Bone Mineral Density and Trabecular Bone Score in Predicting Vertebral Fractures in Male Employees of the Electricity Generating Authority of Thailand
Issued Date
2022-01-01
Resource Type
ISSN
20908059
eISSN
20420064
Scopus ID
2-s2.0-85128420081
Journal Title
Journal of Osteoporosis
Volume
2022
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Osteoporosis Vol.2022 (2022)
Suggested Citation
Sakulpisuti C., Sritara C., Kositwattanarerk A., Fuangfa P., Suppasilp C., Vathesatogkit P., Matchariyakul D., Ongphiphadhanakul B., Sritara P. Bone Mineral Density and Trabecular Bone Score in Predicting Vertebral Fractures in Male Employees of the Electricity Generating Authority of Thailand. Journal of Osteoporosis Vol.2022 (2022). doi:10.1155/2022/6832166 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/86604
Title
Bone Mineral Density and Trabecular Bone Score in Predicting Vertebral Fractures in Male Employees of the Electricity Generating Authority of Thailand
Author's Affiliation
Other Contributor(s)
Abstract
Purpose. Osteoporotic VF is frequently asymptomatic and affects not only women but also men. Identifying patients at risk is essential for early management and prevention. BMD and the TBS are measurements of bone strength and trabecular microarchitecture, respectively. Their role in VF prediction in men is less well-studied. We determined the BMD and TBS predictive ability for osteoporotic VF in men. Methods. A total of 115 male participants of the Electricity Generating Authority of Thailand (EGAT) cohorts without a history of VF who completed the baseline BMD and TBS measurements in 2012 and a thoracolumbar spine radiograph in 2017 were recruited. The VF was assessed using the Genant semiquantitative method. Logistic regression analysis was performed to identify factors associated with the fracture. The area under the receiving operator curve (AUC) was analyzed to define VF predictive ability. Results. Forty subjects (34.78%) had VFs. The unadjusted relative risks (95% confidence interval) for VF for one standard deviation decrease in the TBS and low TBS were 1.319 (1.157-1.506) and 2.347 (1.496-3.682), respectively, and remained significant after BMD and age adjustment. For VF prediction, combined models had a greater AUC than models predicted from a single variable. The use of low TBS, femoral neck BMD, and age provided the best AUC (0.693). Conclusion. BMD and the TBS could predict osteoporotic VF in male EGAT employees. The use of both BMD and the TBS in the VF prediction process improved predictive ability.