A Study on Intelligent Optical Bone Densitometry.

Osteoporosis is a prevalent chronic disease worldwide, particularly affecting the aging population. The gold standard diagnostic tool for osteoporosis is Dual-energy X-ray Absorptiometry (DXA). However, the expensive cost of the DXA machine and the need for skilled professionals to operate it restrict its accessibility to the general public. This paper builds upon previous research and proposes a novel approach for rapidly screening bone density. The method involves utilizing near-infrared light to capture local body information within the human body. Deep learning techniques are employed to analyze the obtained data and extract meaningful insights related to bone density. Our initial prediction, utilizing multi-linear regression, demonstrated a strong correlation (r = 0.98, p-value = 0.003**) with the measured Bone Mineral Density (BMD) obtained from Dual-energy X-ray Absorptiometry (DXA). This indicates a highly significant relationship between the predicted values and the actual BMD measurements. A deep learning-based algorithm is applied to analyze the underlying information further to predict bone density at the wrist, hip, and spine. The prediction of bone densities in the hip and spine holds significant importance due to their status as gold-standard sites for assessing an individual's bone density. Our prediction rate had an error margin below 10% for the wrist and below 20% for the hip and spine bone density.

Development and experimental validation of an energy metabolism-related gene signature for diagnosing of osteoporosis.

Osteoporosis is usually caused by excessive bone resorption and energy metabolism plays a critical role in the development of osteoporosis. However, little is known about the role of energy metabolism-related genes in osteoporosis. This study aimed to explore the important energy metabolism-related genes involved in the development of osteoporosis and develop a diagnosis signature for osteoporosis. The GSE56814, GSE62402, and GSE7158 datasets were downloaded from the NCBI Gene Expression Omnibus. The intersection of differentially expressed genes between high and low levels of body mineral density (BMD) and genes related to energy metabolism were screened as differentially expressed energy metabolism genes (DE-EMGs). Subsequently, a DE-EMG-based diagnostic model was constructed and differential expression of genes in the model was validated by RT-qPCR. Furthermore, a receiver operating characteristic curve and nomogram model were constructed to evaluate the predictive ability of the diagnostic model. Finally, the immune cell types in the merged samples and networks associated with the selected optimal DE-EMGs were constructed. A total of 72 overlapped genes were selected as DE-EMGs, and a five DE-EMG based diagnostic model consisting B4GALT4, ADH4, ACAD11, B4GALT2, and PPP1R3C was established. The areas under the curve of the five genes in the merged training dataset and B4GALT2 in the validation dataset were 0.784 and 0.790, respectively. Moreover, good prognostic prediction ability was observed using the nomogram model (C index = 0.9201; P = 5.507e-14). Significant differences were observed in five immune cell types between the high- and low-BMD groups. These included central memory, effector memory, and activated CD8 T cells, as well as regulatory T cells and activated B cells. A network related to DE-EMGs was constructed, including hsa-miR-23b-3p, DANCR, 17 small-molecule drugs, and two Kyoto Encyclopedia of Genes and Genomes pathways, including metabolic pathways and pyruvate metabolism. Our findings highlighted the important roles of DE-EMGs in the development of osteoporosis. Furthermore, the DANCR/hsa-miR-23b-3p/B4GALT4 axis might provide novel molecular insights into the process of osteoporosis development.

Raman spectroscopic analysis for osteoporosis identification in humans with hip fractures.

Osteoporosis is a significant health concern. While multiple techniques have been utilized to diagnose this condition, certain limitations still persist. Raman spectroscopy has shown promise in predicting bone strength in animal models, but its application to humans requires further investigation. In this study, we present an in vitro approach for predicting osteoporosis in 10 patients with hip fractures using Raman spectroscopy. Raman spectra were acquired from exposed femoral heads collected during surgery. Employing a leave-one-out cross-validated linear discriminant analysis (LOOCV-LDA), we achieved accurate classification (90 %) between osteoporotic and osteopenia groups. Additionally, a LOOCV partial least squares regression (PLSR) analysis based on the complete Raman spectra demonstrated a significant prediction (r2 = 0.84, p < 0.05) of bone mineral density as measured by dual X-ray absorptiometry (DXA). To the best of our knowledge, this study represents the first successful demonstration of Raman spectroscopy correlating with osteoporotic status in humans.

Development of a program theory for osteoporosis patient education in Denmark: a qualitative study based on realist evaluation.

BACKGROUND: Osteoporosis patient education is offered in many countries worldwide. When evaluating complex interventions like these, it is important to understand how and why the intervention leads to effects. This study aimed to develop a program theory of osteoporosis patient education in Danish municipalities with a focus on examining the mechanisms of change i.e. what is about the programs that generate change. METHODS: The program theory was developed in an iterative process. The initial draft was based on a previous published systematic review, and subsequently the draft was continually refined based on findings from observations (10 h during osteoporosis patient education) and interviews (individual interviews with six employees in municipalities and three health professionals at hospitals, as well as four focus group interviews with participants in patient education (in total 27 informants)). The transcribed interviews were analyzed using thematic analysis and with inspiration from realist evaluation the mechanisms as well as the contextual factors and outcomes were examined. RESULTS: Based on this qualitative study we developed a program theory of osteoporosis patient education and identified four mechanisms: motivation, recognizability, reassurance, and peer reflection. For each mechanism we examined how contextual factors activated the mechanism as well as which outcomes were achieved. For instance, the participants' motivation is activated when they meet in groups, and thereafter outcomes such as more physical activity may be achieved. Recognizability is activated by the participants' course of disease, which may lead to better ergonomic habits. Reassurance may result in more physical activity, and this mechanism is activated in newly diagnosed participants without previous fractures. Peer reflection is activated when the participants meet in groups, and the outcome healthier diet may be achieved. CONCLUSIONS: We developed a program theory and examined how and why osteoporosis patient education is likely to be effective. Understanding these prerequisites is important for future implementation and evaluation of osteoporosis patient education.

[Expert consensus on integrated traditional Chinese and western medicine diagnosis and treatment for osteoporotic fractures].

Osteoporotic fractures represent the most severe complications of osteoporosis,characterized by insidious onset,high mortality and disability rates,and a steadily increasing incidence,imposing a significant socioeconomic burden. Western medicine has advantages in diagnosis and surgical interventions,while traditional Chinese medicine excels in holistic management and the restoration of bodily equilibrium. The integration of both traditional Chinese medicine (TCM) and western medicine emerges as an effective therapeutic strategy for osteoporotic fractures. In order to propagate the concept of integrated diagnosis and treatment,foster the advancement of integrated medical techniques for osteoporotic fractures,and establish standardized and normative protocols for disease prevention,diagnosis,and treatment,a consensus expert group,led by Geriatric Branch of Chinese Geriatrics Society,the Young Osteoporosis Group of Orthopedics Branch of Chinese Medical Association,Osteoporosis Group of Orthopedics Branch of Chinese Physician Association,and Osteoporosis Professional Committee of the Shanghai Society of Integrated Traditional Chinese and Western Medicine,was established. This group engaged in deliberations and formulated the "Expert Consensus on Integrated Traditional Chinese and Western Medicine Diagnosis and Treatment of Osteoporotic Fractures" elucidating the concept of integrated medicine and offering recommendations in the domains of prevention,diagnosis,and treatment,with the aspiration of ameliorating the prognosis of osteoporotic fractures and enhancing the quality of life for these patients.

Challenges of fracture risk assessment in Asian and Black women.

OBJECTIVES: Bone mineral density (BMD) and fracture risk calculators (eg, the Fracture Risk Assessment Tool [FRAX]) guide primary prevention care in postmenopausal women. BMD scores use non-Hispanic White (NHW) reference data for T-score classification, whereas FRAX incorporates BMD, clinical risk factors, and population differences when calculating risk. This study compares findings among Asian, Black, and NHW women who underwent osteoporosis screening in a US health care system. STUDY DESIGN: Retrospective cross-sectional study. METHODS: Asian, Black, and NHW women aged 65 to 75 years who underwent BMD testing (with no recent fracture, osteoporosis therapy, metastatic cancer, multiple myeloma, metabolic bone disorders, or kidney replacement therapy) were compared across the following measures: femoral neck BMD (FN-BMD) T-score (normal ≥ -1, osteoporosis ≤ -2.5), high FRAX 10-year hip fracture risk (FRAX-Hip ≥ 3%), FRAX risk factors, and diabetes status. RESULTS: Among 3640 Asian women, 23.8% had osteoporosis and 8.7% had FRAX-Hip scores of at least 3% (34.5% among those with osteoporosis). Among 11,711 NHW women, 12.3% had osteoporosis and 17.2% had FRAX-Hip scores of at least 3% (84.8% among those with osteoporosis). Among 1711 Black women, 68.1% had normal FN-BMD, 4.1% had BMD-defined osteoporosis, and 1.8% had FRAX-Hip scores of at least 3% (32.4% among those with osteoporosis). Fracture risk factors differed by group. Diabetes was 2-fold more prevalent in Black and Asian (35% and 36%, respectively) vs NHW (16%) women. CONCLUSIONS: A large subset of Asian women have discordant BMD and FRAX scores, presenting challenges in osteoporosis management. Furthermore, FN-BMD and especially FRAX scores identified few Black women at high fracture risk warranting treatment. Studies should examine whether fracture risk assessment can be optimized in understudied racial minority populations, particularly when findings are discordant.

Optimising health after early menopause.

The typical age at menopause is 50-51 years in high-income countries. However, early menopause is common, with around 8% of women in high-income countries and 12% of women globally experiencing menopause between the ages of 40 years and 44 years. Menopause before age 40 years (premature ovarian insufficiency) affects an additional 2-4% of women. Both early menopause and premature ovarian insufficiency can herald an increased risk of chronic disease, including osteoporosis and cardiovascular disease. People who enter menopause at younger ages might also experience distress and feel less supported than those who reach menopause at the average age. Clinical practice guidelines are available for the diagnosis and management of premature ovarian insufficiency, but there is a gap in clinical guidance for early menopause. We argue that instead of distinct age thresholds being applied, early menopause should be seen on a spectrum between premature ovarian insufficiency and menopause at the average age. This Series paper presents evidence for the short-term and long-term consequences of early menopause. We offer a practical framework for clinicians to guide diagnosis and management of early menopause, which considers the nature and severity of symptoms, age and medical history, and the individual's wishes and priorities to optimise their quality of life and short-term and long-term health. We conclude with recommendations for future research to address key gaps in the current evidence.

Enhancing 3D DNA Walker-Induced CRISPR/Cas12a Technology for Highly Sensitive Detection of ExomicroRNA Associated with Osteoporosis.

Exosomal microRNAs (exomiRNAs) have emerged as promising biomarkers for the early clinical diagnosis of osteoporosis. However, their limited abundance and short length in peripheral blood present significant challenges for the accurate detection of exomiRNAs. Herein, we have designed and implemented an efficacious fluorescence-based biosensor for the highly sensitive detection of exomiRNA associated with osteoporosis, leveraging the enhancing 3D DNA walker-induced CRISPR/Cas12a technology. The engineered DNA walker is capable of efficiently transforming target exomiRNA into amplifying DNA strands, thereby enhancing the sensitivity of the developed biosensor. Concurrently, the liberated DNA strands serve as activators to trigger Cas12a trans-cleavage activity, culminating in a significantly amplified fluorescent signal for the highly sensitive detection of exomiRNA-214. Under optimal conditions, the devised technology demonstrated the capacity to detect target exomiRNA-214 at concentrations as low as 20.42 fM, encompassing a wide linear range extending from 50.0 fM to 10.0 nM. Moreover, the fluorescence-based biosensor could accurately differentiate between healthy individuals and osteoporosis patients via the detection of exomiRNA-214, which was in agreement with RT-qPCR results. As such, this biosensing technology offers promise as a valuable tool for the early diagnosis of osteoporosis.

Knowledge and Awareness of Osteoporosis: A Survey of Physical Therapy Providers in Saudi Arabia.

Background: Osteoporosis "OP" is classified as one of the most serious health conditions worldwide. OP increases the skeletal fracture risk by 35%, particularly at hip, spine, and wrist joints. Healthcare professionals should be aware of OP clinical signs and have good knowledge while managing all patients. Objectives: This study aims to investigate the current level of osteoporosis knowledge and awareness among physical therapy providers in Saudi Arabia. Methods: One hundred and sixty-eight physical therapy providers participated in this cross-sectional electronic survey from February to July of 2021. The participants completed the Osteoporosis Knowledge Assessment Tool questionnaire (OKAT). Descriptive analysis was utilized to assess the current level of osteoporosis knowledge among physical therapy providers. Results: Among the 168 participants, 55% (n = 92) were over 31 years old and 45% (n = 76) were 30 years old or under. The majority of participants 37% (n = 62) had more than 10 years of experience, 45% (n = 76) mainly treat orthopedic conditions, and 70% (n = 117) live in the western region. The results showed that 67.9% (n = 114) of participants had good knowledge about osteoporosis, while 19.6% (n = 33) had poor knowledge, and only 12.5% (n = 21) had excellent knowledge. Conclusion: Physical therapy providers in Saudi Arabia have a good knowledge of osteoporosis. The overall OP preventive measure knowledge questions were poor. It is crucial for physical therapy providers to act appropriately to prevent falls and mitigate any potential risks.

[Secondary fracture prevention/Update osteoporosis guidelines 2023 of the Umbrella Organization Osteology]. / Sekundäre Frakturprävention/Update Leitlinie Osteoporose 2023 des Dachverbandes Osteologie.

The S3 guidelines on the prophylaxis, diagnostics and treatment of osteoporosis 2023 were completely revised and updated between 2021 and 2023 in accordance with the Association of the Scientific Medical Societies of Germany (AWMF) regulations. The guideline committee consisted of delegates from the 20 specialist societies of the Umbrella Organization Osteology (Dachverband Osteologie, DVO) as well as delegates from the German Society of General Medicine and Family Medicine (DEGAM), the German Society for Nephrology (DGfN) and the Federal Self-help Association for Osteoporosis (BfO).The guidelines focus on preventive measures, diagnostic procedures and treatment approaches for osteoporosis in men aged 50 years and over and postmenopausal women. The main aim is the optimization of care processes, reduction of fracture incidences and maintenance or improvement of the quality of life and functional capacity of patients affected by fractures. A major update to the guidelines includes the introduction of a new risk calculator that can take more risk factors (n = 33) into account and that can estimate the risk of vertebral body and proximal femoral fractures for a 3-year period (previously 10 years). This results in new thresholds for diagnostics and treatment. The programmed app is currently not yet certified as a medical product and a paper version is therefore currently available for patient care with the planned integration of a web-based version of the risk calculator. From the perspective of trauma surgery, the recommendations and innovations for manifest osteoporosis are of particular clinical importance. The focus of the DVO guidelines update is therefore on the implementation of secondary fracture prevention in trauma surgery, orthopedic and geriatric traumatology in the clinical and practical daily routine.

Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data.

Osteoporosis is a major public health concern that significantly increases the risk of fractures. The aim of this study was to develop a Machine Learning based predictive model to screen individuals at high risk of osteoporosis based on chronic disease data, thus facilitating early detection and personalized management. A total of 10,000 complete patient records of primary healthcare data in the German Disease Analyzer database (IMS HEALTH) were included, of which 1293 diagnosed with osteoporosis and 8707 without the condition. The demographic characteristics and chronic disease data, including age, gender, lipid disorder, cancer, COPD, hypertension, heart failure, CHD, diabetes, chronic kidney disease, and stroke were collected from electronic health records. Ten different machine learning algorithms were employed to construct the predictive mode. The performance of the model was further validated and the relative importance of features in the model was analyzed. Out of the ten machine learning algorithms, the Stacker model based on Logistic Regression, AdaBoost Classifier, and Gradient Boosting Classifier demonstrated superior performance. The Stacker model demonstrated excellent performance through ten-fold cross-validation on the training set and ROC curve analysis on the test set. The confusion matrix, lift curve and calibration curves indicated that the Stacker model had optimal clinical utility. Further analysis on feature importance highlighted age, gender, lipid metabolism disorders, cancer, and COPD as the top five influential variables. In this study, a predictive model for osteoporosis based on chronic disease data was developed using machine learning. The model shows great potential in early detection and risk stratification of osteoporosis, ultimately facilitating personalized prevention and management strategies.

The yield of routine laboratory examination in osteoporosis evaluation in primary care.

This study evaluated the yield of routine laboratory examination in a large population of older women in primary care. The prevalence of laboratory abnormalities was low and the clinical consequences in follow-up were limited. There was a weak association of laboratory abnormalities with osteoporosis but no association with vertebral fractures and recent fractures. PURPOSE: Most osteoporosis guidelines advice routine laboratory examination. We have investigated the yield of laboratory examinations in facture risk evaluation of elderly women in primary care. METHODS: We assessed the prevalence of laboratory abnormalities and their association with risk factors for fractures, recent fractures, low bone mineral density (BMD), and prevalent vertebral fracture in 8996 women ≥ 65 years of age participating in a primary care fracture risk screening study. In a sample of 2208 of these participants, we also evaluated the medical consequences in the medical records during a follow-up period of ≥ 1 year. RESULTS: Vitamin D deficiency (< 30 nmol/L) was present in 13% and insufficiency (< 50 nmol/L) in 43% of the study sample. The prevalence of other laboratory abnormalities (ESR, calcium, creatinine, FT4) was 4.6% in women with risk factors for fractures, 6.1% in women with low BMD (T-score ≤ - 2.5), 6.0% after a prevalent vertebral fracture, 5.2% after a recent fracture and 2.6% in the absence of important risk factors for fractures. Laboratory abnormalities other than vitamin D were associated with low BMD (OR 1.4, 95%CI 1.1-1.8) but not with prevalent vertebral fractures nor recent fractures. Low BMD was associated with renal failure (OR 2.0, 95%CI 1.3-3.4), vitamin D insufficiency (OR 1.2, 95%CI 1.0-1.3) and deficiency (OR 1.3, 95%CI 1.1-.5). In the follow-up period, 82% of the laboratory abnormalities did not result in a new diagnosis or treatment reported in the medical records. CONCLUSIONS: We identified a low prevalence of laboratory abnormalities in a primary care population of older women and the majority of these findings had no medical consequences.

Evidence-Based Guideline for the management of osteoporosis in men.

Historically, osteoporosis has been viewed as a disease of women, with research, trials of interventions and guidelines predominantly focused as such. It is apparent, however, that this condition causes a substantial health burden in men also, and that its assessment and management must ultimately be addressed across both sexes. In this article, an international multidisciplinary working group of the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases presents GRADE-assessed recommendations for the diagnosis, monitoring and treatment of osteoporosis in men. The recommendations are based on a comprehensive review of the latest research related to diagnostic and screening approaches for osteoporosis and its associated high fracture risk in men, covering disease burden, appropriate interpretation of bone densitometry (including the use of a female reference database for densitometric diagnosis in men) and absolute fracture risk, thresholds for treatment, and interventions that can be used therapeutically and their health economic evaluation. Future work should specifically address the efficacy of anti-osteoporosis medications, including denosumab and bone-forming therapies.

Analysis of related factors for sarco-osteoporosis in middle-aged and elderly inpatients and development and validation of a nomogram.

BACKGROUND: Sarco-osteoporosis is a skeletal muscle disease associated with aging and complex pathological factors. At present, there are few studies on the analysis of its related factors, and a nomogram to estimate the risk of sarco-osteoporosis in middle-aged and elderly patients is not available. METHODS: A total of 386 patients admitted to our hospital from October 2021 to October 2022 were collected, and the general demographic data and clinical data of the patients were collected.386 subjects were enrolled in the study and randomly divided into training set and validation set at a ratio of 7:3. In the training set, the Least absolute shrinkage and selection operator(LASSO)regression technique was used to select the optimal predictive features, and multivariate logistic regression was used to screen the factors associated with sarco-osteoporosis, and a nomogram was constructed using meaningful variables from multivariate analysis. The performance of the nomograms was assessed and validated by Area Under Curve (AUC) and calibration curves. RESULTS: There were no significant differences in baseline characteristic of individuals in training set and validation set, six variables with non-zero coefficients were screened based on LASSO regression in the training set. Multivariate logistic regression analysis showed that the related factors for sarco-osteoporosis in middle-aged and elderly inpatients included age (OR = 1.08, 95%CI 1.03 ∼ 1.14), regular exercise (OR = 0.29, 95%CI 0.15 ∼ 0.56), albumin (OR = 0.9, 95%CI 0.82 ∼ 0.98), height (OR = 0.93, 95%CI 0.88 ∼ 0.99) and lean mass index (OR = 0.66, 95%CI 0.52 ∼ 0.85), and a nomogram was constructed based on the above factors. AUC of nomogram were 0.868(95%CI 0.825 ∼ 0.912) in the training set and 0.737(95%CI 0.646 ∼ 0.828) in the validation set. Calibration curve analysis showed that the predicted probability of sarco-osteoporosis had high consistency with the actual probability, and the absolute error of the training set and verification set was 0.018 and 0.03, respectively. CONCLUSIONS: Our research showed that the occurrence of sarco-osteoporosis was associated with age, regular exercise, albumin, height and lean mass index, and we have developed a nomogram that can be effectively used in the preliminary and in-depth risk prediction of sarco-osteoporosis in middle-aged and elderly hospitalized patients.

Pre-existing osteoporosis and serum vitamin D levels in patients with distal radius fractures: are we missing something?

INTRODUCTION: Given the significant therapeutic gap for osteoporosis, this study aims to investigate the most common osteoporosis-related fracture. The analysis will also consider patients' serum vitamin D levels and the indications for basic osteoporosis diagnostic tests and osteoporosis therapy prior to fracture. MATERIALS AND METHODS: This prospective clinical trial included patients with distal radius fractures who underwent surgery at our hospital between 1 April 2021 and 7 April 2022. Blood samples were taken from all participants and existing risk factors for osteoporosis were recorded. In addition, the indication for a guideline-based osteoporosis diagnosis was assessed and the risk of another future fracture with FRAX® was calculated. This information was used to decide whether there was an indication for specific osteoporosis therapy. RESULTS: A diagnosis gap of 53% and a treatment gap of 84% were identified among the 102 patients investigated. The patients' ages ranged from 46 to 91 years, with an average vitamin D level of 57 nmol/l, which was below the recommended level of 75 nmol/l. It was noted on a monthly basis that the vitamin D level (without substitution) never exceeded the recommended value of 75 nmol/l in any month. Three-quarters of patients had indications for a baseline osteoporosis diagnosis, yet less than 50% received one. According to FRAX® data, 57% of patients had indications for specific osteoporosis treatment before experiencing the fracture. CONCLUSION: Even without a previous distal radius fracture, many patients are in need of osteoporosis diagnosis or treatment. Our research suggests that patients with distal radius fractures should have their vitamin D levels checked via a blood test and be evaluated for osteoporosis. As endogenous vitamin D levels are often inadequate, year-round vitamin D supplementation should be considered for the prevention of osteomalacia and as a basis for the treatment of osteoporosis. GERMAN CLINICAL TRIAL REGISTER ID: DRKS00028085.

PMAIP1, a novel diagnostic and potential therapeutic biomarker in osteoporosis.

BACKGROUND: Osteoporosis is a common endocrine metabolic bone disease, which may lead to severe consequences. However, the unknown molecular mechanism of osteoporosis, the observable side effects of present treatments and the inability to fundamentally improve bone metabolism seriously restrict the impact of prevention and treatment. The study aims to identify potential biomarkers from osteoclast progenitors, specifically peripheral blood monocytes on predicting the osteoporotic phenotype. METHODS: Datasets were obtained from Gene Expression Omnibus (GEO). Based on the differentially expressed genes (DEGs) and GSEA results, GO and KEGG analyses were performed using the DAVID database and Metascape database. PPI network, TF network, drug-gene interaction network, and ceRNA network were established to determine the hub genes. Its osteogenesis, migration, and proliferation abilities in bone marrow mesenchymal stem cells (BMSCs) were validated through RT-qPCR, WB, ALP staining, VK staining, wound healing assay, transwell assay, and CCK-8 assay. RESULTS: A total of 63 significant DEGs were screened. Functional and pathway enrichment analysis discovered that the functions of the significant DEGs (SDEGs) are mainly related to immunity and metal ions. A comprehensive evaluation of all the network analyses, PMAIP1 was defined as osteoporosis's core gene. This conclusion was further confirmed in clinical cohort data. A series of experiments demonstrated that the PMAIP1 gene can promote the osteogenesis, migration and proliferation of BMSC cells. CONCLUSIONS: All of these outcomes showed a new theoretical basis for further research in the treatment of osteoporosis, and PMAIP1 was identified as a potential biomarker for osteoporosis diagnosis and treatment.

Osteoporosis and cement usage in total hip arthroplasty.

PURPOSE: Cement usage in total hip arthroplasty (THA) is increasingly common. However, osteoporosis-related fracture risk in cemented vs uncemented THA patients is poorly characterized. We aim to analyze the usage of metabolic bone care and osteoporosis fracture risk in cemented vs uncemented THA patients using FRAX and radiographic bone measurements. METHODS: Chart review on 250 THA patients was performed retrospectively. Demographics, FRAX scores, hip radiograph measurements, osteoporosis diagnosis, treatment and screening were compared between cemented and uncemented THA patients. Logistic regression model was used to analyze factors influencing cement usage. RESULTS: Cemented THA patients have significantly higher osteoporosis-related fracture risk as measured by FRAX major (20% vs 13%) and FRAX hip (8% vs 5%). There is no significant difference in osteoporosis treatment, vitamin D / calcium supplementation, or metabolic bone disease screening based on patients' cement status. Female sex and rheumatoid arthritis status significantly predict cement usage, but FRAX scores do not predict cement usage. Additionally, 50% (10/20) of patients with Dorr C classification were uncemented. CONCLUSION: Although some patients undergoing THA with high osteoporosis-related fracture risk were identified and cemented, some risk factors including poor proximal femur shape (by Dorr classification) and poor bone quality (as measured by FRAX score) were potentially overlooked. Cemented patients had an increased risk for fractures but did not receive appropriately increased osteoporosis screening or treatment. LEVEL OF EVIDENCE: III.

Improving patients' experiences of diagnosis and treatment of vertebral fracture: co-production of knowledge sharing resources.

BACKGROUND: Osteoporosis involves changes to bones that makes them prone to fracture. The most common osteoporotic fracture is vertebral, in which one or more spinal vertebrae collapse. People with vertebral fracture are at high risk of further fractures, however around two-thirds remain undiagnosed. The National Institute for Health and Care Excellence (NICE) recommends bone protection therapies to reduce this risk. This study aimed to co-produce a range of knowledge sharing resources, for healthcare professionals in primary care and patients, to improve access to timely diagnosis and treatment. METHODS: This study comprised three stages: 1. In-depth interviews with primary care healthcare professionals (n = 21) and patients with vertebral fractures (n = 24) to identify barriers and facilitators to diagnosis and treatment. 2. A taxonomy of barriers and facilitators to diagnosis were presented to three stakeholder groups (n = 18), who suggested ways of identifying, diagnosing and treating vertebral fractures. Fourteen recommendations were identified using the nominal group technique. 3. Two workshops were held with stakeholders to co-produce and refine the prototype knowledge sharing resources (n = 12). RESULTS: Stage 1: Factors included lack of patient information about symptoms and risk factors, prioritisation of other conditions and use of self-management. Healthcare professionals felt vertebral fractures were harder to identify in lower risk groups and mistook them for other conditions. Difficulties in communication between primary and secondary care meant that patients were not always informed of their diagnosis, or did not start treatment promptly. Stage 2: 14 recommendations to improve management of vertebral fractures were identified, including for primary care healthcare professionals (n = 9) and patients (n = 5). Stage 3: The need for allied health professionals in primary care to be informed about vertebral fractures was highlighted, along with ensuring that resources appealed to under-represented groups. Prototype resources were developed. Changes included help-seeking guidance and clear explanations of medical language. CONCLUSIONS: The study used robust qualitative methods to co-produce knowledge sharing resources to improve diagnosis. A co-production approach enabled a focus on areas stakeholders thought to be beneficial to timely and accurate diagnosis and treatment. Dissemination of these resources to a range of stakeholders provides potential for substantial reach and spread.

Analyzing the risk of osteoporosis and fracture in rheumatoid arthritis patients who have been treated with various biologics.

BACKGROUND: Rheumatoid arthritis (RA) is a major risk factor for osteoporosis/osteoporotic fractures. We aimed to elucidate the role of treatment choices among osteoporosis/osteoporotic fractures. METHODOLOGY: We utilized the Chang-Gung Research Database to assess the risks of osteoporosis/osteoporotic fractures among independently treated RA patients, using retrospective time-to-event outcomes analysis. RESULTS: A total of 3509 RA patients with a mean of 63.1 ± 8.6 years were analyzed. Among all, 1300 RA patients (37%) were diagnosed with newly diagnosed osteoporosis. The crude incidence of newly diagnosed osteoporosis was the highest among those treated with other conventional disease-modifying anti-rheumatic drugs (cDMARDs; 74.1 events/1000-PYs, 95%CI 66.0-82.3), followed by those with a non-treatment period (68 events/1000-PYs, 95%CI 63.1-72.9), methotrxate (MTX) monotherapy (60.7 events/1000-PYs, 95%CI 41.2-80.3), MTX plus other cDMARDs (51.9 events/1000-PYs, 95%CI 43.4-60.3), and abatacept/rituximab (48.6 events/1000-PYs, 95%CI 14.9-82.3). The lowest crude incidence was found in patients treated with anti-TNFi biologics (40.4 events/1000-PYs, 95%CI 28.6-52.2) and other biologic disease-modifying anti-rheumatic drugs (bDMARDs; 40.1 events/1000-PYs, 95%CI 8.0-72.1). A total of 270 patients (20.8%) suffered from an incident fracture during follow-ups. The crude incidence of fracture was the highest among those treated with abatacept/rituximab (49.0 events/1000-PYs, 95%CI 6.0-91.9), followed by those with non-treatment periods (24.3 events/1000-PYs, 95%CI 19.3-29.4), other cDMARDs (24.2 events/1000-PYs, 95%CI 18.1-30.2), anti-TNFi biologics (20.2 events/1000-PYs, 95%CI 8.8-31.6). Other bDMARDs (13.3 events/1000-PYs, 95%CI 0-39.2), MTX mono (12.5 events/1000-PYs, 95%CI 0.3-24.8), and MTX plus other cDMARDs (11.4 events/1000-PYs, 95%CI 5.4-17.4) were low incidences. CONCLUSION: The treatment option has emerged as a critical determinant in the context of future osteoporosis and osteoporotic fracture risks among RA. These findings offer a valuable resource for clinicians, empowering them to tailor bespoke treatment strategies for RA patients, thereby mitigating the potential for future osteoporosis and fractures.