Osteoporotic Fractures: Diagnosis, Evaluation, and Significance From the International Working Group on DXA Best Practices.

Osteoporotic fractures, also known as fragility fractures, are reflective of compromised bone strength and are associated with significant morbidity and mortality. Such fractures may be clinically silent, and others may present clinically with pain and deformity at the time of the injury. Unfortunately, and even at the time of detection, most individuals sustaining fragility fractures are not identified as having underlying metabolic bone disease and are not evaluated or treated to reduce the incidence of future fractures. A multidisciplinary international working group with representation from international societies dedicated to advancing the care of patients with metabolic bone disease has developed best practice recommendations for the diagnosis and evaluation of individuals with fragility fractures. A comprehensive narrative review was conducted to identify key articles on fragility fractures and their impact on the incidence of further fractures, morbidity, and mortality. This document represents consensus among the supporting societies and harmonizes best practice recommendations consistent with advances in research. A fragility fracture in an adult is an important predictor of future fractures and requires further evaluation and treatment of the underlying osteoporosis. It is important to recognize that most fragility fractures occur in patients with bone mineral density T scores higher than -2.5, and these fractures confirm the presence of skeletal fragility even in the presence of a well-maintained bone mineral density. Fragility fractures require further evaluation with exclusion of contributing factors for osteoporosis and assessment of clinical risk factors for fracture followed by appropriate pharmacological intervention designed to reduce the risk of future fracture. Because most low-trauma vertebral fractures do not present with pain, dedicated vertebral imaging and review of past imaging is useful in identifying fractures in patients at high risk for vertebral fractures. Given the importance of fractures in confirming skeletal fragility and predicting future events, it is recommended that an established classification system be used for fracture identification and reporting.

Race-specific FRAX models are evidence-based and support equitable care: a response to the ASBMR Task Force report on Clinical Algorithms for Fracture Risk.

Task Force on 'Clinical Algorithms for Fracture Risk' commissioned by the American Society for Bone and Mineral Research (ASBMR) Professional Practice Committee has recommended that FRAX® models in the US do not include adjustment for race and ethnicity. This position paper finds that an agnostic model would unfairly discriminate against the Black, Asian and Hispanic communities and recommends the retention of ethnic and race-specific FRAX models for the US, preferably with updated data on fracture and death hazards. In contrast, the use of intervention thresholds based on a fixed bone mineral density unfairly discriminates against the Black, Asian and Hispanic communities in the US. This position of the Working Group on Epidemiology and Quality of Life of the International Osteoporosis Foundation (IOF) is endorsed both by the IOF and the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO).

Severe atypical iliac wing fracture associated with long-term bisphosphonate use.

BACKGROUND: Bisphosphonate use is associated with atypical non-traumatic fractures, which are most commonly seen in the femur. CASE PRESENTATION: We report a 63-year-old postmenopausal woman who presented acutely with progressively worsening lumbar pain radiating to her left hip for 10 days. There was no antecedent trauma. On examination, the patient could not bear weight on her left leg due to the severity of the pain. Radiography and computed tomography of the pelvis demonstrated an iliac wing fracture which was treated conservatively. The patient had a significant past medical history of breast cancer and intense bisphosphonate use for several years which was discontinued 3 years previously. No discrete bone lesion was seen at the fracture site on computed tomography, and there was no evidence of metastatic disease elsewhere. A dual-energy X-ray absorptiometry scan showed the lowest bone mineral density T-score of - 1.2. A diagnosis of an atypical fracture related to long-term bisphosphonate therapy was made. CONCLUSION: To the best of our knowledge, this is the first reported case of an isolated iliac wing fracture associated with long-term bisphosphonate therapy in the literature. Whilst the incidence of such fractures is exceedingly rare, it is an important differential in patients with atypical fractures on long-term bisphosphonates.

Modelling future bone mineral density: Simplicity or complexity?

BACKGROUND: Osteoporotic fractures are a major global public health issue, leading to patient suffering and death, and considerable healthcare costs. Bone mineral density (BMD) measurement is important to identify those with osteoporosis and assess their risk of fracture. Both the absolute BMD and the change in BMD over time contribute to fracture risk. Predicting future fracture in individual patients is challenging and impacts clinical decisions such as when to intervene or repeat BMD measurement. Although the importance of BMD change is recognised, an effective way to incorporate this marginal effect into clinical algorithms is lacking. METHODS: We compared two methods using longitudinal DXA data generated from subjects with two or more hip DXA scans on the same machine between 2000 and 2018. A simpler statistical method (ZBM) was used to predict an individual's future BMD based on the mean BMD and the standard deviation of the reference group and their BMD measured in the latest scan. A more complex deep learning (DL)-based method was developed to cope with multidimensional longitudinal data, variables extracted from patients' historical DXA scan(s), as well as features drawn from the ZBM method. Sensitivity analyses of several subgroups was conducted to evaluate the performance of the derived models. RESULTS: 2948 white adults aged 40-90 years met our study inclusion: 2652 (90 %) females and 296 (10 %) males. Our DL-based models performed significantly better than the ZBM models in women, particularly our Hybrid-DL model. In contrast, the ZBM-based models performed as well or better than DL-based models in men. CONCLUSIONS: Deep learning-based and statistical models have potential to forecast future BMD using longitudinal clinical data. These methods have the potential to augment clinical decisions regarding when to repeat BMD testing in the assessment of osteoporosis.

Bone mineral density and fractures in patients with rheumatoid arthritis: the DXA-HIP project.

Objectives: RA is a chronic disabling disease affecting 0.5-1% of adults worldwide. People with RA have a greater prevalence of multimorbidity, particularly osteoporosis and associated fractures. Recent studies suggest that fracture risk is related to both non-RA and RA factors, whose importance is heterogeneous across studies. This study seeks to compare baseline demographic and DXA data across three cohorts: healthy controls, RA patients and a non-RA cohort with major risk factors and/or prior major osteoporotic fracture (MOF). Methods: This is a cross-sectional study using data collected from three DXA centres in the west of Ireland from January 2000 to November 2018. Results: Data were available for 30 503 subjects who met our inclusion criteria: 9539 (31.3%) healthy controls, 1797 (5.9%) with RA and 19 167 (62.8%) others. Although age, BMI and BMD were similar between healthy controls, the RA cohort and the other cohort, 289 (16.1%) RA patients and 5419 (28.3%) of the non-RA cohort had prior MOF. In the RA and non-RA cohorts, patients with previous MOF were significantly older and had significantly lower BMD at the femoral neck, total hip and spine. Conclusion: Although age, BMI and BMD were similar between a healthy control cohort and RA patients and others with major fracture risk factors, those with a previous MOF were older and had significantly lower BMD at all three measured skeletal sites. Further studies are needed to address the importance of these and other factors for identifying those RA patients most likely to experience fractures.

Prevalence of Low Bone Mass and Osteoporosis in Ireland: the Dual-Energy X-Ray Absorptiometry (DXA) Health Informatics Prediction (HIP) Project.

Osteoporosis is a common disease that has a significant impact on patients, healthcare systems, and society. World Health Organization (WHO) diagnostic criteria for postmenopausal women were established in 1994 to diagnose low bone mass (osteopenia) and osteoporosis using dual-energy X-ray absorptiometry (DXA)-measured bone mineral density (BMD) to help understand the epidemiology of osteoporosis, and identify those at risk for fracture. These criteria may also apply to men ≥50 years, perimenopausal women, and people of different ethnicity. The DXA Health Informatics Prediction (HIP) project is an established convenience cohort of more than 36,000 patients who had a DXA scan to explore the epidemiology of osteoporosis and its management in the Republic of Ireland where the prevalence of osteoporosis remains unknown. In this article we compare the prevalence of a DXA classification low bone mass (T-score < -1.0) and of osteoporosis (T-score ≤ -2.5) among adults aged ≥40 years without major risk factors or fractures, with one or more major risk factors, and with one or more major osteoporotic fractures. A total of 33,344 subjects met our study inclusion criteria, including 28,933 (86.8%) women; 9362 had no fractures or major risk factors, 14,932 had one or more major clinical risk factors, and 9050 had one or more major osteoporotic fractures. The prevalence of low bone mass and osteoporosis increased significantly with age overall. The prevalence of low bone mass and osteoporosis was significantly greater among men and women with major osteoporotic fractures than healthy controls or those with clinical risk factors. Applying our results to the national population census figure of 5,123,536 in 2022 we estimate between 1,039,348 and 1,240,807 men and women aged ≥50 years have low bone mass, whereas between 308,474 and 498,104 have osteoporosis. These data are important for the diagnosis of osteoporosis in clinical practice, and national policy to reduce the illness burden of osteoporosis. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Exploring Adaptive Cycling Interventions for Young People with Disability: An Online Survey of Providers in Australia.

Adapted cycles offer young people with disability a fun way to participate in over-ground cycling, but little is known about current practices to train and sustain cycling in this group. This study aimed to describe interventions used to introduce adaptive cycling to young people with disability and explore barriers and facilitators to adapted cycle use. A cross-sectional online survey was distributed among Australian allied health, education and recreation providers through targeted advertizing and snowball methods. Data were analysed using mixed methods and reporting was guided by the CHERRIES and CROSS checklists. There were 107 respondents with n = 90 (84.1%) who fully completed the survey. Respondents worked with riders who had cerebral palsy, neurodevelopmental disabilities and movement impairments. Adaptive cycling interventions were customized according to a rider's goals, needs and resourcing. The training of cycling skills included "an eclectic mix" of experiential learning, individual goals, task-specific training and holistic practice models. Diverse factors impacted cycling participation, with opportunities reliant on access to a supportive environment, including a suitable adapted cycle. This study found that providers viewed adaptive cycling as a therapeutic or active leisure experience within protected traffic-free environments. Strategies to extend adaptive cycling opportunities into the community are required.

Ireland DXA-FRAX may differ significantly and substantially to Web-FRAX.

Appropriate use of FRAX reduces the number of people requiring DXA scans, while contemporaneously determining those most at risk. We compared the results of FRAX with and without inclusion of BMD. It suggests clinicians to carefully consider the importance of BMD inclusion in fracture risk estimation or interpretation in individual patients. PURPOSE: FRAX is a widely accepted tool to estimate the 10-year risk of hip and major osteoporotic fracture in adults. Prior calibration studies suggest this works similarly with or without the inclusion of bone mineral density (BMD). The purpose of the study is to compare within-subject differences between FRAX estimations derived using DXA and Web software with and without the inclusion of BMD. METHOD: A convenience cohort was used for this cross-sectional study, consisting of 1254 men and women aged between 40 and 90 years who had a DXA scan and complete validated data available for analysis. FRAX 10-year estimations for hip and major osteoporotic fracture were calculated using DXA software (DXA-FRAX) and the Web tool (Web-FRAX), with and without BMD. Agreements between estimates within each individual subject were examined using Bland-Altman plots. We performed exploratory analyses of the characteristics of those with very discordant results. RESULTS: Overall median DXA-FRAX and Web-FRAX 10-year hip and major osteoporotic fracture risk estimations which include BMD are very similar: 2.9% vs. 2.8% and 11.0% vs. 11% respectively. However, both are significantly lower than those obtained without BMD: 4.9% and 14% respectively, P < 0.001. Within-subject differences between hip fracture estimates with and without BMD were < 3% in 57% of cases, between 3 and 6% in 19% of cases, and > 6% in 24% of cases, while for major osteoporotic fractures such differences are < 10% in 82% of cases, between 10 and 20% in 15% of cases, and > 20% in 3% of cases. CONCLUSIONS: Although there is excellent agreement between the Web-FRAX and DXA-FRAX tools when BMD is incorporated, sometimes there are very large differences for individuals between results obtained with and without BMD. Clinicians should carefully consider the importance of BMD inclusion in FRAX estimations when assessing individual patients.

Outcomes of COVID-19 in people with rheumatic and musculoskeletal disease in Ireland over the first 2 years of the pandemic.

BACKGROUND: Poor COVID-19 outcomes occur with higher frequency in people with rheumatic and musculoskeletal diseases (RMD). Better understanding of the factors involved is crucial to informing patients and clinicians regarding risk mitigation. AIM: To describe COVID-19 outcomes for people with RMD in Ireland over the first 2 years of the pandemic. METHODS: Data entered into the C19-GRA provider registry from Ireland between 24th March 2020 and 31st March 2022 were analysed. Differences in the likelihood of hospitalisation and mortality according to demographic and clinical variables were investigated. RESULTS: Of 237 cases included, 59.9% were female, 95 (41.3%) were hospitalised, and 22 (9.3%) died. Hospitalisation was more common with increasing age, gout, smoking, long-term glucocorticoid use, comorbidities, and specific comorbidities of cardiovascular and pulmonary disease, and cancer. Hospitalisation was less frequent in people with inflammatory arthritis and conventional synthetic or biologic disease-modifying antirheumatic drug use. Hospitalisation had a U-shaped relationship with disease activity, being more common in both high disease activity and remission. Mortality was more common with increasing age, gout, smoking, long-term glucocorticoid use, comorbidities, and specific comorbidities of cardiovascular disease, pulmonary disease, and obesity. Inflammatory arthritis was less frequent in those who died. CONCLUSION: Hospitalisation or death were more frequently experienced by RMD patients with increasing age, certain comorbidities including potentially modifiable ones, and certain medications and diagnoses amongst other factors. These are important 'indicators' that can help risk-stratify and inform the management of RMD patients.

Impact of adapted bicycle riding on outcomes for children and adolescents with disabilities: A systematic review.

AIM: To review the evidence for the effects of adapted bicycle riding on body structures and functions, activity, participation, and quality of life outcomes in children with disabilities, along with family-level participation outcomes. METHOD: A systematic review with searches of nine electronic databases to identify studies involving participants with a developmental disability aged 4 to 18 years who used a dynamic adapted bicycle was completed in August 2021. Risk of bias was assessed based on individual study designs. A narrative synthesis integrated the findings of the included studies. Certainty of evidence was synthesized using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. RESULTS: Ten studies were included with 234 participants. Five studies reported outcomes at the body structures and functions level, ten reported activity-level outcomes, two reported participation-related outcomes, and none assessed quality of life or family participation in social and recreational activities. INTERPRETATION: Adapted bicycle riding interventions may improve gross motor function, enhance lower-limb muscle strength, and promote physical activity; however, certainty of evidence of effects was rated very low using GRADE. Further research is required to understand the impact of adapted bicycle riding on the participation outcomes of children and adolescents with disabilities and on family-level participation in social and recreational activities. WHAT THIS PAPER ADDS: Adapted bicycle riding interventions may improve motor functions and physical activity. Evidence about participation outcomes after adapted bicycle riding is limited. Research on adapted bicycle riding interventions in natural settings is needed.

Risk assessment tools for osteoporosis and fractures in 2022.

Osteoporosis is one of the frequently encountered non-communicable diseases in the world today. Several hundred million people have osteoporosis, with many more at risk. The clinical feature is a fragility fracture (FF), which results in major reductions in the quality and quantity of life, coupled with a huge financial burden. In recognition of the growing importance, the World Health Organisation established a working group 30 years ago tasked with providing a comprehensive report to understand and assess the risk of osteoporosis in postmenopausal women. Dual-energy X-ray absorptiometry (DXA) is the most widely endorsed technology for assessing the risk of fracture or diagnosing osteoporosis before a fracture occurs, but others are available. In clinical practice, important distinctions are essential to optimise the use of risk assessments. Traditional tools lack specificity and were designed for populations to identify groups at higher risk using a 'one-size-fits-all' approach. Much has changed, though the purpose of risk assessment tools remains the same. In 2022, many tools are available to aid the identification of those most at risk, either likely to have osteoporosis or suffer the clinical consequence. Modern technology, enhanced imaging, proteomics, machine learning, artificial intelligence, and big data science will greatly advance a more personalised risk assessment into the future. Clinicians today need to understand not only which tool is most effective and efficient for use in their practice, but also which tool to use for which patient and for what purpose. A greater understanding of the process of risk assessment, deciding who should be screened, and how to assess fracture risk and prognosis in older men and women more comprehensively will greatly reduce the burden of osteoporosis for patients, society, and healthcare systems worldwide. In this paper, we review the current status of risk assessment, screening and best practice for osteoporosis, summarise areas of uncertainty, and make some suggestions for future developments, including a more personalised approach for individuals.

Conceptual design of the dual X-ray absorptiometry health informatics prediction system for osteoporosis care.

Osteoporotic fractures are a major and growing public health problem, which is strongly associated with other illnesses and multi-morbidity. Big data analytics has the potential to improve care for osteoporotic fractures and other non-communicable diseases (NCDs), reduces healthcare costs and improves healthcare decision-making for patients with multi-disorders. However, robust and comprehensive utilization of healthcare big data in osteoporosis care practice remains unsatisfactory. In this paper, we present a conceptual design of an intelligent analytics system, namely, the dual X-ray absorptiometry (DXA) health informatics prediction (HIP) system, for healthcare big data research and development. Comprising data source, extraction, transformation, loading, modelling and application, the DXA HIP system was applied in an osteoporosis healthcare context for fracture risk prediction and the investigation of multi-morbidity risk. Data was sourced from four DXA machines located in three healthcare centres in Ireland. The DXA HIP system is novel within the Irish context as it enables the study of fracture-related issues in a larger and more representative Irish population than previous studies. We propose this system is applicable to investigate other NCDs which have the potential to improve the overall quality of patient care and substantially reduce the burden and cost of all NCDs.

Temporal trends in COVID-19 outcomes in people with rheumatic diseases in Ireland: data from the COVID-19 Global Rheumatology Alliance registry.

OBJECTIVES: Although evidence is accumulating globally, data on outcomes in rheumatic disease and COVID-19 in Ireland are limited. We used data from the COVID-19 Global Rheumatology Alliance (C19-GRA) to describe time-varying COVID-19 outcomes for people with rheumatic disease in Ireland. METHODS: Data entered into the C19-GRA provider registry from Ireland between 24 March 2020 and 9 July 2021 were analysed. Differences in the likelihood of hospitalization and mortality according to demographic and clinical variables were investigated using Chi-squared test or Fisher's exact test, as appropriate. Trends in odds of hospitalization and mortality over time were investigated using logistic regression with the time period as a categorical variable. RESULTS: Of 212 cases included, 59.4% were female and median age was 58.0 years (range 13-96). Of the 212 cases, 92 (43%) were hospitalized and 22 (10.4%) died. Increasing age, a diagnosis of gout, ever smoking, glucocorticoid use, having comorbidities and specific comorbidities of cancer, cardiovascular and pulmonary disease were more common in those hospitalized. A diagnosis of inflammatory arthritis, csDMARD and/or b/tsDMARD use were less frequent in those hospitalized. Increasing age, a diagnosis of gout, ever smoking, having comorbidities and specific comorbidities of obesity, cardiovascular and pulmonary disease were more common in those who died. Odds of hospitalization or mortality did not change over time. CONCLUSION: No temporal trend was observed in either COVID-19-related hospitalization or mortality outcomes for people with rheumatic disease in Ireland.

How does proximal femur BMD of healthy Irish adults compare to NHANES III? Results of the DXA-HIP Project.

This study examines the distribution of proximal femur bone mineral density in a cohort of healthy Irish adults. These values are similar to those of the NHANES III Caucasian cohorts, supporting international recommendations to use this reference group for calculating DXA T-scores and Z-scores in Irish adults. INTRODUCTION: Bone mineral density (BMD) is widely used in the assessment and monitoring of osteoporosis. International guidelines recommend referencing proximal femur BMD measurements to NHANES III values to calculate T-scores and Z-scores, but their validity for the Irish population has not been established. In this study, we compare BMD values of healthy Irish Caucasian adults to those of Caucasian men and women in the NHANES III cohort study. METHODS: Men and women without bone disease and/or major risk factors for fracture, and/or not taking osteoporosis medication who had a screening DXA scan (GE Lunar, Madison, USA) at one of 3 centres in the West of Ireland were selected for this study. We calculated the mean and standard deviation (SD) used by GE for calculating white female NHANES III T-scores at the femoral neck and total hip sites, and used these values to calculate white female T-scores for men and women across each decade in our study sample. We calculated mean white female T-scores for each decade for both Caucasian men and women in the NHANES III cohort using the published data. Finally, we plotted these results against those of our study population. RESULTS: In total, 6729 (18.5%) of 36,321 adults were included in our analyses, including 5923 (88%) women. The majority of the study population were aged between 40 and 89 years. Our results show that the proximal femur BMD of healthy Irish men and women is broadly similar to that of the NHANES III reference population, especially middle-aged adults. Results differ for very young and very old adults, likely reflecting the small sample size and a referral bias. Further studies of these populations and other manufacturers could help clarify these uncertainties. CONCLUSIONS: Our results support using the NHANES III reference population to calculate proximal femur adult T-scores and Z-scores to establish the presence or prevalence of osteoporosis in Ireland.

Predictors of hospitalization in patients with rheumatic disease and COVID-19 in Ireland: data from the COVID-19 global rheumatology alliance registry.

OBJECTIVES: Given the limited data regarding the risk of hospitalization in patients with rheumatic disease and coronavirus disease 2019 (COVID-19) in Ireland, we used the COVID-19 Global Rheumatology Alliance (GRA) registry data to study outcomes and their predictors. The primary objective was to explore potential predictors of hospitalization. METHODS: We examined data on patients and their disease-related characteristics entered in the COVID-19 GRA provider registry from Ireland (from 24 March 2020 to 31 August 2020). Multivariable logistic regression was used to assess the association of demographic and clinical characteristics with hospitalization. RESULTS: Of 105 patients, 47 (45.6%) were hospitalized and 10 (9.5%) died. Multivariable logistic regression analysis showed that age [odds ratio (OR) = 1.06, 95% CI 1.01, 1.10], number of co-morbidities (OR = 1.93, 95% CI 1.11, 3.35) and glucocorticoid use (OR = 15.01, 95% CI 1.77, 127.16) were significantly associated with hospitalization. A diagnosis of inflammatory arthritis was associated with lower odds of hospitalization (OR = 0.09, 95% CI 0.02, 0.32). CONCLUSION: Increasing age, co-morbidity burden and glucocorticoid use were associated with hospitalization, whereas a diagnosis of inflammatory arthritis was associated with lower odds of hospitalization.

Hole Polaron Migration in Bulk Phases of TiO2 Using Hybrid Density Functional Theory.

Understanding charge-carrier transport in semiconductors is vital to the improvement of material performance for various applications in optoelectronics and photochemistry. Here, we use hybrid density functional theory to model small hole polaron transport in the anatase, brookite, and TiO2-B phases of titanium dioxide and determine the rates of site-to-site hopping as well as thermal ionization into the valance band and retrapping. We find that the hole polaron mobility increases in the order TiO2-B < anatase < brookite and there are distinct differences in the character of hole polaron migration in each phase. As well as having fundamental interest, these results have implications for applications of TiO2 in photocatalysis and photoelectrochemistry, which we discuss.

Vertebral Fractures in Ireland: A Sub-analysis of the DXA HIP Project.

Osteoporosis is an important global health problem resulting in fragility fractures. The vertebrae are the commonest site of fracture resulting in extreme illness burden, and having the highest associated mortality. International studies show that vertebral fractures (VF) increase in prevalence with age, similarly in men and women, but differ across different regions of the world. Ireland has one of the highest rates of hip fracture in the world but data on vertebral fractures are limited. In this study we examined the prevalence of VF and associated major risk factors, using a sample of subjects who underwent vertebral fracture assessment (VFA) performed on 2 dual-energy X-ray absorptiometry (DXA) machines. A total of 1296 subjects aged 40 years and older had a valid VFA report and DXA information available, including 254 men and 1042 women. Subjects had a mean age of 70 years, 805 (62%) had prior fractures, mean spine T-score was - 1.4 and mean total hip T-scores was - 1.2, while mean FRAX scores were 15.4% and 4.8% for major osteoporotic fracture and hip fracture, respectively. Although 95 (7%) had a known VF prior to scanning, 283 (22%) patients had at least 1 VF on their scan: 161 had 1, 61 had 2, and 61 had 3 or more. The prevalence of VF increased with age from 11.5% in those aged 40-49 years to > 33% among those aged ≥ 80 years. Both men and women with VF had significantly lower BMD at each measured site, and significantly higher FRAX scores, P < 0.01. These data suggest VF are common in high risk populations, particularly older men and women with low BMD, previous fractures, and at high risk of fracture. Urgent attention is needed to examine effective ways to identify those at risk and to reduce the burden of VF.

Utility of Osteoporosis Self-Assessment Tool as a Screening Tool for Osteoporosis in Irish Men and Women: Results of the DXA-HIP Project.

Many algorithms have been developed and publicised over the past 2 decades for identifying those most likely to have osteoporosis or low BMD, or at increased risk of fragility fracture. The Osteoporosis Self-assessment Tool index (OSTi) is one of the oldest, simplest, and widely used for identifying men and women with low BMD or osteoporosis. OSTi has been validated in many cohorts worldwide but large studies with robust analyses evaluating this or other algorithms in adult populations residing in the Republic of Ireland are lacking, where waiting times for public DXA facilities are long. In this study we evaluated the validity of OSTi in men and women drawn from a sampling frame of more than 36,000 patients scanned at one of 3 centres in the West of Ireland. 18,670 men and women aged 40 years and older had a baseline scan of the lumbar spine femoral neck and total hip available for analysis. 15,964 (86%) were female, 5,343 (29%) had no major clinical risk factors other than age, while 5,093 (27%) had a prior fracture. Approximately 2/3 had a T-score ≤-1.0 at one or more skeletal sites and 1/3 had a T-score ≤-1.0 at all 3 skeletal sites, while 1 in 5 had a DXA T-score ≤-2.5 at one or more skeletal sites and 5% had a T-score ≤-2.5 at all 3 sites. OSTi generally performed well in our population with area under the curve (AUC) values ranging from 0.581 to 0.881 in men and 0.701 to 0.911 in women. The performance of OSTi appeared robust across multiple sub-group analyses. AUC values were greater for women, proximal femur sites, those without prior fractures and those not taking osteoporosis medication. Optimal OSTi cut-points were '2' for men and '0' for women in our study population. OSTi is a simple and effective tool to aid identification of Irish men and women with low BMD or osteoporosis. Use of OSTi could improve the effectiveness of DXA screening programmes for older adults in Ireland.

Challenges and opportunities for quality densitometry in Latin America.

Latin America and the Caribbean region account for 8% of the world's total population. Experts from 18 countries were invited to contribute to this article to provide the best available data on the number, types, and quality of densitometry, DXA experts, the local/national incidence and prevalence of osteoporosis and fragility fractures, and other uses and information on the challenges and opportunities for quality densitometry with examples of local initiatives. Osteoporosis is the primary reason for densitometry in our region, which is not a priority for public health in most countries. Access and quality are major challenges, and there is a clear trend to concentrate on densitometry services in the largest cities. Urgent action is needed to face the rapidly increasing burden of osteoporosis in our region, including robust and up to date epidemiology, access to health professionals, and quality densitometry. Health professionals require better access to training, courses, and other activities at a more local or regional level.

Machine Learning Can Improve Clinical Detection of Low BMD: The DXA-HIP Study.

BACKGROUND: Identification of those at high risk before a fracture occurs is an essential part of osteoporosis management. This topic remains a significant challenge for researchers in the field, and clinicians worldwide. Although many algorithms have been developed to either identify those with a diagnosis of osteoporosis or predict their risk of fracture, concern remains regarding their accuracy and application. Scientific advances including machine learning methods are rapidly gaining appreciation as alternative techniques to develop or enhance risk assessment and current practice. Recent evidence suggests that these methods could play an important role in the assessment of osteoporosis and fracture risk. METHODS: Data used for this study included Dual-energy X-ray Absorptiometry (DXA) bone mineral density and T-scores, and multiple clinical variables drawn from a convenience cohort of adult patients scanned on one of 4 DXA machines across three hospitals in the West of Ireland between January 2000 and November 2018 (the DXA-Heath Informatics Prediction Cohort). The dataset was cleaned, validated and anonymized, and then split into an exploratory group (80%) and a development group (20%) using the stratified sampling method. We first established the validity of a simple tool, the Osteoporosis Self-assessment Tool Index (OSTi) to identify those classified as osteoporotic by the modified International Society for Clinical Densitometry DXA criteria. We then compared these results to seven machine learning techniques (MLTs): CatBoost, eXtreme Gradient Boosting, Neural network, Bagged flexible discriminant analysis, Random forest, Logistic regression and Support vector machine to enhance the discrimination of those classified as osteoporotic or not. The performance of each prediction model was measured by calculating the area under the curve (AUC) with 95% confidence interval (CI), and was compared against the OSTi. RESULTS: A cohort of 13,577 adults aged ≥40 yr at the age of their first scan was identified including 11,594 women and 1983 men. 2102 (18.13%) females and 356 (17.95%) males were identified with osteoporosis based on their lowest T-score. The OSTi performed well in our cohort in both men (AUC 0.723, 95% CI 0.659-0.788) and women (AUC 0.810, 95% CI 0.787-0.833). Four MLTs improved discrimination in both men and women, though the incremental benefit was small. eXtreme Gradient Boosting showed the most promising results: +4.5% (AUC 0.768, 95% CI 0.706-0.829) for men and +2.3% (AUC 0.833, 95% CI 0.812-0.853) for women. Similarly MLTs outperformed OSTi in sensitivity analyses-which excluded those subjects taking osteoporosis medications-though the absolute improvements differed. CONCLUSION: The OSTi retains an important role in identifying older men and women most likely to have osteoporosis by bone mineral density classification. MLTs could improve DXA detection of osteoporosis classification in older men and women. Further exploration of MLTs is warranted in other populations, and with additional data.