scholarly journals Optimal Analysis to Discriminate Males’ Osteoporosis With Simple Physiological Indicators

2016 ◽  
Vol 10 (6) ◽  
pp. 487-494 ◽  
Author(s):  
Shu-Fang Chang ◽  
Rong-Sen Yang
Keyword(s):  
Body Weight ◽  
Hip Fracture ◽  
Large Scale ◽  
Assessment Tool ◽  
Characteristic Curve ◽  
Cutoff Point ◽  
Health Staff ◽  
Mineral Density ◽  
Self Assessment ◽  
Predictive Values

Males account for one third of global hip fracture patients, and their hip fracture-related mortality rate is higher than that of females. Scholars have primarily investigated self-evaluation indicators for elderly Caucasians and other ethnicities, and have rarely conducted large-scale cutoff point studies on Asian males. In this study, a large-scale database on bone mineral density (BMD) examinations was used to conduct a cutoff point study on males with osteoporosis. This study involved a retrospective research design. Males who accepted BMD examinations from 2009 to 2012 at a large teaching hospital in Taiwan were sampled in this study. This study used the database for analyzing effects with using osteoporosis self-assessment indicator, age, body weight, and body mass index (BMI) to discriminate osteoporosis in males, specifically focusing on accuracy, cutoff point, sensitivity, specificity, and positive and negative predictive values. Overall, receiver operating characteristic curve for the samples reached 70%. These cutoff points included: a body weight is less than 58.8 kg, BMI is 23 kg/m2, and the osteoporosis self-assessment score is −1.86, to identify osteoporosis. Involving body weight and BMI as optimal assessing indicators for assessing osteoporosis among males younger than 65 years, and the osteoporosis self-assessment tool was ideal for measuring males older than 65 years. Professional health staff should apply convenient, low-cost, and accurate evaluation tools that can assist Asian males in planning preventive osteoporosis strategies to avoid osteoporotic fractures and death.

scholarly journals Simple Self-Assessment Tool to Predict Osteoporosis in Taiwanese Men

2021 ◽  
Vol 8 ◽  
Author(s):  
Dung-Huan Liu ◽  
Chung-Yuan Hsu ◽  
Pei-Ching Wu ◽  
Ying-Chou Chen ◽  
You-Yin Chen ◽  
...  
Keyword(s):  
Assessment Tool ◽  
Risk Index ◽  
Area Under The Curve ◽  
Assessment Tools ◽  
Mineral Density ◽  
Self Assessment ◽  
Fracture Risk Assessment Tool ◽  
Patients At Risk ◽  
Taiwanese Men ◽  
Country Specific

Background: Although the self-assessment tools for predicting osteoporosis are convenient for clinicians, they are not commonly used among men. We developed the Male Osteoporosis Self-Assessment Tool for Taiwan (MOSTAi) to identify the patients at risk of osteoporosis.Methods: All the participants completed a questionnaire on the clinical risk factors for the fracture risk assessment tool. The risk index was calculated by the multivariate regression model through the item reduction method. The receiver operating characteristic (ROC) curve was used to analyze its sensitivity and specificity, and MOSTAi was developed and validated.Results: A total of 2,290 men participated in the bone mineral density (BMD) survey. We chose a model that considered two variables (age and weight). The area under the curve (AUC) of the model was 0.700. The formula for the MOSTAi index is as follows: 0.3 × (weight in kilograms) – 0.1 × (years). We chose 11 as the appropriate cut-off value for the MOSTAi index to identify the subjects at the risk of osteoporosis.Conclusions: The MOSTAi is a simple, intuitive, and country-specific tool that can predict the risk of osteoporosis in Taiwanese men. Due to different demographic characteristics, each region of the world can develop its own model to identify patients with osteoporosis more effectively.

scholarly journals Comparison of osteoporotic fracture risk in surgical and natural menopausal patients

2021 ◽  
Vol 67 (3) ◽  
pp. 322-327
Author(s):  
Ayça Utkan Karasu ◽  
Yetkin Karasu ◽  
Müzeyyen Gülnur Özakşit ◽  
Yusuf Üstün ◽  
Yaprak Üstün Engin
Keyword(s):  
Hip Fracture ◽  
Femoral Neck ◽  
Fracture Risk ◽  
Osteoporotic Fracture ◽  
Assessment Tool ◽  
Lumbar Vertebrae ◽  
Mineral Density ◽  
Natural Menopause ◽  
T Score ◽  
Surgical Menopause

Objectives: This study aims to compare the fracture risk calculated with Fracture Risk Assessment Tool (FRAX®) in patients with natural and surgical menopause. Patients and methods: Between April 2019 and July 2019, 285 postmenopausal patients (mean age 57.3 years; range, 40 to 78 years) who were admitted to the menopause clinic were enrolled in this prospective cross-sectional study. Of these, 220 were in natural menopause and 65 were in surgical menopause. Demographic data, medical history, and International Physical Activity Questionnaire scores were collected through face-to-face interviews with the patients. Femoral neck and lumbar vertebrae (L1-L4) T-scores were evaluated using dual-energy X-ray absorptiometry. Fragility fracture risk was assessed using FRAX®. Results: The groups were similar in terms of age, body mass index, duration of menopause, smoking, alcohol use, and history of fracture (p>0.05). The risk of major osteoporotic fracture and hip fracture calculated without adding bone mineral density (BMD) was similar between groups (p=0.417 and p=0.234). The risk of hip fracture calculated with the addition of BMD was higher in natural menopause patients (p=0.023). Lumbar vertebrae T-scores were similar between two groups regardless of age; femoral neck T-scores were higher in surgical menopause (T-score=-0.8) than natural menopause group (T-score=-1.25) aged under 60 years, whereas this difference disappeared after 60 years of age. Conclusion: In our study, the fracture risk and the severity of osteoporosis were not different in surgical menopausal patients compared to the natural menopausal patients. Hip fracture risk calculated using BMD was lower in patients under 50 years of age in surgical menopausal patients. However, the fracture risks were similar in both groups after 50 years of age.

scholarly journals Diagnostic performance and clinical implications of rapid SARS-CoV-2 antigen testing in Mexico using real-world nationwide COVID-19 registry data

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256447
Author(s):  
Omar Yaxmehen Bello-Chavolla ◽  
Neftali Eduardo Antonio-Villa ◽  
Luisa Fernández-Chirino ◽  
Enrique C. Guerra ◽  
Carlos A. Fermín-Martínez ◽  
...  
Keyword(s):  
Symptom Onset ◽  
Diagnostic Performance ◽  
Large Scale ◽  
Characteristic Curve ◽  
False Negative ◽  
High Specificity ◽  
Adverse Outcomes ◽  
Clinical Implications ◽  
Predictive Values ◽  
Qrt Pcr

Background SARS-CoV-2 testing capacity is important to monitor epidemic dynamics and as a mitigation strategy. Given difficulties of large-scale quantitative reverse transcription polymerase chain reaction (qRT-PCR) implementation, rapid antigen tests (Rapid Ag-T) have been proposed as alternatives in settings like Mexico. Here, we evaluated diagnostic performance of Rapid Ag-T for SARS-CoV-2 infection and its associated clinical implications compared to qRT-PCR testing in Mexico. Methods We analyzed data from the COVID-19 registry of the Mexican General Directorate of Epidemiology up to April 30th, 2021 (n = 6,632,938) and cases with both qRT-PCR and Rapid Ag-T (n = 216,388). We evaluated diagnostic performance using accuracy measures and assessed time-dependent changes in the Area Under the Receiver Operating Characteristic curve (AUROC). We also explored test discordances as predictors of hospitalization, intubation, severe COVID-19 and mortality. Results Rapid Ag-T is primarily used in Mexico City. Rapid Ag-T have low sensitivity 37.6% (95%CI 36.6–38.7), high specificity 95.5% (95%CI 95.1–95.8) and acceptable positive 86.1% (95%CI 85.0–86.6) and negative predictive values 67.2% (95%CI 66.2–69.2). Rapid Ag-T has optimal diagnostic performance up to days 3 after symptom onset, and its performance is modified by testing location, comorbidity, and age. qRT-PCR (-) / Rapid Ag-T (+) cases had higher risk of adverse COVID-19 outcomes (HR 1.54 95% CI 1.41–1.68) and were older, qRT-PCR (+)/ Rapid Ag-T(-) cases had slightly higher risk or adverse outcomes and ≥7 days from symptom onset (HR 1.53 95% CI 1.48–1.59). Cases detected with rapid Ag-T were younger, without comorbidities, and milder COVID-19 course. Conclusions Rapid Ag-T could be used as an alternative to qRT-PCR for large scale SARS-CoV-2 testing in Mexico. Interpretation of Rapid Ag-T results should be done with caution to minimize the risk associated with false negative results.

Body Mass Index can be a Good Predictor of Bone Mineral Density in Postmenopausal Women in India

2014 ◽  
Vol 3 (4) ◽  
pp. 276
Author(s):  
Biplob Chowdhury ◽  
Brajanath Kundu
Keyword(s):  
Bone Mineral Density ◽  
Body Mass Index ◽  
Body Weight ◽  
Postmenopausal Women ◽  
Body Mass ◽  
Bone Mineral ◽  
Assessment Tool ◽  
Negative Impact ◽  
Mineral Density ◽  
Women In India

Risk factors for the prediction of osteoporosis are an important and cost effective method since osteoporosis is a silent disease. The purpose of the study was to evaluate the associations between weight, body mass index (BMI), the Osteoporosis Self-Assessment Tool (OST), and bone mineral density (BMD) in postmenopausal women in India. In this cross sectional study, 90 postmenopausal women aged 45–85 years who had given consent participated and the study was conducted between April, 2012 and May, 2013. BMD was measured by ultrasound bone densitometry at calcaneal site. Linear regression multivariate models were used to examine the associations with weight, BMI, OST, and BMD. Body weight, BMI, and OST had almost similar overall performance in their ability to classify women with BMD T-score ≤−2.5. Regression results showed that the linear combination of three independent variables BMI, OST and body weight. BMI predicted 65.7% of the variance in BMD, <em>R</em><sup>2</sup> = .657, <em>R</em><em><sup>2</sup></em><sup> </sup>adjusted = .609, (F=21.295, p&lt;.000). The strongest predictor of low BMD was BMI. BMI showed significant association with BMD with a correlation of .846. Low weight and BMI predict osteoporosis and are associated with increased risks in postmenopausal women. The negative impact of low body weight on bone health should be more widely recognized.

scholarly journals Body Mass Index can be a Good Predictor of Bone Mineral Density in Postmenopausal Women in India

2014 ◽  
Vol 3 (4) ◽  
pp. 276
Author(s):  
Biplob Chowdhury ◽  
Brajanath Kundu
Keyword(s):  
Bone Mineral Density ◽  
Body Mass Index ◽  
Body Weight ◽  
Postmenopausal Women ◽  
Body Mass ◽  
Bone Mineral ◽  
Assessment Tool ◽  
Negative Impact ◽  
Mineral Density ◽  
Women In India

Risk factors for the prediction of osteoporosis are an important and cost effective method since osteoporosis is a silent disease. The purpose of the study was to evaluate the associations between weight, body mass index (BMI), the Osteoporosis Self-Assessment Tool (OST), and bone mineral density (BMD) in postmenopausal women in India. In this cross sectional study, 90 postmenopausal women aged 45–85 years who had given consent participated and the study was conducted between April, 2012 and May, 2013. BMD was measured by ultrasound bone densitometry at calcaneal site. Linear regression multivariate models were used to examine the associations with weight, BMI, OST, and BMD. Body weight, BMI, and OST had almost similar overall performance in their ability to classify women with BMD T-score ≤−2.5. Regression results showed that the linear combination of three independent variables BMI, OST and body weight. BMI predicted 65.7% of the variance in BMD, <em>R</em><sup>2</sup> = .657, <em>R</em><em><sup>2</sup></em><sup> </sup>adjusted = .609, (F=21.295, p&lt;.000). The strongest predictor of low BMD was BMI. BMI showed significant association with BMD with a correlation of .846. Low weight and BMI predict osteoporosis and are associated with increased risks in postmenopausal women. The negative impact of low body weight on bone health should be more widely recognized.

scholarly journals Osteoporosis Self-Assessment Tool Performance in a Large Sample of Postmenopausal Women of Mendoza, Argentina

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Fernando D. Saraví
Keyword(s):  
Postmenopausal Women ◽  
Predictive Value ◽  
White Women ◽  
Assessment Tool ◽  
Density Measurement ◽  
Area Under The Curve ◽  
Mineral Density ◽  
Self Assessment ◽  
Tool Performance ◽  
Patients At Risk

The Osteoporosis Self-assessment Tool (OST) is a clinical instrument designed to select patients at risk of osteoporosis, who would benefit from a bone mineral density measurement. The OST only takes into account the age and weight of the subject. It was developed for Asian women and later validated for European and North American white women. The performance of the OST in a sample of 4343 women from Greater Mendoza, a large metropolitan area of Argentina, was assessed. Dual X-ray absorptiometry (DXA) scans of lumbar spine and hip were obtained. Patients were classified as either osteoporotic (N=1830) or nonosteoporotic (n=2513) according to their lowest T-score at any site. Osteoporotic patients had lower OST scores (P<0.0001). A receiver operating characteristic (ROC) curve showed an area under the curve of 71% (P<0.0001), with a sensitivity of 83.7% and a specificity of 44% for a cut-off value of 2. Positive predictive value was 52% and negative predictive value was 79%. The odds ratio for the diagnosis of osteoporosis was 4.06 (CI95 3.51 to 4.71;P<0.0001). It is concluded that the OST is useful for selecting postmenopausal women for DXA testing in the studied population.

scholarly journals A simplified questionnaire for self-assessment of hirsutism in population-based studies

2015 ◽  
Vol 172 (4) ◽  
pp. 451-459 ◽  
Author(s):  
Ligia Gabrielli ◽  
Estela M L Aquino
Keyword(s):  
Large Scale ◽  
Characteristic Curve ◽  
Population Based ◽  
Adult Health ◽  
Self Assessment ◽  
Body Hair ◽  
Retest Reliability ◽  
Test Retest Reliability ◽  
Independent Medical Examination ◽  
Self Administered Questionnaire

ObjectiveThe measurement of excess body hair is not straightforward. As the modified Ferriman–Gallwey (mFG) score is unsuitable for self-assessment and requires specialist training, a short, self-administered questionnaire to identify hirsutism was constructed and validated for large-scale application, particularly targeting population-based studies.DesignA validation study was conducted to assess a new hirsutism questionnaire.MethodsA total of 90 women aged 35–72 years who were enrolled in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) were evaluated. A self-administered instrument containing four questions was designed to evaluate five body areas: upper lip, chin, chest, lower abdomen, and thighs with respect to the current distribution of body hair and that before 35 years of age. A score of 0–4 was attributed to each region based on drawings provided in the instrument. Test–retest reliability was evaluated by reformulating the initial questions. An independent medical examination was conducted to apply the gold standard, the mFG score.ResultsThe area under the receiver operating characteristic curve was 0.93 (95% CI: 0.87–0.99). A cut-off score of 5 showed the best balance between sensitivity (85%) and specificity (90%), with 88.9% accuracy. Spearman's correlation between current and past body hair score was calculated at 0.82 (P=0.000), and showed a test–retest reliability of 0.49, with a trend toward similar answers regarding changes in the quantity of body hair over time, irrespective of how the questions were asked (P=0.000).ConclusionThe accuracy and internal consistency of this self-administered questionnaire for the identification of hirsutism were good. Therefore, this questionnaire represents a useful tool for self-assessment of hirsutism in population-based studies.

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