Abstract

Osteoporosis (OP) is a metabolic bone disease with a high incidence rate worldwide. Its main features are decreased bone mass, increased bone fragility and deterioration of bone microstructure. It is caused by an imbalance between bone formation and bone resorption. Ginsenoside is a safe and effective traditional Chinese medicine (TCM) usually extracted from ginseng plants, having various therapeutic effects, of which the effect against osteoporosis has been extensively studied. We searched a total of 44 relevant articles with using keywords including osteoporosis, ginsenosides, bone mesenchymal cells, osteoblasts, osteoclasts and bone remodeling, all of which investigated the cellular mechanisms of different types of ginsenosides affecting the activity of bone remodeling by mesenchymal stem cells, osteoblasts and osteoclasts to counteract osteoporosis. This review describes the different types of ginsenosides used to treat osteoporosis from different perspectives, providing a solid theoretical basis for future clinical applications.

Introduction

Osteoporosis (OP) is a metabolic bone disease characterized by decreased bone mass and destruction of bone tissue microstructure, leading to increased bone fragility and susceptibility to fractures ( Gopinath, 2023 ). A global epidemiological survey on osteoporotic vertebral fractures showed that one in three women and one in five men over the age of 50 will be directly affected by osteoporosis for the rest of their lives ( Laird et al., 2023 ). A study on the prediction of hip fractures in Asia estimated that by 2050, the direct cost of osteoporotic fractures in Asia alone may reach at least $15 billion per year ( Cheung et al., 2018 ). Therefore, early detection and treatment of osteoporosis is crucial for preventing fractures and reducing the burden on the global health care system.

Normal bone homeostasis in the human body is mainly maintained by osteoblasts differentiated from bone marrow mesenchymal stem cells (BMSCs) and osteoclasts produced by the fusion of monocytes and macrophages ( Guo et al., 2023 ; Kular et al., 2012 ), which participate in bone reconstruction and exert the sequential function of absorbing old bone and forming new bone ( Harris et al., 2023 ; Iantomasi et al., 2023 ) ( Fig. 1 ). The main cause of OP is aging, while secondary causes include genetic diseases, endocrine diseases, gastrointestinal diseases, blood diseases, neurological diseases, rheumatism and autoimmune diseases ( Patel and Wairkar, 2023 ). In addition, lifestyle changes, such as vitamin D and calcium deficiency, high salt intake, alcohol consumption, and smoking, also significantly increase the risk of osteoporosis. These factors can lead to an imbalance in bone cell activity and disrupt the dynamic cycle of bone formation and absorption, thereby affecting bone homeostasis and exacerbating OP ( Beekman et al., 2023 ).

Conclusion

In recent years, there has been increasing research on the treatment of osteoporosis with ginsenosides. Therefore, this review describes the possible mechanisms of different types of treatment for osteoporosis from three aspects, BMSCs, osteoblasts, and osteoclasts, and summarizes their specific signaling pathways or key factor mechanisms. However, this treatment method is still in the initial stage of clinical transformation, and there are still many obstacles between its experimental results and clinical application, such as in terms of combination therapy, drug delivery pathways, bioavailability, and combination with biochemical materials. With increasing attention given to the role of ginsenosides in bone reconstruction, ginsenosides may become a new drug for treating osteoporosis and promoting fracture healing and a powerful candidate for cytokines in tissue engineering bone.

Abstract

Osteoporosis is a systemic bone disease characterized by reduced bone mass and deterioration of the microstructure of bone tissue, leading to an increased risk of fragility fractures and affecting human health worldwide. Food-derived peptides are widely used in functional foods due to their low toxicity, ease of digestion and absorption, and potential to improve osteoporosis. This review summarized and discussed methods of diagnosing osteoporosis, treatment approaches, specific peptides as alternatives to conventional drugs, and the laboratory preparation and identification methods of peptides. It was found that peptides interacting with RGD (arginine-glycine-aspartic acid)-binding active sites in integrin could alleviate osteoporosis, analyzed the interaction sites between these osteogenic peptides and integrin, and further discussed their effects on improving osteoporosis. These may provide new insights for rapid screening of osteogenic peptides, and provide a theoretical basis for their application in bone materials and functional foods.

Osteoporosis

As the global population ages, the prevalence of diseases associated with aging, such as diabetes, arthritis, and dementia, also increases ( Li et al., 2021 , Lopes et al., 2022 ). Among these, the increasing incidence of chronic diseases such as osteoporosis have caused a significant societal burden ( Su et al., 2020 ). Osteoporosis affects more than 200 million people worldwide ( Shen et al., 2022 ). By 2030, the number of hip fractures among males are estimated to increase by 51.8% globally, and females are at even higher risk ( Gasparik et al., 2023 ). The increasing incidence of osteoporosis may contribute to a higher risk of fractures and reduced life expectancy, necessitating investigations on the prevention and treatment of this condition.

In the human body, normal bone metabolism involves persistent bone tissue remodeling through osteoblast-dependent bone formation and osteoclast-dependent bone resorption. Enhanced bone resorption leads to reduced bone density, a primary factor in the development of osteoporosis ( Malluche, Davenport, Lima, & Monier-Faugere, 2022 ). Osteoporosis is characterized by reduced bone density, deteriorating bone microstructure, and aggravated bone fragility, which increase the risk of fracture. These changes in bone structure are closely linked to the activities of osteoblasts and osteoclasts: osteoblasts secrete non-collagen proteins to regulate the mineralization of bone matrix, while osteoclasts are responsible for bone resorption ( Kittivanichkul, Watanabe, Nagaoka, & Malaivijitnond, 2016 ). Osteocytes, the most abundant cells in mature bone ( Fig. 1 ), interact with osteoblasts and osteoclasts to influence bone formation and resorption and are closely related to osteoporosis.

Perspectives

The value of food protein digests and bioactive peptides as functional foods in the future cannot be estimated. A healthy diet should contain osteogenic peptides that have been investigated through preclinical research and clinical trials. Prediction of osteogenic peptides directly from enzymatic hydrolysis products has significantly reduced the cost of osteogenic peptides compared to multi-step purification, isolation, screening and identification. Moreover, advanced and powerful technologies, such as mass spectrometry, protein purification, bioinformatics, crystallography, micro-computed tomography, and biofilm interference, are widely utilized to study molecular structure and provide a theoretical basis for understanding the relationship between structure and activity at the molecular level. In this review, the evaluation methods and treatment methods of osteoporosis are reviewed, and it is found that osteopoietic peptides from food sources are a potential source to replace drugs with side effects for osteoporosis treatment. Peptides can improve osteoporosis by interacting with RGD binding sites within integrins, which may be used in future computer simulations to rapidly predict and screen new methods of osteogenic peptides. Taken together, these not only improve the safety of osteoporosis treatment but also reduce the cost of screening osteogenic peptides. This review aims to encourage studies on the structure-activity relationships between osteogenic peptides and integrins that regulate cell adhesion, promoting osteoblast and inhibiting osteoclast proliferation and differentiation. Osteogenic peptides also have the potential for application in the development of bioadhesives for bone materials. Therefore, research ideas for predicting and screening bone-forming active peptides have been summarized, these ideas may lead to the development of bone materials, active drugs that promote bone formation and functional foods.

Abstract

Background
Osteoarthritis (OA), the leading cause of disability among adults, has no cure and is associated with significant comorbidities. The premise of this randomized clinical trial is that, in a population at risk, a 48-month program of dietary weight loss and exercise will result in less incident structural knee OA compared to control.

Methods/design
The Osteoarthritis Prevention Study (TOPS) is a Phase III, assessor-blinded, 48-month, parallel 2 arm, multicenter randomized clinical trial designed to reduce the incidence of structural knee OA. The study objective is to assess the effects of a dietary weight loss, exercise, and weight-loss maintenance program in preventing the development of structural knee OA in females at risk for the disease. TOPS will recruit 1230 ambulatory, community dwelling females with obesity (Body Mass Index (BMI) ​≥ ​30 ​kg/m2) and aged ≥50 years with no radiographic (Kellgren-Lawrence grade ≤1) and no magnetic resonance imaging (MRI) evidence of OA in the eligible knee, with no or infrequent knee pain. Incident structural knee OA (defined as tibiofemoral and/or patellofemoral OA on MRI) assessed at 48-months from intervention initiation using the MRI Osteoarthritis Knee Score (MOAKS) is the primary outcome. Secondary outcomes include knee pain, 6-min walk distance, health-related quality of life, knee joint loading during gait, inflammatory biomarkers, and self-efficacy. Cost effectiveness and budgetary impact analyses will determine the value and affordability of this intervention.

Discussion
This study will assess the efficacy and cost effectiveness of a dietary weight loss, exercise, and weight-loss maintenance program designed to reduce incident knee OA.

Backgrounds

Osteoarthritis (OA), the leading cause of disability among adults, has no cure and is associated with significant comorbidities [1]. Its increased prevalence and severity make it burdensome for people afflicted with the disease, and for health care organizations intended to administer care [2]. Obesity and OA were first linked in 1945 and this relationship has since been verified repeatedly [[3], [4], [5], [6]]. Obesity is a major risk factor associated with knee pain; people with obesity were 2.7 times more likely to have knee OA than adults without obesity [7].

Our mechanistic model, influenced by the seminal work of Griffin and Guilak [8], supports the premise that dietary weight loss and exercise may reduce knee joint loads, lower inflammation, and increase self-efficacy resulting in a lower incidence of structural knee OA (Fig. 1). Previous work showed that weight loss decreased knee joint loads such that every pound lost was associated with a 4-pound reduction in knee compressive forces while walking. The cumulative effect of this load reduction, over thousands of steps per day, reduces microdamage to the subchondral plate and calcified cartilage [9]. These areas are close to the overlying articular cartilage and likely protect articular cartilage integrity (Fig. 1).

Discussion

Implementing a randomized clinical trial designed to prevent incident knee OA presents numerous challenges. OA disease status and severity are defined structurally via x-ray [36] or MRI [19] and clinically using a combination of symptoms reported by the patient and derived from a physical exam [66]. The primary outcome measure for TOPS is structural knee OA using MRI, due to its superior sensitivity and granularity compared to radiographic assessments. In addition, the use of radiographic assessments as the primary outcome measure to determine the presence or absence of incident knee OA would have increased the sample size by 478 participants (39 ​%), requiring additional clinical centers and greater costs to test the hypothesis effectively.

Losing weight and preventing weight regain are difficult [67]. Biological changes fight attempts to maintain weight loss; the body acts in starvation mode increasing feelings of hunger, satiety is suppressed, metabolic rate slows, all in an attempt to defend higher body weights [68]. Psychosocial obstacles include decreased self-efficacy, increased chronic perceived psychosocial stress, and using food for comfort; environmental obstacles include large food portions and food availability [69]. Our previous work provides encouragement that most of the weight-loss attained by the TOPS diet and exercise group can be retained long-term with implementation of the weight-loss maintenance program. In a subsample of the IDEA cohort (N ​= ​94), the diet-only group retained 5.8 ​kg (65 ​%) of an 8.9 ​kg weight loss 3.5 years following completion of the 18-month diet intervention [70]. Maintenance of this clinically important weight-loss occurred without any post-intervention interaction with the study staff.

Summary

Background
Cephalosporins are recommended as first-line antibiotic prophylaxis in total joint replacement surgery. Studies have shown an increased risk for periprosthetic joint infection (PJI) when non-cephalosporin antibiotics have been used. This study examines the effect of non-cephalosporin antibiotic prophylaxis on the risk for PJI.

Methods
Patients with a primary hip or knee replacement performed from 2012 to 2020 were identified (27 220 joint replacements). The primary outcome was the occurrence of a PJI in a one-year follow-up. The association between perioperative antibiotic prophylaxis and the outcome was examined using logistic regression analysis.

Discussion
Cefuroxime was used as prophylaxis in 26,467 operations (97.2%), clindamycin in 654 (2.4%) and vancomycin in 72 (0.3%). The incidence of PJI was 0.86% (228/26,467) with cefuroxime and 0.80% (6/753) with other prophylactic antibiotics. There was no difference in the risk for PJI with different prophylactic antibiotics in the univariate (OR 1.06, 95% CI 0.47–2.39) or multivariable analysis (OR 1.02, 95% CI 0.45–2.30).

Conclusion
Non-cephalosporin antibiotic prophylaxis in primary total joint replacement surgery was not associated with an increased risk for PJI.

Introduction

Periprosthetic joint infection (PJI) is one of the most feared complications after prosthetic joint surgery and therefore it is essential to prevent them. Perioperative antibiotic prophylaxis has a well-established role in the prevention of surgical site infections (SSIs) related to prosthetic joint surgery. First- or second-generation cephalosporins are recommended as first-line prophylactic antibiotics. [1].

The most common reasons to use non-cephalosporin prophylactic antibiotics are reported penicillin allergy and carriage of methicillin resistant Staphylococcus aureus (MRSA) [1]. The prevalence of a reported penicillin allergy among patients with prosthetic joint surgery has been between 2.5–17% [[2], [3], [4], [5]]. Cephalosporins are often avoided and other prophylactic antibiotics, such as clindamycin or vancomycin, are given prior to joint replacement surgery to patients with a reported penicillin allergy [2,4].

Studies have shown an association between a reported penicillin or beta-lactam allergy and an increased risk of SSI after joint replacement surgery [5], even though this association has not been evident in all studies [2]. The increased risk for SSI associated with reported penicillin allergy is postulated to be due to the use of non-cephalosporin prophylactic antibiotics [6]. The risk for infection after prosthetic joint surgery has been shown to be higher when clindamycin has been compared with cloxacillin [7] and when vancomycin has been compared with cefazolin [4,8]. Wyles et al. showed that the risk for infection after prosthetic joint surgery was significantly higher when non-cefazolin prophylactic antibiotics were used [3].

Results

The study population consisted of 27,220 primary joint replacement surgeries performed on 22,497 patients. Of these surgeries, 12,452 (46%) were hip replacements and 14 768 (54%) were knee replacements. In addition, 1450 (5%) of the joint replacement surgeries were bilateral.

vvCefuroxime was used as prophylaxis in 26,467 operations (97.2%), other antibiotics were used as follows: clindamycin 654 (2.4%), vancomycin 72 (0.3%) and other antibiotics in 27 (0.1%) operations. The proportion of women was higher, and patients were slightly younger, had a higher BMI and higher ASA scores among those receiving non-cefuroxime antibiotic prophylaxis than those receiving cefuroxime (Table I). Surgeries with non-cefuroxime antibiotic prophylaxis were longer in duration than those with cefuroxime prophylaxis (Table I).

Abstract

     Recently, automated disease diagnosis based on medical images has become an integral component of digital pathology packages. Texture analysis is commonly used to address this issue, particularly in the context of estimating the osteoporosis progression in bone samples. Most research in this context uses handcrafted methods to directly extract bones image features despite the substantial correlation between sick and healthy bones, which explains the limited results. In this work, the handcrafted feature extraction method (e.g. HOG and/or LPQ) will be applied to a set of descriptors obtained from a deep analysis of bone texture images using Gabor’s filter bank. In addition, the classifier automatically adjusts the Gabor filters settings, using the bat-inspired algorithm based optimization, to achieve deep analysis behavior and optimal performance. Using a typically osteoporosis database, our experimental results reveal a significant improvement over the state-of-the-art deep/handcrafted techniques, resulting in an excellent performance of 89.66% for osteoporosis diagnosis.

Introduction

     In 1895, Roentgen [1] may have been the first to notice that X-rays could be used to acquire an image of the organs inside the human body, from which one could determine whether or not there was disease. Since then, medical imaging using X-rays has become an important diagnostic tool for a variety of diseases. In fact, information extracted from images plays an important role in decision-making at many stages of patient care, including detection, characterization, staging, evaluation of treatment response, follow-up and evaluation of residual and recurrent disease after treatment, and surgery and radiotherapy guidance [2]. Despite the incredible development of medical imaging devices, the analysis and interpretation of captured images remains a major challenge for radiologists, because any error in interpretation can lead to the prescription of the wrong drugs, thus putting the patient in danger and destroying the success of the treatment. For example, on mammogram images, it can be difficult for radiologists, with a subjective examination, to distinguish between a tumor and a calcification. It is also difficult for them to detect with the naked eye the presence of a tumor in the dense breast [3]. Due to the inexperience of many radiologists and the large number of cases reviewed periodically, the treatment process will be expensive due to the large number of errors. So, to avoid or cut down on diagnostic mistakes, radiologists need a way to help them make the right decisions. Soft computing paradigms are a good way to do this.

Conclusion

     Recent increases in the need for radiologists are primarily due to the rapid growth of medical imaging due to advancements in imaging technologies. Indeed, following the increase in demand, the workload of the radiologist has increased, which can unfortunately lead to diagnostic errors due to the specialists workload. Recently, the application of Artificial Intelligence (AI) approaches to the clinical practice of medical imaging has played a significant role in enhancing diagnostic accuracy and efficacy. In addition to improving diagnostic accuracy, these strategies bridge the gap between inexperienced and experienced clinicians or between generalists and specialists. The diagnosis of osteoporosis is one of the most crucial diagnostic practices requiring medical imaging. In this paper, we present an AI-based technique for automatically detecting osteoporosis by analyzing X-ray images of bone tissue. In this study, we developed a model for diagnosing osteoporosis based on handcrafted features taken from descriptors obtained from a thorough analysis of the bone image using a set of Gabor filters with different orientations. Two well-know hand-crafted methods were used to extract descriptor features, namely HOG and LPQ. To achieve a high level of performance, we used a bat-based optimization method to determine appropriate Gabor filter parameters. Additionally, we combined information at two distinct levels, including fusion at score level and fusion at decision level. In this study, we have attempted to cover all aspects of system development. Consequently, our studies consisted of selecting the optimal parameters of the normalization approach, deciding whether to analyze the full image or to analyze it in blocks, selecting the Gabor filter parameters, and lastly combining the information from various subsystems. In fact, all of these tests resulted in an excellent performance (ACC = 89.66%) that outperformed several previously published studies. In future work, we intend to combine these features with clinical data to develop a multimodality model. In addition, we will try to use/develop more predictive handcrafted features to improve the accuracy of the diagnosis.

Abstract

Summary

     In this systematic review, the effects of osteoporosis patient education were examined. All studies found an effect on physical function, but for the other themes, the results were inconclusive. The findings indicate a need for further research in this topic.

Introduction

     Osteoporosis is a chronic disease with serious consequences for the individual and major societal costs. With the aim of fracture prevention, many countries offer osteoporosis patient education. The objectives were to examine the effects and mediators of osteoporosis patient education and describe the characteristics of studies with and without an effect. Though, none of the included studies reported mediators, and therefore, we could not examine that.

Methods

     Six databases were searched in October 2020. Two researchers independently conducted title and abstract screening as well as full-text review. Records were included if participants had osteoporosis, and the patient education was group-based, face-to-face, and addressed two or more aspects, e.g., diet, medication, and exercise. The Cochrane Collaboration tools were used for risk of bias assessment. Finally, data were extracted into a standardized form and presented narratively.

Results

     In total, 2934 records were identified, and 13 studies met the inclusion criteria. All six studies examining the effects of patient education on physical function demonstrated improvements. In addition, one out of two RCT studies and one non-randomized study reported improved psychological wellbeing. Just one out of five RCT studies showed improvements regarding physical discomfort and disability. Effects on health-related quality of life, adherence and persistence, and knowledge of osteoporosis were inconclusive.

Conclusion

     There is limited evidence for the effectiveness of osteoporosis patient education. There is a need for high-quality randomized controlled trials, which should describe the characteristics of the interventions and examine the mechanisms of osteoporosis patient education.

Introduction

     Osteoporosis is a chronic disease that causes reduced density and quality of the bones and thereby increases the risk of fractures. It is estimated that 27.6 million people in Europe have osteoporosis [1]. The disease and the related fractures have high societal costs (€37.4 billion in Europe) [1] as well as individual consequences, such as decrease in quality of life [2], change in self-image, and dependency on others [3].

      Osteoporosis is normally treated by ensuring sufcient levels of calcium and vitamin D in the diet, preventing immobilization by staying physically active, and initiating pharmacological treatment [4, 5]. Therefore, patients with osteoporosis may beneft from patient education covering these themes. The aim of osteoporosis patient education is to increase participants’ understanding, skills, and confdence [4] as well as medication compliance and persistence [4, 6], and thereby prevent fractures. During osteoporosis patient education, the participants should get training and information, but patient education should not just provide information, it should also enable behavioral change if participants * M. Rubæk merub@sdu.dk 1 National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark 2 National Research Center for Bone Health, Zealand University Hospital, Køge, Denmark / Published online: 12 November 2021 Osteoporosis International (2022) 33:959–977 1 3 have the opportunity to interact with health professionals and gain social and psychological support from a group of participants [4, 6].

Conclusions

     Previous studies have indicated that osteoporosis patients may beneft from patient education. However, research on this topic is sparce and inconsistent. In this systematic review, we found that patient education has an efect on physical function. For the other themes, the results were inclusive and for mediators, there were no data.

     As there are some shortcomings in the included studies, there is potential for further research on this topic. There is a need for studies that evaluate osteoporosis patient education in well-conducted randomized controlled trials with long follow-up periods. It is crucial that they describe the characteristics of the studies so that they can be compared and implemented in practice. Moreover, they should examine the mediators and thereby contribute to a wider understanding of the mechanisms of osteoporosis patient education.

Abstract

     This paper presents an Artificial Nerual Network (ANN) for identification of postmenopausal women who are at high risk for developing osteopathy. While 800 patients took part in the study, 180 were used for network training. The following parameters were used: T-score (from −2,5 to −4), Age, Blood calcium level (<1,9 mmol/L), Blood vitamin D level (<20 ng/ml), Hip fracture, Spine fracture, Joint fracture, Glucocorticoids use, Smoking status, and BMI. The network has 10 input parameters and 1 output parameter. For the final architecture of expert system, a neural network with 20 neurons in hidden layer was chosen based on the training results. The signal from each neuron from hidden layer is directed to neuron in output layer, where this neuron processes the signal and gives desired output of the network. The sensitivity was 97,5%, specificity 70%, and accuracy 94,44%.

Introduction

     Osteoporosis is a skeletal illness that causes weakening of the bones, which can lead to increased fractures. People with osteoporosis have decreased bone mass and microarchitectural degeneration of bone tissue, in addition to lower bone strength [1-3].

     Osteoporosis is a skeletal illness that causes weakening of the bones, which can lead to increased fractures. People with osteoporosis have decreased bone mass and microarchitectural degeneration of bone tissue, in addition to lower bone strength [1-3].

     According to data from 2010, 6,6% of men and 22,1% of women over 50 in the EU have osteoporosis. Because of the expanding number of patients worldwide, it is now referred to as a “silent epidemic.” Variable and non-variable factors that raise the chance of developing osteoporosis and bone fractures can be separated. One of the most important variables is smoking, which is linked to decreased bone resistance to mechanical stresses and friction. The effects of excessive alcohol use on bone homeostasis are significant. Caffeine, glucocorticoid therapy, insufficient calcium and vitamin D intake, insufficient physical activity, low BMI, past bone fractures, and a family history of osteoporosis are all risk factors [4-6].

Conclusion

     As osteoporosis in postmenopausal women is a rising problem in the modern world, predictive modelling of the risk of developing osteoprosis is highly desirable. This paper presents the development and validation of an ANN based model for prediction and automated diagnosis of osteoporosis in post-menopausal women based on risk-contributing factors. Giving the high accuracy and sensitivity of proposed ANN for identification of high risk of osteoporosis development in postmenopausal women, it can be concluded that AI has a high potential for decission making for this specific purpose. Prediction of high risk for osteoprosis development can contribute to adjustments in lifestyle and possible prevention of osteoporosis. In addition to the benefit this would have to each individual, the cost reduction in terms of preventing costly interventions necessary in case of osteoporosis development is a significant contribution.

Abstract

     Osteoporosis is underrecognized and undertreated in men, even though up to 25% of fractures in patients over the age of 50 years occur in men. Men develop osteoporosis with normal aging and accumulation of comorbidities that cause bone loss. Secondary causes of bone loss may be found in up to 60% of men with osteoporosis. Mortality in men who experience major fragility fracture is greater than in women. Diagnosis of osteoporosis in men is similar to women, based on low-trauma or fragility fractures, and/or bone mineral density dual-energy X-ray absorptiometry (DXA) T-scores at or below −2.5. Because most clinical trials with osteoporosis drugs in men were based on bone density endpoints, not fracture reduction, the antifracture efficacy of approved treatments in men is not as well documented as that in women. Men at a high risk of fracture should be offered treatment to reduce future fractures.

Introduction

     Osteoporosis is a worldwide disease that causes more than nine million fragility fractures annually, one every 3 s [1].

     Men have a lower risk of osteoporosis and fragility fractures than women. This is because women have bones with smaller diameters, lower peak bone mass, a menopause-related bone resorption process, and a higher risk of falls than men [2]. Despite osteoporosis and fragility fractures being less common in men than women, 39% of osteoporotic fractures worldwide occur in men [1]. Data from 2005 indicate that of the 2 million osteoporotic fractures that occur annually in the US, 29% occur in men. This percentage corresponds to an associated cost of 17 billion US dollars [3]. In men and women, the incidence of hip fractures increases exponentially with age, although in men, the increase begins approximately 10 years later [4]. Data from the U.S. 2008 Nationwide Emergency Department Sample showed the incidence of hip fracture in men ranging from 0.56 per 1000 per year at the age of 60 years to 13 per 1000 per year at age 85 years [5]. Similar results were reported in a Norwegian study covering the years 2004–2005, with an incidence of 0.49 per 1000 person-years of hip fractures in men at age 60 and 12.3 per 1000 person-years at age 85 [6]. A 60-year-old man has an approximately 25% risk of having an osteoporotic fracture during his remaining lifetime [7]. Men are less likely than women to be evaluated and receive antiresorptive treatment after a hip fracture [8,9]. The mortality rate associated with hip fractures [10,11] and vertebral and other fractures [12] is higher in men than in women. In a prospective study in community dwelling women and men aged 60 years and older in Australia, mortality after a low trauma fracture was 48% in women and 57% in men within 10 years [13]. The reason for this difference in mortality is not clear, but higher risk of infection in men than in women after a low trauma fracture could be one explanation [14].

Conclusion

     Male osteoporosis occurs less frequently than osteoporosis in postmenopausal women but is still responsible for a substantial disease burden in the population. Approximately 25% of fractures in patients over 50 years occur in men. Osteoporosis in men increases with age as in women, and mortality after major fragility fractures is greater in men than women. Male osteoporosis is defined by the occurrence of fragility fractures, in some parts of the world, only hip and spine fractures or by DXA BMD T-scores of −2.5 or lower at the hip, lumbar spine, and/or forearm. Men having T-scores of −2.5 or lower and prior fragility fractures are at high risk of future fractures. Men with T-scores between −1.0 and −2.5 should be assessed by FRAX or similar tools to determine fracture risk. At least half of men with osteoporosis have secondary causes of bone loss, and identification and treatment of these causes may help prevent further bone loss and possibly improve bone density. Treatment trials of osteoporosis in men have led to the approval of multiple medications for use in men, although these trials were typically small, short in duration, and used bone density rather than fracture endpoints.

Abstract

     Osteoporosis is a disease characterized by impaired bone microarchitecture and reduced bone mineral density (BMD) resulting in bone fragility and increased risk of fracture. In western societies, one in three women and one in five men will sustain an osteoporotic fracture in their remaining lifetime from the age of 50 years. Fragility fractures, especially of the spine and hip, commonly give rise to increased morbidity and mortality. In the five largest European countries and Sweden, fragility fractures were the cause of 2.6 million disability-adjusted life years in 2016 and the fracture-related costs increased from €29.6 billion in 2010 to €37.5 billion in 2017. In the European Union and the USA, only a small proportion of women eligible for pharmacological treatment are being prescribed osteoporosis medication. Secondary fracture prevention, using Fracture Liaison Services, can be used to increase the rates of fracture risk assessment, BMD testing and use of osteoporosis medication in order to reduce fracture numbers. Additionally, established primary prevention strategies, based on case-finding methods utilizing fracture prediction tools, such as FRAX, to identify women without fracture but with elevated risk, are recommended in order to further reduce fracture numbers.

Postmenopausal osteoporosis

     Osteoporosis is a disease characterized by impaired bone microarchitecture and reduced bone mineral density (BMD) resulting in bone fragility and increased risk of fracture [1,2]. BMD measured using dual-energy X-ray absorptiometry to a large extent reflects bone strength [3], and for each standard deviation (SD) decrease in femoral neck BMD, the fracture risk is increased two-fold to three-fold [4] in postmenopausal women. In 1994, the World Health Organization (WHO) defined osteoporosis using a BMD threshold of −2.5 SDs or lower than the mean value for young adult women, referred to as a T-score of −2.5 SD or less. A measurement of BMD at the femoral neck, and derivation of the T-score using the National Health and Nutrition Examination Survey (NHANES) III reference database with women aged 20–29 years, has been proposed as the reference standard for describing osteoporosis. However, other sites such as the total hip, lumbar spine and radius are frequently used in clinical practice [5,6]. Aging leads to bone loss, and, particularly, the first few years after menopause represent a period of accelerated bone loss [7]. Thus, the prevalence of osteoporosis increases with age [2].

Concluding remarks

     Bone fragility and the resulting fractures are very common in postmenopausal women and projections indicate that, due to the aging population, an increase in the number of osteoporotic fractures, accompanied by substantially increased DALYs and financial costs, is to be expected globally. Secondary fracture prevention, orchestrated via implementation of FLS, so that a growing proportion of women at risk are evaluated and treated with osteoporosis medications is a crucial step in reducing fracture numbers. In addition, established primary prevention strategies, based on case-finding methods utilizing fracture prediction tools, such as FRAX, to identify women without fracture but with elevated risk, could be increasingly used in order to further reduce fracture numbers.

Abstract

     In this chapter, we emphasize among rheumatoid arthritis (RA) patients, whom and how to screen for osteoporosis. We highlight certain modalities, advancements in technology, secondary osteoporosis workup, and laboratory testing as well as their caveats. Finally, we discuss current guidance on how to direct the laboratory and radiology testing in the context of the individual patient with RA to guide and select from the osteoporosis treatment options currently available.

Introduction

     Rheumatoid arthritis (RA) is associated with double the risk of fracture when compared to the general population [1]. Unfortunately, osteoporosis screening and treatment rates are low in RA and may be due to the lack of clear guidelines for this high-risk population [2]. In this review, we collate the existing evidence to provide an evidence-based guide to osteoporosis screening and treatment for people with RA.

     There are no RA-specific guidelines for osteoporosis screening which likely contributes to the low rates of osteoporosis screening and detection in this high-risk population [2]. To provide evidencebased screening recommendations for people with RA, we combine recommendations from the 2014 National Osteoporosis Foundation (NOF) [3] and the 2017 American College of Rheumatology (ACR) glucocorticoid-induced osteoporosis (GIOP) guidelines [4]. The 2014 NOF guideline states that adults with a diagnosis (such as RA) or taking a medication (such as glucocorticoids (GCs)) should be screened. This recommendation does not apply to healthy young males or premenopausal females without fracture history. There is an additional statement to screen post-menopausal females and males over 50 with clinical risk factors for fracture. We use this statement to base our recommendation to screen all people with RA aged 50 and above [3]. The 2017 ACR GIOP guideline recommends bone mineral density (BMD) screening for anyone 40 years and older who are taking
2.5 mg prednisone equivalents per day for 3 months or longer [4]. It also provides guidance for BMD testing for people under 40 years of age with significant risk factors such as prior fracture or exposure to very high doses of GCs [4].

Conclusions

     Early case detection and screening in RA patients is critical, especially in those with high ACPA positivity, prolonged RA disease duration, significant GC exposure, or history of low trauma fracture. While there is a need for more RA-specific studies and RA-focused bone health guidelines, we advocate for the clinician to risk stratify based on existing guidelines to aid in shared decision-making with patients and choosing the appropriate osteoporosis agent for fracture prevention.

Abstract

     Low hemoglobin (Hb) level or anemia is associated with osteoporosis and bone fracture. Cadmium (Cd) and lead (Pb) exposure are also risk factors of osteoporosis and anemia. However, the role of anemia in Cd/Pb related bone loss remains unclear. The aim of present study was to investigate the association between Hb level and bone loss in a population with environmental lead and cadmium exposure. One hundred and ninety-four women and 108 men with different levels of Cd/Pb exposure were included in our study. The Cd/Pb exposure was determined using graphite-furnace atomic absorption spectrometry. Forearm bone mineral density (BMD) was determined by peripheral dual-energy X-ray absortiometry. Hb concentration was determined using an automatic blood cellcounter. A logistic model was established to predict the risk of osteoporosis. The BMDs of women that had the highest quartile BCd and BPb were markedly lower than that with the lowest quartile (p < 0.05). The BMD and the prevalence of osteoporosis in men with anemia were lower and higher than that with normal Hb (p < 0.05), respectively. In men, age, BPb and anemia were independent risk factors for osteoporosis. The odds ratio (OR) of men with anemia was 11.28 (95%confidence interval (CI):1.94-65.54) and 19.56 (95%CI: 2.98-128.78) compared to those with normal Hb after adjusting for potential cofounders. No such association was found in women. The area under the curve was 0.88 (95%CI: 0.82-0.96) in predicting osteoporosis using the logistic model in men. Linear discriminant analysis also showed that 90.7% of osteoporosis was correctly classified. Our data show that anemia is associated with incident of osteoporosis in men but not in women that environmentally exposed to Pb and Cd.

Introduction

     Cadmium (Cd) and lead (Pb) are both distributed in the environment and used in industrial field. Both Cd and Pb can enter the human body via digestive tract. Bone is an important target organ for Cd and Pb toxicity. Cd and Pb exposure are associated with low bone mass or osteoporosis (A˚ kesson et al., 2014; Jalili et al., 2020; Li et al., 2016). Moreover, both animal and population studies indicated that Cd and Pb exposure can affect hemoglobin (Hb) level, in particular to Pb exposure. Chronic Pb exposure is a risk factor of hematologic impairments that can decrease the Hb content (Dobrakowski et al. 2015; Li et al., 2018; Nakhaee et al. 2018) and hematocrit (Chwalba et al. 2019; Nakhaee et al. 2018). However, the association and interplay between those outcomes has not been completely clarified (Zhang et al., 2020).

Conclusion

     In conclusion, we observe that anemia is a negative and independent risk of osteoporosis in men but not in women that environmentally exposed to Cd and Pb. Age, BPb and anemia are important factors that are related to osteoporosis in men. A model based on the three factors showed acceptable performance in predicting osteoporosis. Hb level or anemia should be considered when aim to show the association between Pb or Cd exposure and bone loss, in particular to men population