Osteoporosis Risk Assessment Research Articles

Comparative evaluation of trabecular bone density in Hounsfield units in the lumbar native CT cross-section for osteoporosis diagnosis and fracture risk determination by different examiners

An increasing loss of bone mineral density (BMD) in the axial skeleton leads to osteoporosis and fractures, with an increase found in the thoracic and thoracolumbar regions. The extent to which an examiner-independent assessment of the extent of osteoporosis and fracture risk determination is possible by determining the trabecular density in Hounsfield units (HU) in the spine should be examined. The next question was whether quantitative BMD values can be calculated from the HU values. 225 patients (pt.) with an average age of 64.9 ± 13.1 years and abody-mass-index (BMI) of 26.8 ± 6.8 kg/m2, of which 37were men and 188 were women, were examined to determine whether they had osteoporosis. The BMD was determined in mg/cm3 using quantitative computed tomography (QCT) in the lumbar region. After anonymization by three experienced radiologists, an additional measurement of the trabecular bone density in HU, was carried out in the same vertebral bodies (atotal of 675 vertebral bodies), each using aregion of interest (ROI) positioned in the midvertebral cancellous space in the sagittal reformed CT image. In additional lateral X‑rays of the thoracic and lumbar spine, vertebral fractures were detected and graded. Sacral insufficiency fractures that occurred at the same time were also recorded. The median BMD was 73.2 (57.05-104.17) mg/cm3 and the median HU was 89.93 (67.90-126.95). With acorrelation of 0.988 (p < 0.001), quantitative values in mg/cm3 can be calculated using the following formula: Xq = 12.1 + 0.68 × HU. With HU values less than 69.84 and aBMD of the lumbar spine below 59.54 mg/cm3, there was asignificantly increased number of OVF. At least one OVF was found in 137/225 pt. In 17/137 pt., sacral fractures were also found; these patients showed the significantly lowest values with amedian BMD of 41.81 (16.2-53.7) mg/cm3. Comparable HU values were determined independently of the examiners (p > 0.05). The trabecular density measurements in HU values can be converted into quantitative BMD values in mg/cm3, which enables agood assessment of osteoporosis and fracture risk. Taking the results obtained into account, an opportunistic evaluation using HU values in native CT alone seems quite possible. Experienced examiners have arrived at comparable results.

Post-Stroke Osteoporosis Screening: A Scoping Review.

There are no specific screening recommendations for post-stroke osteoporosis despite evidence that people post-stroke are at heightened risk of fragility fractures. Our objective was to explore the extent of evidence and map the current literature available for osteoporosis screening in the post-stroke population. This scoping review searched for articles in Medline, Embase, and CINAHL databases published in English before May 2024, involving osteoporosis screening for adults after stroke. Title and abstract screening as well as full text review and data extraction was performed by two reviewers. Analysis of the studies is descriptive and narrative. Eight articles met inclusion criteria: five published articles and three peer-reviewed conference abstracts. Three study designs were utilized: four cross-sectional studies, three cohort studies, and one survey. Four studies investigated post-stroke osteoporosis screening rates, two looked at screening pathways for post-stroke osteoporosis, and two assessed novel osteoporosis screening tools. No post-stroke osteoporosis screening guidelines were found. Across all included studies, reported screening rates for post-stroke osteoporosis were less than 10%. This scoping review emphasizes the need for osteoporosis screening guidelines and risk assessment tools specific to the post-stroke population.

Risk of osteoporotic fractures in menopausal women with common mental health diagnoses prescribed SSRIs/SNRIs: cohort and self-controlled case series analyses

SummaryIn a population-based cohort study of menopausal women with common mental health diagnoses, SSRIs/SNRIs were associated with a 32% increased risk of osteoporotic fractures. The risk of osteoporotic fractures was particularly increased for longer periods of treatment with SSRIs/SNRIs (> 5 years) and in younger menopausal women (< 50 years old).PurposeTo investigate the association between selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) and the risk of osteoporotic fractures (OF) in menopausal women with common mental health diagnoses (CMHD).MethodsWe conducted the study with two designs (cohort and self-controlled case series [SCCS]), using the IQVIA Medical Research Database (IMRD) UK. The source population comprised women aged ≥ 50 years and women with a record indicating menopause (< 50 years). All women had a recorded CMHD. For the cohort analysis, the risk of OFs was estimated by comparing women prescribed SSRIs/SNRIs (exposed) to those not exposed. Cox regression was used to estimate hazard ratios (HR) with 95% confidence intervals (CIs). For the SCCS, women acted as their own controls; periods of exposure to SSRIs/SNRIs were compared to periods of non-exposure using conditional Poisson regression to estimate incidence rate ratios (IRR) with 95% CIs.ResultsWe identified 292,848 women, of whom 35,222 experienced OFs within a median follow-up of 6.01 years. We found strong evidence of an association between SSRIs/SNRIs and the risk of OFs (adjusted HR = 1.32, 95% CI:1.29–1.35). Compared to periods of no exposure, SSRIs/SNRIs increased the risk of OFs during the first 30 days (IRR = 1.38, 95% CI:1.26–1.51), during the first 90 days (IRR = 1.58, 95% CI: 1.48–1.69), and the remaining exposure (IRR = 1.42, 95% CI:1.37–1.48).ConclusionsIn a population of menopausal women with CMHDs, the prescribing of SSRIs/SNRIs antidepressants was associated with a higher risk of OFs. Careful assessment of osteoporosis risk needs to be considered when treating menopausal women with SSRIs/SNRIs antidepressants.

Nonlinear relationship between cardiometabolic index and bone mineral density in U.S. adults: the mediating role of percent body fat.

Both lipid metabolism and obesity are crucial factors in osteoporosis, influencing the relevance of the cardiometabolic index (CMI), a new body fat index incorporating obesity and lipid metrics. Our study aims to explore the relationship between CMI and lumbar spine bone mineral density (BMD) and the mediating role of body fat percentage. Utilizing the National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2018, we conducted a cross-sectional analysis. We employed multiple linear regression models, subgroup analyses, generalized additive models (GAM), smooth curve fitting, and mediation analysis to evaluate the linear and nonlinear relationships between CMI and lumbar spine BMD. The study involved 5,124 participants with an average lumbar spine BMD of 1.03 ± 0.15g/cm2. We identified a negative correlation between CMI and lumbar spine BMD (β = -0.015; 95% CI: -0.023, -0.008). Nonlinear associations were evident, with inflection points at CMI values of 1.12 and 2.86. Subgroup analyses showed consistent negative correlations across all categories without significant differences (p for interaction > 0.05). Moreover, body fat percentage negatively correlated with BMD (β = -0.005; 95% CI: -0.006, -0.004) and mediated 9.41% of the relationship between CMI and BMD. Increased CMI levels are associated with lower lumbar spine BMD, with body fat percentage significantly mediating this relationship. This underscores the importance of managing body composition in the context of bone health, highlighting CMI's potential utility in osteoporosis risk assessment.

Validation of Ten Osteoporosis Screening Tools in Rural Communities of Taiwan.

Patients with osteoporosis are at risk of fractures, which can lead to immobility and reduced quality of life. Early diagnosis and treatment are crucial for preventing fractures, but many patients are not diagnosed until after a fracture has occurred. This study aimed to evaluate the performance of 10 osteoporosis screening tools (OSTs) in rural communities of Taiwan. In this prospective study, a total of 567 senior citizens from rural communities underwent bone mineral density (BMD) measurement using dual-energy X-ray absorptiometry (DXA) and ten OSTs were administered. Discrimination analysis was performed using the area under the receiver operating characteristic curve (AUROC). Primary outcomes included area under curve (AUC) value, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The DXA examination revealed that 63.0% of females and 22.4% of males had osteoporosis. Among females, Osteoporosis Index of Risk (OSIRIS) and Osteoporosis Self-Assessment Tool for Asians (OSTA) presented the best AUC value with 0.71 (0.66-0.76) and 0.70 (0.66-0.75), respectively. Among males, BWC had the best AUC value of 0.77 (0.67-0.86), followed by OSTA, Simple Calculated Osteoporosis Risk Estimation (SCORE), and OSIRIS. OSTA and OSIRIS showed acceptable performance in both genders. The specificity of Fracture Risk Assessment Tool (FRAX-H), SCORE, National Osteoporosis Foundation Score, OSIRIS, Osteoporosis Risk Assessment Instrument, Age, Bulk, One or Never Estrogen (ABONE), and Body weight criteria increased in both genders after applying the optimum cut-off. Considering it high AUC and simplicity of use, OSTA appeared to be the recommended tool for seniors of both genders among the ten OSTs. This study provides a viable reference for future development of OSTs in Taiwan. Further adjustment according to epidemiological data and risk factors is recommended while applying OSTs to different cohorts.

Are Radiographic Changes in the Mandibular Canal Associated With Bone Mineral Density?

Osteoporosis, highly prevalent among postmenopausal women, significantly reduces bone density and increases the risk of fractures. Cortical bone, which constitutes the largest calcium deposit in the human skeleton, is primarily affected in various conditions, including osteoporosis. Due to its visibility in panoramic radiography, the cortical area of the mandibular canal could be valuable in assessing decreases in bone mineral density (BMD). The study aimed to characterize and compare changes in the cortices of the mandibular canal between normal, osteopenic, and osteoporotic postmenopausal women. Our cross-sectional study analyzed postmenopausal patients. We included only patients with panoramic radiographs with good quality and who underwent osteoporosis risk assessment by dual-energy x-ray absorptiometry (DXA). BMD was measured by DXA at 3 sites (spine, femur, and forearm) and used to classify the patients into normal, osteopenic, or osteoporotic. This classification remained consistent across all measurement sites. The main outcome variable was BMD of the mandibular canal cortices measured using black pixel intensity. Demographic covariates, including age, weight, height, and BMD, were assessed. One-way analysis of variance between groups considering a P<.05. The relationship between covariates and dependent variables was assessed using the Pearson correlation test. The sample comprised 52 postmenopausal women aged more than 40 years (mean age 61±10years), 26 (50%) normal, 18 (35%) osteopenic, and 8 (15%) osteoporotic. Significant differences were observed in the percentage of black pixels in the mandibular ramus between the groups. In this region, the average percentage of black pixels was 3.19% (± 0.65) for the normal group, 2.78% (±0.65) for the osteopenia group, and 2.35% (± 0.65) for the osteoporosis group (P=.015). No significant differences were found in other mandibular regions. Our findings demonstrate an association between BMD assessed in the mandibular canal cortex and the presence of osteoporosis as determined by DXA. While the observed differences in black pixel percentages in the mandibular ramus are minor, they are statistically significant, suggesting that panoramic radiography may serve as an adjunctive tool for osteoporosis screening.

Menopausal wellbeing: navigating quality of life and osteoporosis risk.

Multifaceted dimensions influence the quality of life among post-menopausal women. Osteoporosis, a condition characterized by fragile bones, poses a significant risk, potentially leading to fractures and decreased wellbeing. This study aims to assess the quality of life of postmenopausal women, its determinants, and also the risk of osteoporosis among them. A cross-sectional study was done among 379 post-menopausal women residing in rural and urban areas of Ernakulam district, Kerala, India. They were selected by probability proportional to size sampling from 10 clusters. Quality of life was measured using MENQOL-I questionnaire and osteoporosis risk assessment was done using OSTA score. The study participants had a mean age of 60 years, (standard deviation of 6.83 years). On average, menopause occurred at 50.58 years (standard deviation of 4.28 years). The most common symptoms impacting quality of life among postmenopausal women were psychosocial symptoms, followed by physical and vasomotor symptoms. Furthermore, a high proportion (63.6%) of participants were at risk for osteoporosis. History of fracture, concern of falling, marital status and having an insurance, are factors associated with various domains of quality of life. This study underscores the complex interplay of demographic factors, menopausal experiences, and their impact on the participants' quality of life. The prevalence of psychosocial symptoms and the significant risk of osteoporosis call for tailored healthcare interventions. Postmenopausal women with history of fracture, high concern of fall and single women require special attention. Encouraging women to take up selfcare practices will help during the menopausal transition to have a good quality of life.

Osteoporosis and fracture risk assessment in adults with ischaemic stroke

PurposeTo study the prevalence of osteoporosis, falls and fractures in adults with ischaemic stroke.MethodsObservational cohort study of adults aged ≥ 50 years admitted with ischaemic stroke over a 12-month period were invited to participate in a telephone interview one-year post-stroke to ascertain falls and fracture. A Fracture Risk After Ischaemic Stroke (FRAC-stroke) score was calculated.ResultsOf the 1267 patients admitted to the stroke unit between 1 January 2020 and 31 December 2020, 624 had a modified Rankin Score documented. Of these, 316 adults ≥ 50 years had ischaemic stroke and 131 consented to a telephone interview. Mean age was 72.4 ± 10.7 years and 36.6% were female. 34 patients (25.9%) had a FRAC-stroke score of ≥ 15, equating to ≥ 5% risk of fracture in the year following stroke. Eleven (8.4%) patients (6 female) had a minimal trauma fracture in the 12 months post-stroke. There was a significant difference in patients experiencing falls pre- and post-stroke (19.8% vs 31.3%, p = 0.04). FRAC-stroke score was higher in those who had a fracture post stroke compared those who did not (20.4 vs 8.9, p < 0.001). Receiver operating characteristic analysis found an area under the curve of 0.867 for FRAC-stroke score (95% CI 0.785–0.949, p < 0.005). The optimal cutoff value for FRAC-stroke score predicting fracture was 12 with a sensitivity of 90.9% and specificity of 70%.ConclusionThe FRAC-stroke score is a simple clinical tool that can be used to identify patients at high risk of fracture post-stroke who would most benefit from osteoporosis therapy.SummaryStroke is a risk factor for fracture due to immobilisation, vitamin D deficiency and increased falls risk. This study found that a simple bedside tool, the FRAC-stroke score, can predict fracture after ischaemic stroke. This will allow clinicians to plan treatment of osteoporosis prior to discharge from a stroke unit.

Guidelines for fracture risk assessment and management of osteoporosis in postmenopausal women and men above the age of 50 in Qatar

SummaryWe present comprehensive guidelines for osteoporosis management in Qatar. Formulated by the Qatar Osteoporosis Association, the guidelines recommend the age-dependent Qatar fracture risk assessment tool for screening, emphasizing risk-based treatment strategies and discouraging routine dual-energy X-ray scans. They offer a vital resource for physicians managing osteoporosis and fragility fractures nationwide.PurposeOsteoporosis and related fragility fractures are a growing public health issue with an impact on individuals and the healthcare system. We aimed to present guidelines providing unified guidance to all healthcare professionals in Qatar regarding the management of osteoporosis.MethodsThe Qatar Osteoporosis Association formulated guidelines for the diagnosis and management of osteoporosis in postmenopausal women and men above the age of 50. A panel of six local rheumatologists who are experts in the field of osteoporosis met together and conducted an extensive review of published articles and local and international guidelines to formulate guidance for the screening and management of postmenopausal women and men older than 50 years in Qatar.ResultsThe guidelines emphasize the use of the age-dependent hybrid model of the Qatar fracture risk assessment tool for screening osteoporosis and risk categorization. The guidelines include screening, risk stratification, investigations, treatment, and monitoring of patients with osteoporosis. The use of a dual-energy X-ray absorptiometry scan without any risk factors is discouraged. Treatment options are recommended based on risk stratification.ConclusionGuidance is provided to all physicians across the country who are involved in the care of patients with osteoporosis and fragility fractures.

High Body Fat as a Predictor of Osteoporosis Risk in Postmenopausal Women: Insights From a Community-Based Cross-Sectional Study in Rural South India.

Osteoporosis poses a significant health burden, particularly among postmenopausal women. While obesity in the form of BMI has been implicated in various health conditions, the relationship between waist-hip ratio (WHR) and osteoporosis remains debated. This study aims to estimate the prevalence of osteoporosis risk and explore the association between WHR and osteoporosis risk among postmenopausal women in rural South India. A community-based cross-sectional study was conducted in the Chengalpattu district of Tamil Nadu. The study enrolled 435 postmenopausal women aged 45 years and above and the data were collected on socio-demographic characteristics, anthropometric measurements, and osteoporosis risk assessment using the Osteoporosis Self-assessment Tool for Asian Women (OSTA) scale. Logistic regression analysis was performed to identify factors associated with osteoporosis risk with 95%CI. The mean (SD) age of participants was 54.5 (8.6) years, 87% were married, 33% were illiterate with mean (SD) WHR of 0.88 (0.1). Around 80.5% of the participants were categorized as low risk, 16.1% as intermediate risk, and 3.5% as high risk based on OSTA scores. Older age, lower educational attainment, and higher waist-hip ratio were significantly associated with increased osteoporosis risk. This community-based study found a 20% osteoporosis risk among postmenopausal women using the OSTA scale, with age, lower education, and waist-hip ratio as key determinants. Early identification and interventions, particularly targeting older and obese individuals, are crucial to alleviate the burden and complications of osteoporosis.

The association of FRAX with predictors of falls in the assessment of postmenopausal osteoporosis in Turkey: the fracture study of Turkey (FRACT study)

SummaryAlthough FRAX is used for fracture risk evaluation, this tool does not include balance and fall risk. The association between the predictors of falls and high FRAX scores we found in this study suggests that risk indicators for falls may add substantial value to FRAX by improving fracture risk prediction.PurposeThis observational, descriptive, and cross-sectional study aimed to assess the fall risk predictors and explore their association with FRAX in Turkish patients with postmenopausal osteoporosis.MethodsTwo hundred and nine (209) women with postmenopausal osteoporosis referred to the Fracture Liaison Service (FLS) at Istanbul University–Cerrahpaşa were enrolled in the FRACT study (The Fracture Study of Turkey). Clinical risk factors were assessed using the FRAX tool. Tandem stance, Tandem walking, Timed up and go (TUG), and Chair stand tests were performed to assess balance and fall risk.ResultsAmong patients with a mean age of 67.6 (± 9.7) years, 66 patients (31.6%) had osteoporosis without fractures and 143 patients (68.4%) had fragility fractures. The proportion of patients with poor performance of fall prediction tests was significantly higher in patients with a fragility fracture than those with osteoporosis alone. There was an inverse relationship between dynamic balance tests and the reported number of prior falls in the past year. FRAX score was higher in patients with impaired Tandem stance, Tandem walking, and TUG tests (p = 0.008, p = 0.035, p = 0.001, respectively).ConclusionAssessment of fall risk predictors should be one of the major pillars in the physical evaluation of osteoporotic patients in the FLS setting. FRAX is a useful tool to determine the fracture risk of patients with both static and dynamic balance impairments. Combining balance assessment with FRAX may be an important step to optimize osteoporosis risk assessment.

Predictive Modeling of Osteoporosis Risk Factors using XGBoost and Bagging Ensemble Technique

This study presents a predictive modeling framework for osteoporosis risk assessment using ensemble techniques, specifically XGBoost and Bagging. Leveraging a dataset comprising comprehensive health factors influencing osteoporosis development, including demographic details, lifestyle choices, medical history, and bone health indicators, the aim is to facilitate accurate identification of individuals at risk. The dataset consists of 1958 samples, evenly distributed between osteoporosis-positive and osteoporosis-negative cases. The methodology involves the separation of features and labels, followed by data splitting into training and testing sets. XGBoost, a powerful gradient boosting algorithm, is employed as the base estimator within a Bagging ensemble, enhancing predictive accuracy and generalization. The model is trained on the training set and evaluated using cross-validation techniques to ensure robustness and mitigate overfitting. The results of the classification report demonstrate promising performance metrics, with an overall accuracy of 88% on the test set. Precision and recall scores indicate strong predictive capabilities, particularly in correctly identifying osteoporosis-positive cases. The novel integration of XGBoost within a Bagging ensemble provides an innovative approach to osteoporosis risk prediction, harnessing the strengths of both algorithms to improve model performance. This research contributes to the advancement of osteoporosis management and prevention strategies by providing a reliable tool for early risk assessment. The combination of machine learning techniques with comprehensive health data offers a valuable approach to personalized healthcare, enabling targeted interventions and optimized resource allocation. Ultimately, this study aims to enhance patient outcomes and reduce the burden of osteoporosis-related morbidity and mortality.

Life's Essential 8 and osteoporosis in adults aged 50years or older: data from the National Health and Nutrition Examination Survey.

The objective of the present study was to evaluate the association between Life's Essential 8 (LE8) and bone mineral density (BMD), as well as osteoporosis risk, in adults aged 50years or over. This cross-sectional study recruited individuals who were 50years old or older from the National Health and Nutrition Examination Survey. LE8 scores were evaluated and calculated according to the scoring algorithm based on the American Heart Association recommendations, which were further categorized into health behaviors (LE8-HB) and health factors (LE8-HF) scores. Furthermore, the present study utilized multivariate linear regression models to examine the correlations between BMD and LE8 scores. In addition, ordinal logistic regression models were employed to determine the associations between the risk of osteoporosis (normal BMD, osteopenia, and osteoporosis) and LE8 scores. The final analysis included a total of 2910 participants, whose mean age was 64.49 ± 9.28years. LE8 and LE8-HF scores exhibited a negative association with BMD and a positive association with osteoporosis risk in unadjusted models. Nevertheless, after adjustment for covariates, LE8 and LE8-HB scores exhibited a positive association with BMD and a negative association with osteoporosis risk, regardless of age, sex, or menopausal status. Scoring systems based on multiple lifestyle and behavior factors, similar to LE8, have the potential to become a novel option and be used for osteoporosis risk assessment.

Development of a diverse osteoporosis screening tool for older US adults from the health and retirement study

Existing osteoporosis screening tools have limitations, including using race as a predictor, and development on homogeneous samples. This biases risk assessment of osteoporosis in diverse populations and increases health inequities. We develop a tool that relies on variables easily learned during point-of-care, known by individuals, and with negligible racial bias. Data from the 2012–2016 waves of the population-based cohort Health and Retirement Study (HRS) were used to build a predictive model of osteoporosis diagnosis on a 75 % training sample of adults ages 50–90. The model was validated on a 25 % holdout sample and a cross-sectional sample of American individuals ages 50–80 from the National Health and Nutrition Examination Survey (NHANES). Sensitivity and specificity were compared across sex and race/ethnicity. The model has high sensitivity in the HRS holdout sample (89.9 %), which holds for those identifying as female and across racial/ethnic groups. Specificity is 57.9 %, and area under the curve (AUC) is approximately 0.81. Validation in the NHANES sample using empirically measured osteoporosis produced relatively good values of sensitivity, specificity, and consistency across groups. The model was used to create a publicly-available, open-source tool called the Osteoporosis Health Equality (& Equity) Evaluation (OsteoHEE). The model provided high sensitivity for osteoporosis diagnosis, with consistently high results for those identifying as female, and across racial/ethnic groups. Use of this tool is expected to improve equity in screening and increase access to bone density scans for those at risk of osteoporosis. Validation on alternative samples is encouraged.

Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes

ObjectiveTo evaluate the risk factors of osteoporosis and establish a risk prediction model based on routine clinical information and traditional Chinese medicine (TCM) syndromes. MethodsAdults aged 30–82 who lived in 12 grass-roots communities or rural towns in Shanghai, Jilin Province, and Jiangsu Province from December 2019 to January 2022 through a multi-stage sampling method were included in this study. The risk factors and risk prediction of osteoporosis in women and men were explored and established by univariate analysis and multivariate logistic regression model. ROC curve and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the prediction model. ResultsA total of 3000 subjects including 2243 females (75 %) and 757 males (25 %) were included in this study. The logistic prediction model of osteoporosis in women was Logit (P) = −2.946 + 0.960 (age ≥50 years old) + 0.633 (BMI ≥24 kg/m2) - 0.545 (daily exposure to sunlight >30 min) + 0.519 (no intake of dairy products) + 0.827 (coronary heart disease) + 0.383 (lumbar disc herniation) + 0.654 (no intake of calcium tablets and vitamin D) - 0.509 (insomnia) + 0.580 (flushed face and congested eyes) + 1.194 (thready and rapid pulse) + 1.309 (sunken and slow pulse). The logistic prediction model of osteoporosis in men was Logit (P) = −1.152–0.644 (daily exposure to sunlight >30 min) + 0.975 (no intake of calcium tablets and vitamin D) - 0.488 (insomnia). The area under the ROC curve (AUC) of female and male osteoporosis prediction models was 0.743 and 0.679, respectively. The Hosmer-Lemeshow goodness-of-fit test was >0.5. ConclusionsThere are some significant differences in risk factors between female and male patients with osteoporosis. The risk of osteoporosis are found to be associated with TCM syndromes, and osteoporosis risk prediction models based on routine clinical information and TCM syndrome is effective.

56 Audit of assessment, prevalence, and treatment of osteoporosis for patients attending the inflammatory bowel disease Service in Mullingar Regional Hospital

Abstract Background Courses of steroids are common in patients with Inflammatory Bowel Disease (IBD) and are a risk factor for developing osteoporosis. Osteoporosis is a clinically silent entity and osteoporosis-related fractures are associated with chronic pain, disability, and impact quality of life. Screening of high-risk populations is the mainstay of fracture prevention. In this audit, we aimed to assess adherence to international guidelines for osteoporosis risk assessment and bone protection. Methods A retrospective audit was performed with a random sampling of 10% of the patients attending between October 2021 to October 2022 the IBD outpatient clinic in Mullingar Regional Hospital. Data included demographics, IBD diagnosis, FRAX tool components, FRAX score, bone health screening, DEXA results, and use of bone mineral protection. Clinical practice was compared against European Crohn’s and Colitis Organisation (ECCO) recommendations on bone protection in IBD. Results Of 150 charts reviewed, 39 charts were missing essential data and 8 had a diagnosis other than IBD. All 103 patients included in the analysis had received &amp;gt;3 months of systemic steroid use, of which 50 had a diagnosis of Crohn’s disease and 63 with ulcerative colitis. Two (2%) patients had a FRAX risk assessment for osteoporosis, and 22 (21%) had a DEXA ordered, of which 7 (7%) were by the IBD clinic. Two (2%) patients had a previous fragility fracture and 3 (3%) had been diagnosed with osteoporosis. Bone protection was used in 21 (20%) patients receiving steroids, including calcium and vitamin D supplementation (n = 19), and bisphosphonate (n = 2). Conclusion There are low rates of osteoporosis screening for IBD patients attending this service. There was inadequate data in the charts to calculate FRAX scores to assess osteoporosis prevalence. An intervention tool is currently being designed and the audit cycle will be completed with a repeat audit after implementation.

Osteoporosis and diabetes - possible links and diagnostic difficulties.

In this review, the authors aimed to clarify the relationship between the occurrence of osteoporosis and diabetes, analyze the differences between the pathogenesis of osteoporosis in different types of diabetes and propose the most effective diagnostic strategy and fracture risk assessment in diabetic patients. A analysis of publications in MEDLINE, COCHRANE and SCOPUS databases was performed, searching for reports on the diagnostics, fracture risk assessment, prevention, and treatment of osteoporosis in patients with diabetes mellitus (DM) published in the years 2016-2022. The key words for the search were: diabetes, osteoporosis, and low-energy fracture. Bone complications of T1DM are more severe than T2DM, because of the lack of anabolic effect of insulin on bones. In T2DM the risk of fractures is elevated; however, identifying the mechanisms underlying the increased risk of fractures in T2DM is not clear. The FRAX tool is not appropriate for assessing the fracture risk in young patients with T1DM. It is quite useful in older patients with T2DM, but in these patients the calculated fracture risk may be underestimated. In T2DM the fracture risk often does not correspond to BMD value as measured by dual-energy X-ray absorptiometry (DXA). Diagnostic tools such as the trabecular bone score may play a significant role in this group of patients. Conclusions: Optimal strategies to identify and treat high risk individuals require further research and proper definition. The diagnostic criteria for osteoporosis should be clearly defined as well as fracture risk assessment and choice of anti-osteoporotic medication. In all cases of secondary osteoporosis, treatment of the underlying disease is the most important. The relationship between high risk of fractures and diabetes is inseparable, and its full understanding seems to be the key to effective management.

Development and validation of osteoporosis risk assessment score in patients with heart failure: comparison with the osteoporosis self-assessment tool for Asians.

Osteoporosis is prevalent and is associated with poor prognosis in patients with heart failure (HF). However, bone mineral density measurement by a dual-energy X-ray absorptiometry (DEXA) scan is not always available in a daily clinical setting or large-scale population-based studies. A single-centre, cross-sectional observational study was conducted with 387 patients [median age: 77 years (interquartile range: 68-83 years); 37% women]. Bone mineral densities were measured by DEXA scans, and osteoporosis was diagnosed as ≤-2.5 standard deviation of the bone mineral densities in healthy young adults. Osteoporosis risk assessment score (ORAS) was developed using significant predictors from a logistic regression model for osteoporosis and was subsequently validated. Osteoporosis was found in 103 (27%) of the 387 HF patients. Multivariate logistic regression analyses yielded the ORAS based on sex, body mass index, handgrip strength, and anti-coagulant therapy utilization. The C-index of ORAS in the developmental set (0.796, 95% confidence interval: 0.747-0.845) was similar to the bootstrap validation of the prediction model (0.784) and tended to be higher than that of the osteoporosis self-assessment tool for Asians (OSTA). A nomogram of ORAS, established on the basis of the final logistic regression model, demonstrated 100% sensitivity at the lowest score (35 points), with an optimal cut-off point of 127 points, yielding 85% sensitivity and 62% specificity. Osteoporosis risk assessment score exhibits superior predictive performance to OSTA in predicting osteoporosis in HF patients, establishing itself as a valuable tool for early detection in both daily clinical practice and large-scale population-based studies.

Race and Ethnicity and Fracture Prediction Among Younger Postmenopausal Women in the Women’s Health Initiative Study

The best approach to identify younger postmenopausal women for osteoporosis screening is uncertain. The Fracture Risk Assessment Tool (FRAX), which includes self-identified racial and ethnic information, and the Osteoporosis Self-assessment Tool (OST), which does not, are risk assessment tools recommended by US Preventive Services Task Force guidelines to identify candidates for bone mineral density (BMD) testing in this age group. To compare the ability of FRAX vs OST to discriminate between younger postmenopausal women who do and do not experience incident fracture during a 10-year follow-up in the 4 racial and ethnic groups specified by FRAX. This cohort study of Women's Health Initiative participants included 67 169 women (baseline age range, 50-64 years) with 10 years of follow-up for major osteoporotic fracture (MOF; including hip, clinical spine, forearm, and shoulder fracture) at 40 US clinical centers. Data were collected from October 1993 to December 2008 and analyzed between May 11, 2022, and February 23, 2023. Incident MOF and BMD (in a subset of 4607 women) were assessed. The area under the receiver operating characteristic curve (AUC) for FRAX (without BMD information) and OST was calculated within each racial and ethnic category. Among the 67 169 participants, mean (SD) age at baseline was 57.8 (4.1) years. A total of 1486 (2.2%) self-identified as Asian, 5927 (8.8%) as Black, 2545 (3.8%) as Hispanic, and 57 211 (85.2%) as White. During follow-up, 5594 women experienced MOF. For discrimination of MOF, AUC values for FRAX were 0.65 (95% CI, 0.58-0.71) for Asian, 0.55 (95% CI, 0.52-0.59) for Black, 0.61 (95% CI, 0.56-0.65) for Hispanic, and 0.59 (95% CI, 0.58-0.59) for White women. The AUC values for OST were 0.62 (95% CI, 0.56-0.69) for Asian, 0.53 (95% CI, 0.50-0.57) for Black, 0.58 (95% CI, 0.54-0.62) for Hispanic, and 0.55 (95% CI, 0.54-0.56) for White women. For discrimination of femoral neck osteoporosis, AUC values were excellent for OST (range, 0.79 [95% CI, 0.65-0.93] to 0.85 [95% CI, 0.74-0.96]), higher for OST than FRAX (range, 0.72 [95% CI, 0.68-0.75] to 0.74 [95% CI, 0.60-0.88]), and similar in each of the 4 racial and ethnic groups. These findings suggest that within each racial and ethnic category, the US FRAX and OST have suboptimal performance in discrimination of MOF in younger postmenopausal women. In contrast, for identifying osteoporosis, OST was excellent. The US version of FRAX should not be routinely used to make screening decisions in younger postmenopausal women. Future investigations should improve existing tools or create new approaches to osteoporosis risk assessment for this age group.

Best Laboratory Screening in Diagnosing Secondary Osteoporosis and Fracture Risk Assessment Tool and the National Osteoporosis Guideline Group Performance in Determining Clinical Risk: A Cross-Sectional Evaluation of the Bone Health in Postmenopausal Brazilian Women.

Identifying postmenopausal women with a high risk of having osteoporosis and fractures is a current challenge. This study aimed to assess the diagnostic performance of biochemical tests in identifying secondary osteoporosis and the fracture risk assessment tool (FRAX) in identifying fracture risk. Data from biochemical tests and bone densitometry of postmenopausal women were analyzed. Additionally, the FRAX result was obtained and the patients were classified according to the National Osteoporosis Guideline Group (NOGG). A total of 646 women were evaluated, of whom 201 (31.1%) had osteoporosis or a previous frailty fracture. These women had statistically different parathyroid hormone (PTH) and alkaline phosphatase serum levels (p&lt;0.01 and p=0.02, respectively) than those without osteoporosis or fracture. However, those at high risk had a higher prevalence of hypovitaminosis D (46% vs. 36%) and hypocalciuria (17% vs. 9%). The FRAX showed an area under the curve of 0.757 (p&lt;0.01) and 0.788 (p&lt;0.01) for identifying women at risk for "major fractures" and "hip," respectively. The NOGG categorization had a sensitivity of 19% to identify high-risk women, a specificity of 91.3% for low-risk women, with a positive predictive value of 57.4% and a negative predictive value of 64.6%. The evaluation of PTH, 25-hydroxy-vitamin D, serum calcium, and 24-hr urinary calcium proved adequate for initial osteoporosis screening. The FRAX tool has a regular ability to screen women at risk for fracture, and the NOGG method has high specificity to identify those at low risk.