.351, and osteocalcin (N=15) were 7.868 ±10.674. Treatment with teriparatide increased the P1NP levels after 3 months in both men and women, with a 50% increase observed in women. Similarly, treatment with denosumab decreased the CTX levels after 3 months in both men and women, with a reduction of 50% observed in women. CONCLUSIONS: The results of this study can contribute to the accurate assessment of bone replacement status in Koreans. We also provide the P1NP level in the Korean population for future comparative studies with other populations.

Analysis of Changes in Sleep Quality and Patterns after Hip Fracture Using Real Evidence of Artificial Intelligence Linked (REAL) Hip Cohort Data.

Background and Objectives: Hip fractures are commonly found in elderly patients, and often result in chronic pain and decreased physical function, as well as worsening of overall health. It is known that early surgical intervention during the acute phase and rehabilitation are important for improving clinical outcomes for these patients. However, the importance of management for improving the quality of life of these patients is becoming more emphasized. Studies on changes in sleep patterns after hip fractures are rare overseas. Therefore, the aim of this study is to investigate the prevalence of sleep disturbance in patients with hip fractures and to analyze the changes in sleep disturbance after surgery by comparing the preoperative and postoperative results. Materials and Methods: During the period from August 2022 to January 2023, patients who underwent surgical treatment for hip fractures and were recruited into the REAL Hip Cohort were selected as research subjects. The sleep survey was conducted using the Pittsburgh Sleep Quality Index (PSQI). The PSQI is composed of 18 questions, each divided into areas of sleep quality, sleep latency, duration, efficiency, disturbance, use of medication, and daytime dysfunction. Each area is scored 0-3 points and the total is 0-21. A score greater than five indicates sleep disorder. The PSQI was surveyed during hospitalization and three months after surgery for post-fracture sleep status. To analyze changes before and after the fracture, paired T-tests and chi-square tests were performed. Results: From August 2022 to January 2023, a total of 40 patients who were recruited into the REAL Hip Cohort responded to the PSQI survey. The average age was 77.4 years and 36 were female. Sleep quality worsened from 0.75 ± 1.0 before surgery to 1.4 ± 1.0 three months after surgery (p = 0.019), and sleep efficiency also worsened from 0.4 ± 0.6 to 1.4 ± 1.0 (p < 0.001). The PSQI increased from an average of 5.2 ± 2.8 before surgery to 8.2 ± 4.2 three months after surgery (p = 0.007), and the number of patients who could be diagnosed with sleep disorders also increased from 12 (40%) to 24 (60%) (p = 0.030). Conclusions: A decline in overall sleep status was observed in patients in a survey on sleep patterns three months after hip fracture. Additional management is needed to improve their sleep patterns.

Development of droplet digital PCR-based detection of bacterial pathogens in prosthetic joint infection: a preliminary study using a synthesized model plasmid.

Periprosthetic joint infection (PJI) can be diagnosed to characterize the microorganisms constituting a biofilm, which is an essential procedure for proper treatment. The gold standard method for detecting and identifying the causative microorganism is culture of microorganisms from patients-derived sample.; however, this method takes a long time and has low sensitivity. To compensate for these limitations, identification methods based on real-time PCR (RT-PCR) have been widely used. However, RT-PCR also has limitations, including low sensitivity and the requirement of a standard curve for quantification. Therefore, to prevent significant proliferation of pathogenic bacteria, it is important to detect a limited number of infectious bacteria during early stages of PJI. In the present study, we developed droplet digital PCR-based detection of bacterial pathogens in PJI. And we evaluated the analytical performance of the assay using a model plasmid, based on the 16S ribosomal DNA sequence of target bacteria commonly found in PJI. We also prepared genomic DNA extracted from E. coli, S. aureus, and S. epidermidis to test whether ddPCR provides better sensitivity and quantification of the target sequences. ddPCR detected 400 attograms of target DNA, which was more than 10 times less than that detected by real-time PCR using synthesized plasmid. In addition, ddPCR detected target regions from genomic DNA of 50 femtograms for E. coli, 70 femtograms for S. epidermidis, and 90 femtograms for S. aureus. The results indicate that ddPCR has the potential to decrease the microbial detection limit and provide precise detection, signifying its effectiveness for early PJI.

The Influences of Macronutrients on Bone Mineral Density, Bone Turnover Markers, and Fracture Risk in Elderly People: A Review of Human Studies.

Osteoporosis is a health condition that involves weak bone mass and a deteriorated microstructure, which consequently lead to an increased risk of bone fractures with age. In elderly people, a fracture attributable to osteoporosis elevates mortality. The objective of this review was to examine the effects of macronutrients on bone mineral density (BMD), bone turnover markers (BTMs), and bone fracture in elderly people based on human studies. A systematic search was conducted in the PubMed®/MEDLINE® database. We included human studies published up to April 2023 that investigated the association between macronutrient intake and bone health outcomes. A total of 11 meta-analyses and 127 individual human studies were included after screening the records. Carbohydrate consumption seemed to have neutral effects on bone fracture in limited studies, but human studies on carbohydrates' effects on BMD or/and BTMs are needed. The human studies analyzed herein did not clearly show whether the intake of animal, vegetable, soy, or milk basic proteins has beneficial effects on bone health due to inconsistent results. Moreover, several individual human studies indicated an association between eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and osteocalcin. Further studies are required to draw a clear association between macronutrients and bone health in elderly people.

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis.

BACKGROUND: The relationship between physical function, musculoskeletal disorders and sarcopenia is intricate. Current physical function tests, such as the gait speed test and the chair stand test, have limitations in eliminating subjective influences. To overcome this, smart devices utilizing inertial measurement unit sensors and artificial intelligence (AI)-based methods are being developed. METHODS: We employed cutting-edge technologies, including the smart insole device and pose estimation based on AI, along with three classification models: random forest (RF), support vector machine and artificial neural network, to classify control and sarcopenia groups. Patient data of 83 individuals were divided into train and test sets, with approximately 67% allocated for training. Classification models were implemented using RStudio, considering individual and combined variables obtained through pose estimation and smart insole measurements. RESULTS: Performance evaluation of the classification models utilized accuracy, precision, recall and F1-score indicators. Using only pose estimation variables, accuracy ranged from 0.92 to 0.96, with F1-scores of 0.94-0.97. Key variables identified by the RF model were 'Hip_dif', 'Ankle_dif' and 'Hipankle_dif'. Combining variables from both methods increased accuracy to 0.80-1.00, with F1-scores of 0.73-1.00. CONCLUSIONS: In our study, a classification model that integrates smart insole and pose estimation technology was assessed. The RF model showed impressive results, particularly in the case of the Hip and Ankle variables. The growth of advanced measurement technologies suggests a promising avenue for identifying and utilizing additional digital biomarkers in the management of various disorders. The convergence of AI technologies with diagnostics and treatment approaches a promising future for enhanced interventions in conditions like sarcopenia.

Effect of Artificial Intelligence or Machine Learning on Prediction of Hip Fracture Risk: Systematic Review.

BACKGROUND: Dual energy X-ray absorptiometry (DXA) is a preferred modality for screening or diagnosis of osteoporosis and can predict the risk of hip fracture. However, the DXA test is difficult to implement easily in some developing countries, and fractures have been observed before patients underwent DXA. The purpose of this systematic review is to search for studies that predict the risk of hip fracture using artificial intelligence (AI) or machine learning, organize the results of each study, and analyze the usefulness of this technology. METHODS: The PubMed, OVID Medline, Cochrane Collaboration Library, Web of Science, EMBASE, and AHRQ databases were searched including "hip fractures" AND "artificial intelligence". RESULTS: A total of 7 studies are included in this study. The total number of subjects included in the 7 studies was 330,099. There were 3 studies that included only women, and 4 studies included both men and women. One study conducted AI training after 1:1 matching between fractured and non-fractured patients. The area under the curve of AI prediction model for hip fracture risk was 0.39 to 0.96. The accuracy of AI prediction model for hip fracture risk was 70.26% to 90%. CONCLUSIONS: We believe that predicting the risk of hip fracture by the AI model will help select patients with high fracture risk among osteoporosis patients. However, to apply the AI model to the prediction of hip fracture risk in clinical situations, it is necessary to identify the characteristics of the dataset and AI model and use it after performing appropriate validation.

Osteoporosis Feature Selection and Risk Prediction Model by Machine Learning Using a Cross-Sectional Database.

BACKGROUND: The purpose of this study was to verify the accuracy and validity of using machine learning (ML) to select risk factors, to discriminate differences in feature selection by ML between men and women, and to develop predictive models for patients with osteoporosis in a big database. METHODS: The data on 968 observed features from a total of 3,484 the Korea National Health and Nutrition Examination Survey participants were collected. To find preliminary features that were well-related to osteoporosis, logistic regression, random forest, gradient boosting, adaptive boosting, and support vector machine were used. RESULTS: In osteoporosis feature selection by 5 ML models in this study, the most selected variables as risk factors in men and women were body mass index, monthly alcohol consumption, and dietary surveys. However, differences between men and women in osteoporosis feature selection by ML models were age, smoking, and blood glucose level. The receiver operating characteristic (ROC) analysis revealed that the area under the ROC curve for each ML model was not significantly different for either gender. CONCLUSIONS: ML performed a feature selection of osteoporosis, considering hidden differences between men and women. The present study considers the preprocessing of input data and the feature selection process as well as the ML technique to be important factors for the accuracy of the osteoporosis prediction model.

Relationship between DNA methylation changes and skeletal muscle mass.

BACKGROUND: Sarcopenia is a disease diagnosed in the elderly. In patients with sarcopenia, the muscle mass decreases every year. The occurrence of sarcopenia is greatly affected by extrinsic factors such as eating habits, exercise, and lifestyle. The present study aimed to determine the relationship between muscle mass traits and genes affected by epigenetic factors with three different adjustment methods using Korean Genome and Epidemiology Study (KOGES) data. RESULTS: We conducted a demographic study and DNA methylation profiling by three studies according to the muscle mass index (MMI) adjustment methods: appendicular skeletal muscle mass divided by body weight (MMI1); appendicular skeletal muscle mass divided by square of height (MMI2); appendicular skeletal muscle mass divided by BMI (MMI3). We analyzed differentially methylated regions (DMRs) for each group. We then restricted our subjects to be top 30% (T30) and bottom 30% (B30) based on each MMI adjustment method. Additionally, we performed enrichment analysis using PathfindR to evaluate the relationship between identified DMRs and sarcopenia. A total of 895 subjects were included in the demographic study. The values of BMI, waist, and hip showed a significant difference in all three groups. Among 446 participants, 44 subjects whose DNA methylation profiles were investigated were included for DNA methylation analysis. The results of enrichment analysis showed differences between groups. In the women group through MMI1 method, only the glutamatergic synapse pathway showed a significant result. In the men group through MMI2 method, the adherens junction pathway was the most significant. Women group through MMI2 method showed similar results, having an enriched Rap1 signaling pathway. In men group through MMI3 method, the Fc epsilon RI signaling pathway was the most enriched. Particularly, the notch signaling pathway was significantly enriched in women group through MMI3 method. CONCLUSION: This study presents results about which factor should be concerned first in muscle mass index (MMI) adjustment. The present study suggested that GAB2 and JPH3 in MMI1 method, HLA-DQB1 and TBCD in MMI2 method, GAB2, NDUFB4 and ISPD in MMI3 method are potential genes that can have an impact on muscle mass. It could enable future epigenetic studies of genes based on annotation results. The present study is a nationwide study in Korea with the largest size up to date that compares adjustment indices for MMI in epigenetic research.

Effectiveness of Weekly Teriparatide Injection in Postmenopausal Patients with Hip Fractures.

Background: Teriparatide is an effective anabolic agent used in the treatment of severe osteoporosis. In addition, it is also used to promote fracture healing. The purpose of this double-blind randomized controlled trial was to evaluate the influence of weekly teriparatide administration on bone formation in hip fracture patients. Methods: The control group (n = 41) was composed of patients treated with normal saline other than teriparatide, and the teriparatide group (n = 51) consisted of patients who received weekly teriparatide. Bone turnover markers, C-terminal telopeptide (CTx) and osteocalcin (OC), were assessed through blood tests at the initial hospital visit and 3-month, 6-month, and 1-year follow-ups. Dual-energy X-ray absorptiometry was performed 5 days postoperatively and at 1-year postoperative follow-up. The degree of fracture union was evaluated by comparing the radiographic union scoring system for hips using Radiographic Union Score for Hip (RUSH) scores between the two groups at 3 months, 6 months, and 1 year after surgery. Results: Evaluation of the rate of change in bone mineral density over 1 year showed that the lumber bone mineral density increased by more than 7% in the experimental group. The control group did not show a difference between the CTx and OC at 6 months, but the difference between the CTx and OC values was large at 6 months in the experimental group. The mean RUSH score was significantly different between the control group and the experimental group: 12.105 and 15.476, respectively (p = 0.004), at 3 months and 18.571 and 22.389, respectively, at 6 months (p = 0.006). Conclusions: Weekly use of teriparatide improved fracture healing, bone formation, and clinical outcomes at 1 year after hip fracture surgery by the anabolic window effect.

Clinical and Radiological Characteristics of Lesser Trochanter Splitting Irreducible Intertrochanteric Fractures.

Background: The purpose of this study was to investigate the demographic factors and radiological characteristics of lesser trochanter splitting (LTS) irreducible intertrochanteric fractures and to report the clinical results of patients who underwent open reduction and internal fixation using dynamic hip screws (DHS). Methods: Inclusion criteria were as follows: AO/Orthopedic Trauma Association type 31A1.2, a fracture line originating from the outside of the greater trochanter that passes through the lesser trochanter, and patients who were followed up for more than 1 year with a confirmed presence or absence of bone union. A total of 13 cases were identified, accounting for 3.1% (13/416 intertrochanteric fractures). Patients were classified according to posterior sagging of the distal shaft fragment relative to the head-neck fragment (posterior sagging group, 6; non-sagging group, 7). Demographic data, comorbidities, injury mechanism, type of anesthesia, operation time, blood loss, tip-apex distance, reduction quality, leg length discrepancy (> 5 mm), long lesser trochanter sign, postoperative complications, and presence of bony union were obtained by reviewing medical records and radiological findings. Results: The mean age of the patients was 50.4 ± 10.4 years, and 12 were men. Except for 1 case (slip down), all were induced by high-energy trauma. According to the grade of reduction quality, 5 cases (38.5%) had good reduction quality and 8 cases (61.5%) had acceptable reduction quality. There were no postoperative complications, and bony union was observed in all cases. The long lesser trochanter sign was observed in 5 cases (38.5%) and leg length discrepancy greater than 5 mm was not observed. Compared with the non-sagging group, the posterior sagging group had more head-neck fragments containing more than 1/2 of the lesser trochanter length, longer operation time, and more blood loss (p < 0.05). Compared to the non-sagging group, the posterior sagging group had worse reduction quality and more long lesser trochanter signs (p < 0.05). Conclusions: Open reduction and internal fixation using DHS for the LTS irreducible intertrochanteric fractures can achieve good clinical and radiological outcomes. However, in the posterior sagging type, reduction can be more difficult with a longer operation time and higher likelihood of blood loss.

Prevalence of Sarcopenia in Africa: A Systematic Review.

Objective: The world population gradually getting older, age-related sarcopenia is becoming more frequent. Known to be highly prevalent in high income countries, relative data in Africa are still scarce. This review aims to estimate the prevalence of sarcopenia in Africa and its characteristics. Study Design and Setting: A literature search in PubMed, Web of Science, Google Scholar, and Scopus was conducted in October 2022. All studies reporting the prevalence of sarcopenia in Africa within 15 years were included, and we did an assessment of bias with Hoy et al's risk bias assessment tool. The estimated prevalence of sarcopenia was the outcome and we performed secondary analyses by age, gender, and diagnostic criteria. The random effect model was used for the prevalence estimation. The prevalence of sarcopenia and 95% confidence interval (95% CI) were calculated using the inverse-variance method. Results: A total of 17 studies met our eligibility criteria, for a study population of 12,690 participants with 44.3% males and 55.7% females. The overall prevalence of sarcopenia was 25% (95% CI: 19-30%). The prevalence of sarcopenia among 50 years old and older was 23% (95% CI: 17-29%). We had a higher prevalence of sarcopenia among males (30%, %95 IC: 20-39%) than females (29%, %95 IC: 21-36%). The prevalence of sarcopenia was different depending on the diagnosis criteria used. Conclusion: The prevalence of sarcopenia in Africa was relatively high. However, the fact that the majority of included studies were hospital-based studies shows the necessity of further community-based studies in order to have a more accurate representation of the situation in the general population.

Effects of Bazedoxifene/Vitamin D Combination Therapy on Serum Vitamin D Levels and Bone Turnover Markers in Postmenopausal Women with Osteopenia: A Randomized Controlled Trial.

BACKGROUND: This study aimed to evaluate the effectiveness of bazedoxifene/vitamin D combination therapy in preventing osteoporosis in postmenopausal women with osteopenia. METHODS: This was an open-label, multicenter randomized-controlled, phase 4 clinical trial. Women between ages of 55 and 70 years in 9 medical tertiary centers in Korea were enrolled and assigned into 2 groups: an experiment group and a control group. The experimental group received bazedoxifene 20 mg/vitamin D 800 IU tablets for 6 months, and the control group received calcium 100 mg/vitamin D 1,000 IU tablets for 6 months. RESULTS: A total of 142 patients (70 in the experimental group and 72 in the control group) were included. The least-square mean±standard error of change in propeptide of type I collagen after 3 months was -6.87±2.56% in the experimental group and 1.22±2.54% in the control group. After 6 months, it was -21.07±2.75% in the experimental group and 1.26±2.71% in the control group. The difference between the 2 groups was -22.33% (p<0.01). The change of C-terminal telopeptide was -12.55±4.05% in the experimental group and 11.02±4.03% in the control group after 3 months. It was -22.0±3.95% and 10.20±3.89, respectively, after 6 months. The difference between the 2 groups was -32.21% (p<0.01) after 6 months. There was no significant difference in adverse events between the 2 groups. CONCLUSIONS: The osteoporosis preventive effect and safety of administering bazedoxifene/vitamin D combination pill were confirmed in postmenopausal women who needed osteoporosis prevention.

Trajectory of bolt and length of plate in femoral neck system determine the stability of femur neck fracture and risk of subsequent subtrochanteric fracture : a finite element analysis.

BACKGROUND: This study aimed to analyze the differences in the stability of fractures, stress distribution around the distal-most screw according to the length of the plate and the trajectory of the bolt in Pauwels type III femoral neck fracture using the femoral neck system (FNS). METHODS: Finite element models of Pauwels type III femoral neck fractures were established with surgical variations in the trajectory of the bolt (central, inferior, valgus, and varus) and length of the lateral plate (1- and 2-hole plate). The models were subsequently subjected to normal walking and stair-climbing loads. RESULTS: The screw-holding cortical bone in subtrochanter in the model with a 2-hole plate and the bolt in the inferior trajectory and the models with 1-hole or 2-hole plate and the bolt in valgus trajectory had shown greater maximum principal strain than the models with central or varus trajectories. The gap and sliding distance on the fracture surface were larger with inferior or varus trajectories of the bolt and smaller with the valgus trajectory of the bolt under both loads, compared to those of the central trajectory. CONCLUSION: For the fixation of Pauwels type III femoral neck fracture, the trajectory of the FNS bolt and the length of the plate affect the mechanical stability of the fracture and the strain of cortical bone around the distal-most screw. The surgical target should stay on the central trajectory of the bolt and the 2-hole plate's mechanical benefits did not exceed the risk.

Pre-sliding of femoral neck system improves fixation stability in pauwels type III femoral neck fracture: a finite element analysis.

BACKGROUND: Femoral neck fractures are a common injury in older adults and their management presents a significant challenge for orthopedic surgeons. The Femoral Neck System (FNS) was recently introduced for the fixation of femur neck fractures. Although neck shortening was reduced with the FNS, the complication rates were not reduced. Thus, improvements to enhance fixation stability should be made for the FNS. We hypothesized that (1) the pre-sliding technique and (2) the use of longer anti-rotation screw would increase fracture stability. This study aimed to determine the change in fracture stability using the pre-sliding technique and long anti-rotation screw in the FNS for fixation of Pauwels type III femoral neck fractures. METHODS: Finite element models of Pauwels type III femoral neck fracture fixed with pre-sliding FNS and 5-mm longer anti-rotation screw were established. The models were subjected to normal walking load. The material properties of the elements belonging to the bone were mapped by assigning the formulation with the computed tomography Hounsfield unit. RESULTS: Pauwels type III femoral neck fractures fixed with pre-slided FNS showed better fracture stability, decreasing fracture gap and sliding by 14% and 12%, respectively, under normal walking load. No element of cortical bone in any of the models had an absolute value of principal strain that exceeded 1%. The peak von Mises stress (VMS) of the implants ranged from 260 to 289 MPa, and the highest peak VMS value was 50% lower than the yield strength of the titanium alloy (800 MPa). The longer anti-rotation screw did not affect fracture stability. CONCLUSIONS: The pre-sliding technique using the FNS showed higher fracture stability than the standard fixation technique for a Pauwels type III femoral neck fracture. The longer anti-rotation screw did not contribute significantly to fixation stability. As this finite element analysis considered the inhomogeneous mechanical property of the bone, it offered equivalent mechanical conditions to investigate the components of interest.