Background: As a result of DEXA and risk factor-based evaluation, which rank patients according to their osteoporosis risk, risk assessment instruments such as the Osteoporosis Self-assessment Tool, Risk Assessment Instrument, and Simple Calculated Risk Estimation were created. Aims: In two phases, the precision of evaluation instruments will be assessed: pre-test, post-test, and pre-diagnostic DEXA will be utilised to determine the accuracy of the assessment tools and pre-test, respectively. Methods: From September to November 2021, this study examines osteoporosis patients at Prince Rashid bin Al-Hasan Military Hospital in Jordan. Bayes' theorem and osteoporosis screening methodologies are utilised to calculate the post-test probability of patients. Evaluation of AUROC and performance metrics will be conducted utilising a ROC curve. The term of the investigation is 2021-2021. Results: The gender distribution of the 206 patients examined in the study was 5.87:1. AUCs SEMs for the binary logistic regression models incorporating independent variables (OST, ORAI, and BAQ) varied in response to the probability of FRAX≥3% versus <3%. FRAX% exhibited the following sensitivity indices: 0.02, 75%, 41.36%, 66.36%, and 41.03%. The innovative quotient (BAQ), which represents the ratio of body weight to age, had respective pre-test probabilities of 0.789±0.033, 0.484±0.042, and 0.254±0.037. Conclusion: The research examined the probability of BLR_BAQ after the test was conducted using OST and ORAI references. Significant AUROCs were observed for all three osteoporosis instruments; however, the performance of the post-test probabilities for FRAX≥3% of the BLR_BAQ model was subpar, as evidenced by both the standards and ORAI inference.
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Khreisat et al. (2024) studied this question.
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