Individuals with a fragility fracture and a prescription for bone active medication have a positive perception of the medication but do not associate it with fracture risk reduction.

Most participants reported a positive perception of bone active medication despite sustaining a fracture while taking the medication, reporting medication side effects, or having a healthcare provider stop the prescription. Participants did not appear to connect the medication to fracture risk, suggesting this connection should be emphasized by healthcare providers. OBJECTIVE: Our purpose was to examine perceptions about bone active medication from individuals with a fragility fracture and a prescription for bone active medication. METHODS: In this qualitative description study, eligible participants were those who attended an Osteoporosis Canada education session, and reported sustaining a previous fragility fracture and receiving a prescription for bone active medication. We conducted one-on-one interviews and analyzed the data using the analytic hierarchy approach. RESULTS: We interviewed 32 female participants (age range 58-89 years). Based on our analysis, two themes were developed: (1) most participants spoke positively about bone active medication, indicating they were willing to start, or continue to take, their medication. Positive perceptions were held by participants who sustained a fracture while taking bone active medication, participants whose healthcare provider had stopped the prescription, and participants who reported side effects from the medication; (2) most participants did not discuss bone active medication in relation to their fracture and did not appear to connect the medication to the concept of fracture risk. Instead, participants talked about the medication in relation to bone health in general, or to bone density. CONCLUSION: Participants appeared to have positive perceptions of bone active medication, despite sustaining a fracture while taking the medication, reporting medication side effects, or having a healthcare provider stop the prescription. Participants did not connect bone active medication to the concept of fracture risk, illustrating the need for healthcare providers to emphasize the connection between fracture risk and bone active medication.

[Geriatric traumatological management of osteoporosis : "Let the first fracture be the last"]. / Alterstraumatologisches Management der Osteoporose : "Lass die erste Fraktur die Letzte sein".

In Germany more than 800,000 osteoporotic fractures occur every year, with severe medical, social and health economic consequences. Nevertheless, as in many other countries there is a large gap in care. Fractures frequently occur in older geriatric patients, who are increasingly being (or should be) treated in geriatric trauma centers. This multidisciplinary approach offers the opportunity not only to restore the patient's mobility and independence but also to set the course for preventing further fractures. Diagnosing osteoporosis and initiating treatment early after a fracture is particularly important as there is an imminently high risk of further fractures in the months and years following a fracture. This review article describes a pragmatic, guideline-based approach to osteoporosis management for geriatric trauma patients. It discusses fracture risk assessment, current treatment thresholds and treatment strategies as well as the individual osteoporosis drugs, the indications and contraindications. This review aims to show that the treatment of osteoporosis within the framework of a geriatric traumatology team is feasible in the majority of cases. It is suggested that a treatment decision can be systematically made based on a few questions or a flow chart.

Fracture risk prediction in diabetes patients based on Lasso feature selection and Machine Learning.

Fracture risk among individuals with diabetes poses significant clinical challenges due to the multifaceted relationship between diabetes and bone health. Diabetes not only affects bone density but also alters bone quality and structure, thereby increases the susceptibility to fractures. Given the rising prevalence of diabetes worldwide and its associated complications, accurate prediction of fracture risk in diabetic individuals has emerged as a pressing clinical need. This study aims to investigate the factors influencing fracture risk among diabetic patients. We propose a framework that combines Lasso feature selection with eight classification algorithms. Initially, Lasso regression is employed to select 24 significant features. Subsequently, we utilize grid search and 5-fold cross-validation to train and tune the selected classification algorithms, including KNN, Naive Bayes, Decision Tree, Random Forest, AdaBoost, XGBoost, Multi-layer Perceptron (MLP), and Support Vector Machine (SVM). Among models trained using these important features, Random Forest exhibits the highest performance with a predictive accuracy of 93.87%. Comparative analysis across all features, important features, and remaining features demonstrate the crucial role of features selected by Lasso regression in predicting fracture risk among diabetic patients. Besides, by using a feature importance ranking algorithm, we find several features that hold significant reference values for predicting early bone fracture risk in diabetic individuals.

Similarities and differences between European guidelines for the management of postmenopausal osteoporosis.

We conducted a review of 10 national guidelines from five EU countries to identify similarities or differences in recommendations for the management of patients with osteoporosis. We found general alignment of key recommendations; however, there are notable differences, largely attributed to country-specific approaches to risk assessment and reimbursement conditions. INTRODUCTION: The classification of fracture risk is critical for informing treatment decisions for post-menopausal osteoporosis. The aim of this review was to summarise 10 national guidelines from five European countries, with a focus on identifying similarities or differences in recommendations for the management of patients with osteoporosis. METHODS: We summarised the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Disease-International Osteoporosis Foundation guidelines and reviewed guidelines from France, Germany, Italy, Spain and the UK. RESULTS: The approach to risk assessment differed across the guidelines. In France, and Spain, risk assessment was based on DXA scans and presence of prior fractures, whereas UK, German and Italian guidelines recommended use of a validated risk tool. These differences led to distinct definitions of very high and high-risk patients. Guidelines aligned in recommending antiresorptive and anabolic agents as pharmacologic options for the management of osteoporosis, with sequential treatment recommended. There was agreement that patients at high or very high risk of fracture or with severe osteoporosis should receive anabolic agents first, followed by antiresorptive drugs. Variations were identified in recommendations for follow up of patients on anti-osteoporosis therapies. Reimbursement conditions in each country were a key difference identified. CONCLUSIONS: Criteria for risk assessment of fractures differ across European guidelines which may impact treatment and access to anabolic agents. Harmonisation across EU guidelines may help identify patients eligible for treatment and impact treatment uptake. However, country-specific reimbursement and prescribing processes may present a challenge to achieving a consistent approach across Europe.

Short-term risk of fracture is increased by deficits in cortical and trabecular bone microarchitecture independent of DXA BMD and FRAX: bone microarchitecture international consortium (BoMIC) prospective cohorts.

Identifying individuals at risk for short-term fracture is essential to offer prompt beneficial treatment, especially since many fractures occur in those without osteoporosis by DXA-aBMD. We evaluated whether deficits in bone microarchitecture and density predict short-term fracture risk independent of the clinical predictors, DXA-BMD and FRAX. We combined data from eight cohorts to conduct a prospective study of bone microarchitecture at the distal radius and tibia (by HR-pQCT) and 2-year incidence of fracture (non-traumatic and traumatic) in 7327 individuals (4824 women, 2503 men, mean 69 ± 9 years). We estimated sex-specific hazard ratios (HR) for associations between bone measures and 2-year fracture incidence, adjusted for age, cohort, height and weight, and then additionally adjusted for femoral neck (FN) aBMD or FRAX for major osteoporotic fracture. Only 7% of study participants had FN T-score ≤ -2.5, whereas 53% had T-scores between -1.0 to -2.5 and 37% had T-scores ≥-1.0. Two-year cumulative fracture incidence was 4% (296/7327). Each SD decrease in radius cortical bone measures increased fracture risk by 38%-76% for women and men. After additional adjustment for FN-aBMD, risks remained increased by 28%-61%. Radius trabecular measures were also associated with 2-year fracture risk independently of FN-aBMD in women (HRs range: 1.21 per SD for trabecular separation to 1.55 for total vBMD). Decreased failure load was associated with increased fracture risk in both women and men (FN-aBMD ranges of adjusted HR = 1.47-2.42). Tibia measurement results were similar to radius results. Findings were also similar when models were adjusted for FRAX. In older adults, failure load and HR-pQCT measures of cortical and trabecular bone microarchitecture and density with strong associations to short-term fractures improved fracture prediction beyond aBMD and FRAX. Thus, HR-pQCT may be a useful adjunct to traditional assessment of short-term fracture risk in older adults, including those with T-scores above the osteoporosis range.

Identifying individuals at risk for short-term fracture (within 2-years) is essential to offer prompt treatment. We examined bone microarchitecture at arm and lower leg for prediction of short-term fractures in 7327 older adults, independent of the common clinical practice measures ­ DXA-BMD and FRAX. After adjusting for other factors, we found that measures of failure load, cortical and trabecular bone microarchitecture and density predicted short-term risk of fracture beyond the usual clinical measures of DXA and FRAX. These measures of bone that indicate deficits in microarchitecture may be a useful adjunct to traditional assessment of fracture risk in older adults.

Skeletal fragility in pituitary disease: how can we predict fracture risk?

Pituitary hormones play a crucial role in regulating skeletal physiology, and skeletal fragility is a frequent complication of pituitary diseases. The ability to predict the risk of fracture events is crucial for guiding therapeutic decisions; however, in patients with pituitary diseases, fracture risk estimation is particularly challenging. Compared to primary osteoporosis, the evaluation of bone mineral density by dual X-ray absorptiometry is much less informative about fracture risk. Moreover, the reliability of standard fracture risk calculators does not have strong validations in this setting. Morphometric vertebral assessment is currently the cornerstone in the assessment of skeletal fragility in patients with pituitary diseases, as prevalent fractures remain the strongest predictor of future fracture events. In recent years, new tools for evaluating bone quality have shown promising results in assessing bone impairment in patients with pituitary diseases, but most available data are cross-sectional, and evidence regarding the prediction of incident fractures is still scarce. Of note, apart from measures of bone density and bone quality, the estimation of fracture risk in the context of pituitary hyperfunction or hypofunction cannot ignore the evaluation of factors related to the underlying disease, such as its severity and duration, as well as the specific therapies implemented for its treatment. Aim of this review is to provide an up-to-date overview of all major evidence regarding fracture risk prediction in patients with pituitary disease, highlighting the need for a tailored approach that critically integrates all clinical, biochemical, and instrumental data according to the specificities of each disease.

Long-Term Bone Density Changes and Fracture Risk in Myasthenia Gravis: Implications for FRAX® Tool Application.

Myasthenia gravis (MG) patients often require long-term glucocorticoid therapy, which may affect bone health. This study aimed to assess long-term changes in bone mineral density (BMD), evaluate osteoporotic fracture incidence, and examine the relationship between MG-specific factors and bone health outcomes over a 10-year period. This single-center, prospective cohort study included 28 MG patients. BMD, T-scores, Z-scores, and bone turnover markers were measured at baseline. FRAX® scores were calculated and adjusted for glucocorticoid dose. Fracture occurrence was monitored for over 10 years. Five (17.9%) patients experienced major osteoporotic fractures during follow-up. The fracture group had significantly lower baseline BMD and T-scores than the no-fracture group. Baseline FRAX® scores for major osteoporotic fracture risk were significantly higher in the fracture group (median 19.0% vs. 5.7%, p = 0.001). The fracture group progressed from osteopenia at baseline to osteoporosis by the end of this study. This study highlights the importance of early and regular bone health assessments in MG patients, particularly those receiving long-term glucocorticoid therapy. The FRAX® tool may be valuable for fracture risk stratification in this population. These findings can inform clinical practice and improve long-term management strategies for MG patients who are at risk of osteoporotic fractures.

The association of type 2 diabetes-related characteristics with fracture risk at different sites.

AIM: To determine the association of diabetes-related characteristics with fractures at different sites in individuals with type 2 diabetes (T2D). MATERIALS AND METHODS: We conducted a cohort study using the Clinical Practice Research Datalink (CPRD) GOLD. Patients aged over 30 years with T2D were identified within the CPRD. Patients were followed from the start of diabetes treatment until the end of data collection, death, or the occurrence of a fracture. Cox proportional hazards models were used to estimate the hazard ratios for the association of the individual characteristics (diabetes duration, glycated haemoglobin [HbA1c] level, and microvascular complications) with fracture risk, adjusted for demographics, comorbidities and comedication. RESULTS: A diabetes duration of >10 years was associated with an increased risk of any fracture and major osteoporotic fractures (MOFs), while a diabetes duration of >8 years was associated with an increased hip fracture risk, compared to a duration <2 years. An HbA1c level <6% was associated with an increased fracture risk compared to HbA1c values of 6% to <7%. The presence of one or two microvascular complications was associated with an increased risk of any fracture and MOFs and the presence of two microvascular complications was associated with an increased hip fracture risk, compared to no microvascular complications. CONCLUSION: In conclusion, our study shows that a diabetes duration of 10 years or more, strict glycaemic control resulting in HbA1c levels below 6%, and/or the presence of at least one microvascular complication increased the risk of any fracture, hip fractures, MOFs, and humerus fractures, but not ankle, scapula or skull fractures.

Periprosthetic bone mineral density, assessed using dual energy x-ray absorptiometry, following arthroplasty in patients with femoral neck fracture: 5-year outcomes of a randomized controlled trial.

OBJECTIVE: The relationship between the surgical approach used for hemiarthroplasty and periprosthetic bone mineral density (BMD) is not well understood. We have previously described a decrease in BMD 1 year postoperatively. Here, we assessed the medium-term changes in periprosthetic BMD. METHODS: We performed a follow-up study of patients with femoral neck fracture (FNF) who underwent uncemented hemiarthoplasty using a direct lateral or anterolateral approach. Dual-energy X-ray absorptiometry (DXA) was used to evaluate the changes in BMD in 23 patients over 5 years. RESULTS: A mean 6% loss of total BMD occurred over 1 year, but between 1 and 5 years, BMD was restored to the baseline value. The mean total BMD in the anterolateral group had decreased by 2% after 3 months and 3% after 12 months, and increased by 2% after 5 years, vs. decreases of 7%, 8%, and 3% for the direct lateral group. Between 1 and 5 years, BMD increased in Gruen zones 2, 3, 4, 5, and 6 in both groups. There was a significantly larger increase in zone 4 in the lateral group (4%) than the anterolateral group. CONCLUSION: The surgical approach affects periprosthetic BMD in patients with FNF. Furthermore, BMD is restored to the baseline value 5 years postoperatively.ClinicalTrials.gov registration number: NCT03753100.

The Fracture Phenotypes in Women and Men of 50 Years and Older with a Recent Clinical Fracture.

PURPOSE OF REVIEW: We review the literature about patients 50 years and older with a recent clinical fracture for the presence of skeletal and extra-skeletal risks, their perspectives of imminent subsequent fracture, falls, mortality, and other risks, and on the role of the fracture liaison service (FLS) for timely secondary fracture prevention. RECENT FINDINGS: Patients with a recent clinical fracture present with heterogeneous patterns of bone-, fall-, and comorbidity-related risks. Short-term perspectives include bone loss, increased risk of fractures, falls, and mortality, and a decrease in physical performance and quality of life. Combined evaluation of bone, fall risk, and the presence of associated comorbidities contributes to treatment strategies. Since fractures are related to interactions of bone-, fall-, and comorbidity-related risks, there is no one-single-discipline-fits-all approach but a need for a multidisciplinary approach at the FLS to consider all phenotypes for evaluation and treatment in an individual patient.

Insulin resistance, bone health, and fracture risk.

Insulin resistance, defined as an impaired biological response to insulin stimulation in target tissues, arises most frequently in the presence of central obesity. Although obesity is generally associated with increased bone mass, recent data challenge this view and, if complicated by T2DM, obese patients are at high risk for fragility fractures. IR may play a key role in this increased fracture risk through effects on bone quality rather than bone quantity. Further understanding of the mechanisms and approaches to prevent osteoporotic fractures in IR-related diseases is needed. CLINICAL RELEVANCE: The dramatic increase in obesity and metabolic syndrome (MetS) over the last half-century has led to a worldwide epidemic of type 2 diabetes mellitus (T2DM) as well as in the incidence of insulin resistance (IR). IR is defined as an impaired biological response to insulin stimulation in target tissues and is primarily related to the liver, muscle, and adipose tissue. The most frequent underlying cause is central obesity, and it is known that excess abdominal adipose tissue secretes increased amounts of free fatty acids, which directly affects insulin signalling, reduces glucose uptake in muscle, and triggers excessive triglyceride synthesis and gluconeogenesis in the liver. When pancreatic ß cells are unable to secrete the higher levels of insulin needed, T2DM, the main complication of IR, occurs. OBSERVATIONS: Although obesity is generally associated with increased bone mass, recent data challenge this view and highlight the multifaceted nature of the obesity-bone relationship. Patients with T2DM are at significant risk for well-known complications of diabetes, including retinopathy, nephropathy, macrovascular disease, and neuropathy, but it is clear that they are also at high risk for fragility fractures. Moreover, recent data provide strong evidence that IR may key role in the increased fracture risk observed in both obesity and T2DM. CONCLUSIONS: In this concise review article, the role of IR in increased risk of osteoporotic fractures in MetS, obesity, and T2DM is discussed and summarised, including consideration of the need for fracture risk assessment as a 'preventive measure', especially in patients with T2DM and chronic MetS with abdominal obesity. Personalised and targeted diagnostic and therapeutic approaches to prevent osteoporotic fractures in IR-related diseases are needed and could make significant contributions to health outcomes.

Is orthotic treatment beneficial for fresh osteoporotic vertebral fractures? A propensity score matching study.

BACKGROUND CONTEXT: Orthotic treatment is a common option for the conservative treatment of osteoporotic vertebral fractures (OVF). However, there is insufficient evidence of its clinical benefit. PURPOSE: To investigate the effectiveness of orthotic treatment for OVF. STUDY DESIGN/SETTING: Retrospective cohort study with data from two prospective studies. PATIENT SAMPLE: This study included 160 patients with fresh OVF enrolled in 2012 and 2020 prospective cohort studies. OUTCOME MEASURES: The visual analog scale (VAS) score for low back pain was used for clinical outcomes, and radiographic parameters included the percent height of the vertebra and angular change of the vertebral body. Moreover, the occurrence of secondary vertebral fractures was followed-up over time. METHODS: The patients were divided into brace and no-brace groups and were matched according to propensity score for age, sex, anterior percent height at the initial examination, and presence of old OVFs. Hazard ratio for the cumulative incidence of secondary vertebral fractures with and without bracing were calculated and analyzed using the generalized Wilcoxon test. In addition, the brace group was divided into soft and rigid brace groups and compared with the no-brace group. RESULTS: Each group had 61 cases after propensity score matching. There were no significant differences in the VAS improvement for low back pain and the change in percent height of the anterior and posterior walls from initial examination to 6 months after injury (p=.87, p=.39 and p=.14, respectively, mixed-effect models). Meanwhile, the mean angular change of fractured vertebrae was 4.3° / 3.2° initially and 1.2° / 2.5° at 6 months (the brace group / no-brace group, respectively; p=.007, mixed-effect models). A significant difference was also observed between the rigid brace group and the no-brace group (p=.008, mixed effect models). The incidence of secondary vertebral fractures was 1.6% / 11.4% at 1 month, indicating a significant difference (the brace group / no-brace group, respectively; p = .028). The hazard ratio for the cumulative incidence of secondary fractures due to orthotic treatment was 0.47 (95% confidence interval 0.20-1.09, p=.054). CONCLUSIONS: Although orthotic treatment for fresh OVF did not relieve pain, it might contribute to the stabilization of the fractured vertebra, especially using a rigid brace. Moreover, it might influence a reduction of the imminent vertebral fracture risk immediately after the onset of OVF. CLASSIFICATIONS: Clinical study.

Involvement of cognitive abilities in the occurrence of fractures in fallers aged 55 years or older: a cross-sectional study.

BACKGROUND: Both bone fragility and poor cognitive functions are known to contribute to fracture occurrence, but it remains unclear whether their contribution is independent of each other and which cognitive dysfunctions are most involved. This study aimed to clarify the involvement of various cognitive abilities in fall-related fractures among community-dwelling fallers aged 55 and over, and to determine whether poor cognitive abilities is a risk factor independent of bone fragility. METHODS: In a cross-sectional study, we collected sociodemographic and medical data, including bone mineral density (BMD), and performed cognitive and mobility assessments in 189 individuals with a history of fall in the previous year. RESULTS: Fallers with a fracture had poorer cognitive and mobility performance than non-injured fallers. Multivariate regressions revealed that cognition, BMD and other risk factors were independently associated with fracture among all participants (OR = 1.04, 95% CI = 1.01-1.08, p = 0.034 for completion time on part A of the Trail Making Test [TMT-A], and OR = 0.53, 95% CI = 0.33-0.84, p < 0.001 for BMD), particularly in women (OR = 0.77, 95% CI = 0.60-0.98, p = 0.039 for backward digit span score, and OR = 0.43, 95% CI = 0.25-0.75, p = 0.001 for BMD). CONCLUSION: Thus, poor cognition, especially poor processing speed and working memory, is associated with an increased risk of fracture in fallers, particularly in women, regardless of BMD or other fracture risk factors. Hence, an in-depth cognitive evaluation should enhance the detection of fallers at risk of fracture, particularly in the absence of signs of osteoporosis, and thus ensure the best possible prevention.

The relationship between treatment-related changes in total hip BMD measured after 12, 18, and 24 mo and fracture risk reduction in osteoporosis clinical trials: the FNIH-ASBMR-SABRE project.

There is a strong association between total hip bone mineral density (THBMD) changes after 24 mo of treatment and reduced fracture risk. We examined whether changes in THBMD after 12 and 18 mo of treatment are also associated with fracture risk reduction. We used individual patient data (n = 122 235 participants) from 22 randomized, placebo-controlled, double-blind trials of osteoporosis medications. We calculated the difference in mean percent change in THBMD (active-placebo) at 12, 18, and 24 mo using data available for each trial. We determined the treatment-related fracture reductions for the entire follow-up period, using logistic regression for radiologic vertebral fractures and Cox regression for hip, non-vertebral, "all" (combination of non-vertebral, clinical vertebral, and radiologic vertebral) fractures and all clinical fractures (combination of non-vertebral and clinical vertebral). We performed meta-regression to estimate the study-level association (r2 and 95% confidence interval) between treatment-related differences in THBMD changes for each BMD measurement interval and fracture risk reduction. The meta-regression revealed that for vertebral fractures, the r2 (95% confidence interval) was 0.59 (0.19, 0.75), 0.69 (0.32, 0.82), and 0.73 (0.33, 0.84) for 12, 18, and 24 mo, respectively. Similar patterns were observed for hip: r2 = 0.27 (0.00, 0.54), 0.39 (0.02, 0.63), and 0.41 (0.02, 0.65); non-vertebral: r2 = 0.27 (0.01, 0.52), 0.49 (0.10, 0.69), and 0.53 (0.11, 0.72); all fractures: r2 = 0.44 (0.10, 0.64), 0.63 (0.24, 0.77), and 0.66 (0.25, 0.80); and all clinical fractures: r2 = 0.46 (0.11, 0.65), 0.64 (0.26, 0.78), and 0.71 (0.32, 0.83), for 12-, 18-, and 24-mo changes in THBMD, respectively. These findings demonstrate that treatment-related THBMD changes at 12, 18, and 24 mo are associated with fracture risk reductions across trials. We conclude that BMD measurement intervals as short as 12 mo could be used to assess fracture efficacy, but the association is stronger with longer BMD measurement intervals.

In this study, we looked at how changes in hip bone density over time relate to the risk of fractures in people taking osteoporosis medications. We analysed data from over 122 000 participants across 22 different clinical trials. We found that the increase in bone density measured after 12, 18, and 24 mo of treatment was linked to the risk of fractures. Specifically, greater improvements in bone density were associated with fewer fractures in the spine, hips, and other bones. Using statistical methods, we calculated the strength of this association. We discovered that the later, we measured BMD in people taking the medication, the stronger the link between improved bone density and reduced fracture risk became. Our findings suggest that bone density measurements after 12 mo of treatment could help predict how well a medication will prevent fractures. However, the best predictions came from bone density changes measured over longer periods.

An electronic health record (EHR)-based risk calculator can predict fractures comparably to FRAX: a proof-of-concept study.

Information in the electronic health record (EHR), such as diagnoses, vital signs, utilization, medications, and laboratory values, may predict fractures well without the need to verbally ascertain risk factors. In our study, as a proof of concept, we developed and internally validated a fracture risk calculator using only information in the EHR. PURPOSE: Fracture risk calculators, such as the Fracture Risk Assessment Tool, or FRAX, typically lie outside the clinician workflow. Conversely, the electronic health record (EHR) is at the center of the clinical workflow, and many variables in the EHR could predict fractures without having to verbally ascertain FRAX risk factors. We sought to evaluate the utility of EHR variables to predict fractures and, as a proof of concept, to create an EHR-based fracture risk model. METHODS: Routine clinical data from 24,189 subjects presenting to primary care from 2010 to 2018 was utilized. Major osteoporotic fractures (MOFs) were captured by physician diagnosis codes. Data was split into training (n = 18,141) and test sets (n = 6048). We fit Cox regression models for candidate risk factors in the training set, and then created a global model using a backward stepwise approach. We then applied the model to the test set and compared the discrimination and calibration to FRAX. RESULTS: We found variables related to vital signs, utilization, diagnoses, medications, and laboratory values to be associated with incident MOF. Our final model included 19 variables, including age, BMI, Parkinson's disease, chronic kidney disease, and albumin levels. When applied to the test set, we found the discrimination (AUC 0.73 vs. 0.70, p = 0.08) and calibration were comparable to FRAX. CONCLUSION: Routinely collected data in EHR systems can generate adequate fracture predictions without the need to verbally ascertain fracture risk factors. In the future, this could allow for automated fracture prediction at the point of care to improve osteoporosis screening and treatment rates.

Digitalising Clinical Guidelines: The Challenge of Patient's Preferences.

Will digitalised clinical guidelines be compatible with individualised and personalised patient care if the disease definitions and classifications used within them contain embedded preferences? Taking bone health as a case study, we found the dominant definition of osteoporosis installs the consensus preference judgement of a 1992 International Expert Committee in the form of a threshold cut-off on the bone mineral density continuum. We found that subsequent UK clinical guidelines follow suit on this diagnostic threshold, but also endorse preference-sensitive thresholds for interventions to prevent fractures, including ones underpinned by cost-effectiveness analysis. The resulting pre-emption of patient's preferences needs to be removed if 'computable' guidelines are to be reconcilable with personalised care. The challenges to be met in digitalisation therefore include major conceptual ones as well as the technical ones that are currently the almost exclusive focus.

Development and reporting of artificial intelligence in osteoporosis management.

An abundance of medical data and enhanced computational power have led to a surge in Artificial Intelligence (AI) applications. Published studies involving AI in bone and osteoporosis research have increased exponentially, raising the need for transparent model development and reporting strategies. This review offers a comprehensive overview and systematic quality assessment of AI articles in osteoporosis while highlighting recent advancements. A systematic search in the PubMed database, from December 17th, 2020, to February 1st, 2023 was conducted to identify AI articles that relate to osteoporosis. The quality assessment of the studies relied on the systematic evaluation of 12 quality items derived from the MI-CLAIM checklist. The systematic search yielded 97 articles that fell into five areas; bone properties assessment (11 articles), osteoporosis classification (26 articles), fracture detection/classification (25 articles), risk prediction (24 articles) and bone segmentation (11 articles). The average quality score for each study area was 8.9 (range: 7-11) for bone properties assessment, 7.8 (range: 5-11) for osteoporosis classification, 8.4 (range: 7-11) for fracture detection, 7.6 (range: 4-11) for risk prediction, and 9.0 (range: 6-11) for bone segmentation. A 6th area, AI-driven clinical decision support, identified the studies from the five preceding areas which aimed to improve clinician efficiency, diagnostic accuracy and patient outcomes through AI-driven models and opportunistic screening by automating or assisting with specific clinical tasks in complex scenarios. The current work highlights disparities in study quality and a lack of standardized reporting practices. Despite these limitations, a wide range of models and examination strategies have shown promising outcomes to aid in the earlier diagnosis and improve clinical decision making. Through careful consideration of sources of bias in model performance assessment, the field can build confidence in AI-based approaches, ultimately leading to improved clinical workflows and patient outcomes.

This review covers the recent advancements in artificial intelligence (AI) for managing osteoporosis, an increasingly prevalent condition that weakens bone tissues and increases fracture risk. Analyzing 97 studies from December 2020 to February 2023, the present work highlights how AI enhances bone properties assessment, osteoporosis classification, fracture detection and classification, risk prediction, and bone segmentation. A systematic qualitative assessment of the studies revealed improvements in study quality compared with the earlier review period, supported by innovative and more explainable AI approaches. AI shows promise in clinical decision support by offering novel screening tools that can help in the earlier identification of the disease, improve clinical workflows and patient prognosis. New pre-processing strategies and advanced model architectures have played a critical role in these improvements. Researchers have enhanced the accuracy and predictive performance of traditional methods by integrating clinical data with imaging data through advanced multi-factorial AI techniques. These innovations, paired with standardized development and validation processes, promise to personalize medicine and enhance patient care in osteoporosis management.

Cardiac Biomarkers are Associated with Incident Fracture Risk in Advanced Chronic Kidney Disease.

Cardiovascular disease is associated with increased fracture risk in the general population. Few data exist on the association between cardiovascular health and incident fracture risk in patients with advanced CKD, a high-risk population for fractures. We aimed to assess the link between fracture risk and cardiovascular health in a prospective cohort of 210 patients with CKD stage G4-5. Incident fractures were recorded during a prospective follow-up of 5 years. Laboratory parameters, abdominal aortic calcification score, echocardiography, ultrasound assessment of brachial artery flow-mediated dilatation and carotid intima-media thickness, and maximal stress ergometry were obtained at baseline. A total of 51 fractures were observed in 40 (19%) patients during follow-up. In separate multivariable Cox proportional hazards models adjusted for age, gender, and baseline eGFR, TnT (HR 1.007, CI 95% 1.003-1.010, p < 0.001) and ProBNP (HR 1.000, CI 95% 1.000-1.000, p = 0.017) were associated with incident fractures and the association persisted after adjusting for coronary artery disease (CAD). The patients unable to perform the ergometry test had a higher risk of incident fractures compared to others (36.1% vs 15.5%, p = 0.009). A cardiovascular composite risk score summarizing TnT, ProBNP, and ergometry data was independently associated with incident fractures in a multivariable Cox model (HR 1.373, CI 95% 1.180-1.599, p < 0.001). Patients with the lowest score were observed with no fractures, while patients with the highest score were observed with a fracture risk of 40.5% during follow-up. Risk of incident fractures is associated with biomarkers of cardiovascular health and a composite cardiovascular risk score in patients with advanced CKD.