Utility of Osteoporosis Self-Assessment Tool as a Screening Tool for Predicting Osteoporosis in Indian Men

Prevalence of osteoporosis and associated factors among people aged 50 years and older in the Madhesh province of Nepal: a community-based cross-sectional study

BACKGROUND

The high prevalence of osteoporosis has increased the economic burden on the health system globally. The burden of osteoporosis and its associated factors have not been adequately assessed in community settings in the Nepalese context thus far. Therefore, this study aimed to assess the prevalence of osteoporosis and its associated factors, lifestyle behaviors, and dietary calcium intake.

METHODS

A community-based cross-sectional study was conducted among 395 people aged 50 years and older in the Madhesh Province of Nepal between July 2022 and August 2023. The Osteoporosis Self-assessment Tools for Asians (OSTA) index was used to measure osteoporosis. A structured questionnaire was used to collect sociodemographic information, anthropometric data, lifestyle behavior, daily dietary calcium intake, and frequency of calcium-rich food consumption. A food frequency questionnaire and 24-hour recall methods were used to assess dietary intake. The chi-square test, binary logistic regression and Mann‒Whitney U test were applied to measure the association between predictors and the outcome of interest.

RESULTS

The prevalence of no risk, moderate risk and high risk of osteoporosis were 38.7%, 39%, and 22.3% respectively. The risk of osteoporosis was higher in females (aOR = 5.18, CI: 2.10-12.75, p < 0.001) and increased risk with advancing age (aOR = 32.49, CI: 14.02-75.28, p < 0.001). Similarly, underweight was associated with increased odds of having osteoporosis (aOR = 13.42, CI = 4.58-39.30, p < 0.001). The incidence of osteoporosis was strongly associated with daily calcium intake of 225 mg (100, 386).

CONCLUSION

This study revealed a high prevalence of osteoporosis among people aged 50 years and older due to the combined effect of being underweight and having inadequate calcium intake. Nutritional counselling services encourage people to consume sufficient calcium-rich food and adopt an appropriate lifestyle behaviours to maintain healthy body weight so that osteoporosis and osteoporotic fractures could be prevented. Further research can explore the impact of socioeconomic status and medical comorbidities on a large scale.

Insights and implications of sexual dimorphism in osteoporosis

Osteoporosis, a metabolic bone disease characterized by low bone mineral density and deterioration of bone microarchitecture, has led to a high risk of fatal osteoporotic fractures worldwide. Accumulating evidence has revealed that sexual dimorphism is a notable feature of osteoporosis, with sex-specific differences in epidemiology and pathogenesis. Specifically, females are more susceptible than males to osteoporosis, while males are more prone to disability or death from the disease. To date, sex chromosome abnormalities and steroid hormones have been proven to contribute greatly to sexual dimorphism in osteoporosis by regulating the functions of bone cells. Understanding the sex-specific differences in osteoporosis and its related complications is essential for improving treatment strategies tailored to women and men. This literature review focuses on the mechanisms underlying sexual dimorphism in osteoporosis, mainly in a population of aging patients, chronic glucocorticoid administration, and diabetes. Moreover, we highlight the implications of sexual dimorphism for developing therapeutics and preventive strategies and screening approaches tailored to women and men. Additionally, the challenges in translating bench research to bedside treatments and future directions to overcome these obstacles will be discussed.

Use of the Osteoporosis Self-Assessment Tool as a Screening Tool for Osteoporosis in Saudi Postmenopausal Women

BACKGROUND

Osteoporosis is commonly referred to as the "silent disease," as bone loss is gradual and asymptomatic. In older women and men, osteoporosis can lead to increased bone fragility, thus increasing the risk of fractures. These fractures are associated with healthcare costs, physical disabilities, impaired quality of life, and mortality. Therefore, the study's main objective was to assess the applicability of the osteoporosis self-assessment tool (OST) in predicting osteoporosis in Saudi postmenopausal women who are 60 years of age and older and to give a thorough understanding of how such a method can aid in the early diagnosis of osteoporosis in Saudi Arabia and give physicians enough time to treat it.  Methods: This study was done at King Abdulaziz Medical City, Riyadh, Saudi Arabia, where we included postmenopausal Saudi women 60 years of age and older who took the bone mineral density (BMD) test in the family medicine department. The approximate target population in this group, between the years 2016 and 2022, was 2969 patients. All data was taken from the BestCare database at King Abdulaziz Medical City in Riyadh. Data were typed in an Excel sheet (Redmond, USA), then transferred to the R Studio software. The data collection method was chart review, so no informed consent was needed from patients. Names and medical record numbers were not stored.  Results: The study included 2969 participants. According to the bone mineral density (BMD) T score results, 490 participants (16.5%) were normal, 1746 participants (58.8%) had osteopenia, and 733 participants (24.7%) suffered from osteoporosis. BMD T scores for normal, osteopenia, and osteoporosis participants were -0.6 (-0.9, -.3), -1.8 (-2.1), and -3 (-3.5, -2.7), consecutively. Estimated OSTI scores for those patients were 2 (0, 4), 1 (-2, 3), and -1 (-4, 1), consecutively. According to the OSTI score for normal participants, 4.29% were classified as being at high risk of osteoporosis. A high risk of osteoporosis was identified in 0.74% of those with osteopenia. 27.83% of osteoporosis patients were classified as being at high risk of osteoporosis. To differentiate normal individuals from those with osteopenia, the cutoff value with optimal sensitivity was 3.5. At such a cutoff value, the test sensitivity was 81.04%. To differentiate normal participants from those with osteoporosis, the cutoff value with optimal sensitivity was 2.5. At such a cutoff value, the test sensitivity was 86.49%. To differentiate osteopenia from osteoporosis patients, the cutoff threshold with optimal sensitivity was 1.5. At such a threshold, sensitivity was 78.44%.  Conclusion: OSTA is a simple and validated tool that can identify subjects at increased risk of osteoporosis. Its use could facilitate a more cost-effective use of BMD; by avoiding measurements in low-risk groups.

Routine chest CT combined with the osteoporosis self-assessment tool for Asians (OSTA): a screening tool for patients with osteoporosis

INTRODUCTION

The osteoporosis self-assessment tool for Asians (OSTA) is a common screening tool for osteoporosis. The seventh thoracic CT (CT-T7) Hounsfield unit (HU) measured by chest CT correlates with osteoporosis. This study aimed to investigate the diagnostic value of OSTA alone, CT-T7 alone, or the combination of OSTA and CT-T7 in osteoporosis.

MATERIALS AND METHODS

In this study, 1268 participants were grouped into 586 men and 682 women. We established multiple linear regression models by combining CT-T7 and OSTA. Receiver operating characteristic (ROC) curves were used to evaluate the ability to diagnose osteoporosis.

RESULTS

In the male group, the mean age was 59.02 years, and 108 patients (18.4%) had osteoporosis. In the female group, the mean age was 63.23 years, and 308 patients (45.2%) had osteoporosis. By ROC curve comparison, the CT-T7 (male, AUC = 0.789, 95% CI 0.745-0.832; female, AUC = 0.835, 95% CI 0.805-0.864) in the diagnosis of osteoporosis was greater than the OSTA (male, AUC = 0.673, 95% CI 0.620-0.726; female, AUC = 0.775, 95% CI 0.741-0.810) in both the male and female groups (p < 0.001). When OSTA was combined with CT, the equation of multiple linear regression (MLR) was obtained as follows: female = 3.020-0.028*OSTA-0.004*CT-T7. In the female group, it was found that the AUC of MLR (AUC = 0.853, 95% CI 0.825-0.880) in the diagnosis of osteoporosis was larger than that of CT-T7 (p < 0.01). When the MLR was 2.65, the sensitivity and specificity were 53.9% and 90%, respectively.

CONCLUSION

For a patient who has completed chest CT, CT-T7 (HU) combined with OSTA is recommended to identify the high-risk population of osteoporosis, and it has a higher diagnostic value than OSTA alone or CT-T7 alone, especially among females. For a female with MLR greater than 2.65, further DXA examination is needed.

Predicting the risk of osteoporosis in older Vietnamese women using machine learning approaches

Osteoporosis contributes significantly to health and economic burdens worldwide. However, the development of osteoporosis-related prediction tools has been limited for lower-middle-income countries, especially Vietnam. This study aims to develop prediction models for the Vietnamese population as well as evaluate the existing tools to forecast the risk of osteoporosis and evaluate the contribution of covariates that previous studies have determined to be risk factors for osteoporosis. The prediction models were developed to predict the risk of osteoporosis using machine learning algorithms. The performance of the included prediction models was evaluated based on two scenarios; in the first one, the original test parameters were directly modeled, and in the second the original test parameters were transformed into binary covariates. The area under the receiver operating characteristic curve, the Brier score, precision, recall and F1-score were calculated to evaluate the models' performance in both scenarios. The contribution of the covariates was estimated using the Permutation Feature Importance estimation. Four models, namely, Logistic Regression, Support Vector Machine, Random Forest and Neural Network, were developed through two scenarios. During the validation phase, these four models performed competitively against the reference models, with the areas under the curve above 0.81. Age, height and weight contributed the most to the risk of osteoporosis, while the correlation of the other covariates with the outcome was minor. Machine learning algorithms have a proven advantage in predicting the risk of osteoporosis among Vietnamese women over 50 years old. Additional research is required to more deeply evaluate the performance of the models on other high-risk populations.

OSTA as a screening tool to predict osteoporosis in Indian postmenopausal women - a nationwide study

This cross-sectional study done on 5356 postmenopausal women showed that OSTA may be used as a reliable screening tool for osteoporosis across different regions of India, a country known for its ethno-linguistic, cultural, and genetic diversity.

BACKGROUND

The gold standard for diagnosing osteoporosis is DXA (dual-energy X-ray absorptiometry) scan, and this is not widely available across India. OSTA (Osteoporosis Self-Assessment Tool for Asians) score predicts risk of osteoporosis and can be used as reference tool for DXA. At a cutoff of ≤  + 1, OSTA predicted femoral neck osteoporosis with a sensitivity of 88% in a previous study among south Indian postmenopausal women. This study was done to validate the OSTA score in postmenopausal women across India.

METHODOLOGY

A cross-sectional study in 5356 postmenopausal women from four regions of India namely south, east, north, and west. Bone mineral density (BMD) and trabecular bone score (TBS) were assessed by DXA. The performance of OSTA in predicting BMD and TBS was assessed using ROC curve.

RESULTS

The mean (SD) age was 61.6 (7.6) years. The performance of OSTA in predicting osteoporosis was fair (P < 0.001) with an AUC of 0.727 (95% CI 0.705-0.749) in the south, 0.693 (95% CI 0.664-0.723) in east India, 0.730 (95% CI 0.700-0.759) in the north, and 0.703 (95% CI 0.672-0.735) in the western region. At a cut-off below + 1.0, sensitivity was 76-84% and specificity was 45-53% in diagnosing osteoporosis at any site. In predicting degraded microarchitecture, the AUC was 0.500-0.600.

CONCLUSION

OSTA may be reliably used as a screening tool for women at high risk of osteoporosis across India and may circumvent the limited availability of DXA scanners across the country.

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.

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.

Using a simple preliminary screening tool to explore related factors of osteoporosis in the elderly of southern Taiwan

The aims of this study were to use a simple screening tool to explore related factors with osteoporosis in the elderly in the community of southern Taiwan.This was an observational cross-sectional study using Osteoporosis Self-Assessment Tool for Asia (OSTA), Osteoporosis Self-Assessment Tool for Taiwanese (OSTAi), and the basic demographic information to identify osteoporosis in the participants. This study collected data from 200 participants aged 65 and above and living in southern Taiwan.The prevalence of osteoporosis among elders in the community was 30.5% (OSTA) and 58.0% (OSTAi), respectively. The prevalence of osteoporosis determined by OSTA and OSTAi in female (33.1% and 63.1%, respectively.) was higher than in male (25.7% and 48.6%, respectively.). Risk factors such as gender, age, and body mass index (BMI) were significantly associated with osteoporosis (P < .001). Using OSTA and OSTAi to assess the risk for osteoporosis, for every 1 year of age increase, the odds ratio (OR) value of osteoporosis increased by 1.84 and 1.50 times, respectively (P < .001); for every 1 kg/m2 increase in BMI, the OR of osteoporosis decreases by 0.36 and 0.44 times, respectively. The results of this study can be used a simple tool of OSTA and OSTAi self-examination to screen potential high-risk groups for osteoporosis in the community.OSTA and OSTAi can screen for possible high-risk groups early and without invasive examinations and self-examination tools in a hospital. Low BMI poses higher risks of osteoporosis for the elderly, so increasing functional ability, improving muscle strength, maintaining exercise habits and keeping proper weight could prevent osteoporosis in the seniors.

The performance of osteoporosis self-assessment tool for Asians (OSTA) in identifying the risk of osteoporosis among Malaysian population aged 40 years and above

The concordance between osteoporosis self-assessment tool for Asians (OSTA) and dual-energy X-ray absorptiometry (DXA) was fair in the study. Modification of OSTA cutoff values improved its sensitivity to identify subjects at risk for suboptimal bone health (osteopenia/osteoporosis) and osteoporosis.

PURPOSE

Osteoporosis self-assessment tool for Asians (OSTA) is a convenient screening algorithm used widely to identify patients at risk of osteoporosis. Currently, the number of studies validating OSTA in Malaysian population is limited. This study aimed to validate the performance of OSTA in identifying subjects with osteoporosis determined with DXA.

METHODS

This cross-sectional study recruited 786 Malaysians in Klang Valley, Malaysia. Their bone health status was assessed by DXA and OSTA. The association and agreement between OSTA and bone mineral density assessment by DXA were determined by Pearson's correlation and Cohen's kappa, respectively. Receiver operating characteristics (ROC) curves were used to determine the sensitivity, specificity, and area under the curve (AUC) for OSTA.

RESULTS

OSTA and DXA showed a fair association in the study (r = 0.382, κ = 0.159, p < 0.001). OSTA (cutoff < - 1) revealed a sensitivity of 32.3%, specificity of 92.3%, and AUC of 0.618 in identifying subjects with suboptimal bone health. The sensitivity of OSTA (cutoff < - 4) in determining subjects at risk of osteoporosis was better among women (sensitivity = 20%) than men (sensitivity = 0%). Modified OSTA cutoff values improved the sensitivity of OSTA in identifying subjects with suboptimal bone health (men = 81.0% at cutoff 3.4, women = 82.8% at cutoff 2.0) and osteoporosis (men = 81.8% at cutoff 1.8, women = 81.3% at cutoff 0.8).

CONCLUSION

OSTA with its original cutoff values is ineffective in identifying individuals at risk for osteoporosis. Adjusting the cutoff values significantly increases the sensitivity of OSTA, thus highlighting the need to validate this instrument among the local population before using it for osteoporosis screening clinically.

Osteoporosis Self-Assessment Tool As a Screening Tool for Predicting Osteoporosis in Elderly Chinese Patients With Established Rheumatoid Arthritis

Osteoporosis Self-Assessment Tool for Asians (OSTA) is an indicator for assessing osteoporosis in postmenopausal women. The aim of this study was to investigate the value of OSTA index on predicting osteoporosis in elderly Chinese patients with established rheumatoid arthritis (RA). A total of 320 patients with RA and 158 normal individuals were recruited from January 2015 to October 2017. Bone mineral density (BMD) at the femur and lumbar spine was measured by dual-energy X-ray absorptiometry. RA group and control group were divided into low risk (values≥-1), medium risk (values between -4 and -1), and high risk (values ≤-4) group according to the value of OSTA index. One-way analysis of variance showed that BMD at all detected regions among the 3 groups were obviously different (p < 0.0001). Incidences of osteoporosis among different OSTA groups were 21.76% (47/216), 56.41% (44/78), and 80.77% (21/26), separately (x² = 67.389, p < 0.0001). In RA group including premenspausal or postmenspausal female subgroup, prevalences of osteoporosis among different OSTA groups were different (p < 0.05-0.0001). We also found a positive linear correlation between OSTA index and BMD (p < 0.0001) both in RA and in control groups. Logistic regression revealed OSTA index (odds ratio = 0.734, p < 0.0001, 95% confidence interval: 0.657-0.819) was a protective factor for occurrence of RA-induced osteoporosis. OSTA had the highest discriminatory power, with an estimated Area Under Curve (AUC) of 0.750 (95% confidence interval 0.694-0.807, p < 0.0001), sensitivity of 76.9% and specificity of 66.5%. Our findings indicated that OSTA index was closely associated with BMD in RA patients, the degree of correlation was much stronger than age or BMI. OSTA index was a predictor for osteoporosis in RA, but it might have little relationship with disease status in RA.

Performance of Osteoporosis Self-Assessment Tool (OST) in Predicting Osteoporosis-A Review

Bone health screening plays a vital role in the early diagnosis and treatment of osteoporosis to prevent fragility fractures among the elderly and high-risk individuals. Dual-energy X-ray absorptiometry (DXA), which detects bone mineral density, is the gold standard in diagnosing osteoporosis but is not suitable for screening. Therefore, many screening tools have been developed to identify individuals at risk for osteoporosis and prioritize them for DXA scanning. The Osteoporosis Self-assessment Tool (OST) is among the first tools established to predict osteoporosis in postmenopausal women. It can identify the population at risk for osteoporosis, but its performance varies according to ethnicity, gender, and age. Thus, these factors should be considered to ensure the optimal use of OST worldwide. Overall, OST is a simple and economical screening tool to predict osteoporosis and it can help to optimize the use of DXA.

Impact of Sexual Dimorphism on Trauma Patterns and Clinical Outcomes of Patients with a High-Risk Score of the Osteoporosis Self-Assessment Tool for Asians: A Propensity Score-Matched Analysis

The Osteoporosis Self-assessment Tool for Asians (OSTA) is a validated index based on age and weight to predict the risk of osteoporosis in women. This cross-sectional study was designed to evaluate the impact of sexual dimorphism on the trauma patterns and the clinical outcomes of patients with high-risk OSTA scores. Trauma data of patients with high-risk OSTA scores between 1 January 2009 and 31 December 2015 were retrieved from the trauma registry system of a level I trauma center. A total of 2248 patients including 1585 women and 663 men were included in this study. In-hospital mortality was assessed as the primary outcome in the propensity score-matched analyses of the female and male patients, which were created in a 1:1 ratio under the adjustment of potential confounders, including age, co-morbidity, mechanism and injury-severity score (ISS). Female patients with a high-risk OSTA score had significantly lower mortality rates than their male counterparts. Among the propensity score-matched population, female patients had lower odds of having cerebral contusion and pneumothorax, but higher odds of presenting with radial, ulnar and femoral fractures than male patients. In addition, the female patients still had significantly lower odds of mortality (odds ratio (OR), 0.5; 95% confidence interval (CI), 0.29-0.90; p = 0.019) than the male patients. However, no significant differences were noted in the length of stay (LOS) in hospital, intensive-care unit (ICU) admission, and LOS in the ICU between the sexes. Female patients with high-risk OSTA scores showed different injury patterns and significantly lower mortality rates than their male counterparts, even after controlling for potential confounding factors.

Evaluation of Different Screening Tools for Predicting Femoral Neck Osteoporosis in Rural South Indian Postmenopausal Women

The measurement of bone mineral density by dual-energy X-ray absorptiometry scan is the "gold standard" for the diagnosis of osteoporosis, which has limited availability in many parts of India. This study was done to assess the diagnostic performance of 6 internationally validated tools (Simple Calculated Osteoporosis Risk Estimation [SCORE], age, bulk, one or never estrogen [ABONE], Osteoporosis Risk Assessment Instrument [ORAI] and Osteoporosis Self-Assessment Tool for Asians [OSTA], Fracture Risk Assessment Tool [FRAX®], and calcaneal quantitative ultrasound [QUS]) for the diagnosis of osteoporosis at the femoral neck (FN). This was a cross-sectional study conducted in 2108 ambulatory South Indian rural postmenopausal women who were assessed with SCORE, ABONE, ORAI, OSTA, and FRAX® tools. QUS was performed in 850 subjects. Bone mineral density was estimated by dual-energy X-ray absorptiometry scan at the FN, and sensitivity and specificity were calculated for all tools for predicting FN osteoporosis. The receiver operating characteristic curve was constructed for each tool and the area under the curve (AUC) was calculated. FN osteoporosis was seen in 27%. The sensitivities of SCORE, ABONE, OSTA, ORAI, FRAX®, and QUS were 91.3%, 91.0%, 88.5%, 81.0%, 72.7%, and 81.9%, and the specificities were 36.0%, 33.5%, 41.7%, 52.0%, 60.5%, and 50.3%, respectively, for the FN osteoporosis. When the receiver operating characteristics were constructed, the AUC was good only for SCORE (0.806), and the performance of the rest was under fair category (0.713-0.766). In our large cohort of rural postmenopausal women, the SCORE screening tool was found to be useful with good sensitivity and good AUC for predicting FN osteoporosis. Thus, this tool may be used in resource-limited countries to screen the population at risk and to enable treating physicians to make appropriate management decisions.

Performance of risk assessment tools for predicting osteoporosis in south Indian rural elderly men

Osteoporosis in elderly men is an under-recognized problem. In the current study, we intend to look at the performance of two risk assessment tools [OSTA and MORES] for the diagnosis of osteoporosis. Osteoporosis was seen in 1/4th of elderly men at spine and 1/6th of them at femoral neck. Both risk assessment tools were found to have good sensitivity in predicting osteoporosis at spine and femoral neck with good area under curve (AUC).

PURPOSE

This study attempts to look at the performance of osteoporosis self-assessment tool for Asians (OSTA) and male osteoporosis risk estimation score (MORES) for predicting osteoporosis in south Indian rural elderly men.

METHODS

Five hundred and twelve men above 65 years of age from a south Indian rural community were recruited by cluster random sampling. All subjects underwent detailed clinical, anthropometric, and bone mineral density measurement at lumbar spine and femoral neck using dual-energy X-ray absorptiometry scan. A T score ≤ - 2.5 was diagnostic of osteoporosis. Scores for OSTA and MORES were calculated at various cut offs, and their sensitivities and specificities for predicting osteoporosis were derived.

RESULTS

The prevalence of osteoporosis was found to be 16% at femoral neck and 23% at spine. OSTA with a cut-off value of ≤2 predicted osteoporosis with a sensitivity and specificity at lumbar spine of 94 and 17% and at femoral neck of 99 and 18%. The area under ROC curve for OSTA index for spine was 0.716 and for femoral neck was 0.778. MORES with a cut-off value of ≥6 predicted osteoporosis at spine with a sensitivity of 98% and specificity of 15%, and at femoral neck, they were 98 and 13%, respectively. The area under ROC curve for MORES for spine was 0.855 and for femoral neck was 0.760.

CONCLUSION

OSTA and MORES were found to be useful screening tools for predicting osteoporosis in Indian elderly men. These tools are simple, easy to perform, and cost effective in the context of rural Indian setting.

Epidemiology of Bone Fracture in Female Trauma Patients Based on Risks of Osteoporosis Assessed using the Osteoporosis Self-Assessment Tool for Asians Score

Background: Osteoporotic fractures are defined as low-impact fractures resulting from low-level trauma. However, the exclusion of high-level trauma fractures may result in underestimation of the contribution of osteoporosis to fractures. In this study, we aimed to investigate the fracture patterns of female trauma patients with various risks of osteoporosis based on the Osteoporosis Self-Assessment Tool for Asians (OSTA) score. Methods: According to the data retrieved from the Trauma Registry System of a Level I trauma center between 1 January 2009 and 31 December 2015, a total of 6707 patients aged ≥40 years and hospitalized for the treatment of traumatic bone fracture were categorized as high-risk (OSTA < -4, n = 1585), medium-risk (-1 ≥ OSTA ≥ -4, n = 1985), and low-risk (OSTA > -1, n = 3137) patients. Two-sided Pearson's, chi-squared, or Fisher's exact tests were used to compare categorical data. Unpaired Student's t-test and Mann-Whitney U-test were used to analyze normally and non-normally distributed continuous data, respectively. Propensity-score matching in a 1:1 ratio was performed with injury mechanisms as adjusted variables to evaluate the effects of OSTA-related grouping on the fracture patterns. Results: High- and medium-risk patients were significantly older, had higher incidences of comorbidity, and were more frequently injured from a fall and bicycle accident than low-risk patients did. Compared to low-risk patients, high- and medium-risk patients had a higher injury severity and mortality. In the propensity-score matched population, the incidence of fractures was only different in the extremity regions between high- and low-risk patients as well as between medium- and low-risk patients. The incidences of femoral fractures were significantly higher in high-risk (odds ratio [OR], 3.4; 95% confidence interval [CI], 2.73-4.24; p < 0.001) and medium-risk patients (OR, 1.4; 95% CI, 1.24-1.54; p < 0.001) than in low-risk patients. In addition, high-risk patients had significantly lower odds of humeral, radial, patellar, and tibial fractures; however, such lower odds were not found in medium- risk than low-risk patients. Conclusions: The fracture patterns of female trauma patients with high- and medium-risk osteoporosis were different from that of low-risk patients exclusively in the extremity region.

Association between the Osteoporosis Self-Assessment Tool for Asians Score and Mortality in Patients with Isolated Moderate and Severe Traumatic Brain Injury: A Propensity Score-Matched Analysis

Background: The purpose of this study was to use a propensity score-matched analysis to investigate the association between the Osteoporosis Self-Assessment Tool for Asians (OSTA) scores and clinical outcomes of patients with isolated moderate and severe traumatic brain injury (TBI). Methods: The study population comprised 7855 patients aged ≥40 years who were hospitalized for treatment of isolated moderate and severe TBI (an Abbreviated Injury Scale (AIS) ≥3 points only in the head and not in other regions of the body) between 1 January 2009 and 31 December 2014. Patients were categorized as high-risk (OSTA score < -4; n = 849), medium-risk (-4 ≤ OSTA score ≤ -1; n = 1647), or low-risk (OSTA score > -1; n = 5359). Two-sided Pearson's chi-squared, or Fisher's exact tests were used to compare categorical data. Unpaired Student's t-test and Mann-Whitney U test were performed to analyze normally and non-normally distributed continuous data, respectively. Propensity score-matching in a 1:1 ratio was performed using NCSS software, with adjustment for covariates. Results: Compared to low-risk patients, high- and medium-risk patients were significantly older and injured more severely. The high- and medium-risk patients had significantly higher mortality rates, longer hospital length of stay, and a higher proportion of admission to the intensive care unit than low-risk patients. Analysis of propensity score-matched patients with adjusted covariates, including gender, co-morbidity, blood alcohol concentration level, Glasgow Coma Scale score, and Injury Severity Score revealed that high- and medium-risk patients still had a 2.4-fold (odds ratio (OR), 2.4; 95% confidence interval (CI), 1.39-4.15; p = 0.001) and 1.8-fold (OR, 1.8; 95% CI, 1.19-2.86; p = 0.005) higher mortality, respectively, than low-risk patients. However, further addition of age as a covariate for the propensity score-matching demonstrated that there was no significant difference between high-risk and low-risk patients or between medium-risk and low-risk patients, implying that older age may contribute to the significantly higher mortality associated with a lower OSTA score. Conclusions: Older age may be able to explain the association of lower OSTA score and higher mortality rates in patients with isolated moderate and severe TBI.

Association of Osteoporosis Self-Assessment Tool for Asians (OSTA) Score with Clinical Presentation and Expenditure in Hospitalized Trauma Patients with Femoral Fractures

Background: A cross-sectional study to investigate the association of Osteoporosis Self-Assessment Tool for Asians (OSTA) score with clinical presentation and expenditure of hospitalized adult trauma patients with femoral fractures. Methods: According to the data retrieved from the Trauma Registry System between 1 January 2009 and 31 December 2015, a total of 2086 patients aged ≥40 years and hospitalized for treatment of traumatic femoral bone fracture were categorized as high-risk patients (OSTA < -4, n = 814), medium-risk patients (-1 ≥ OSTA ≥ -4, n = 634), and low-risk patients (OSTA > -1, n = 638). Two-sided Pearson's, chi-squared, or Fisher's exact tests were used to compare categorical data. Unpaired Student's t-test and Mann-Whitney U-test were used to analyze normally and non-normally distributed continuous data, respectively. Propensity-score matching in a 1:1 ratio was performed using Number Crunching Statistical Software (NCSS) software (NCSS 10; NCSS Statistical Software, Kaysville, UT, USA), with adjusted covariates including mechanism and Glasgow Coma Scale (GCS); injuries were assessed based on the Abbreviated Injury Scale (AIS), and Injury Severity Score (ISS) was used to evaluate the effect of OSTA-related grouping on a patient's outcome. Results: High-risk and medium-risk patients were predominantly female, presented with significantly older age and higher incidences of co-morbidity, and were injured in a fall accident more frequently than low-risk patients. High-risk patients and medium-risk patients had a different pattern of femoral fracture and a significantly lower ISS. Although high-risk and medium-risk patients had significantly shorter lengths hospital of stay (LOS) and less total expenditure than low-risk patients did, similar results were not found in the selected propensity score-matched patients, implying that the difference may be attributed to the associated injury severity of the patients with femoral fracture. However, the charge of surgery is significantly lower in high-risk and medium-risk patients than in low-risk patients, regardless of the total population or the selected propensity score-matched patients. This lower charge of surgery may be attributed to a less aggressive surgery applied for older patients with high or medium risk of osteoporosis. Conclusions: This study of hospitalized trauma patients with femoral fracture according to OSTA risk classification revealed that high-risk and medium-risk patients had significantly higher odds of sustaining injury in a fall accident than low-risk patients; they also present a different pattern of femoral bone fracture as well as a significantly lower ISS, shorter hospital LOS, and less total expenditure. In addition, the significantly lower charge of surgery in high-risk and medium-risk patients than in low-risk patients may be because of the preference of orthopedists for less aggressive surgery in dealing with older patients with osteoporotic femoral bone fracture.