Biomedical Journal (Dec 2022)
Utilizing nomograms to predict prevalent vertebral fracture risk: An analysis of dysmobility syndrome in a community-dwelling population
Abstract
Background: To determine a reliable method to predict prevalent vertebral fractures (VF) by assessing the association between dysmobility syndrome (DS) and VF in a community-dwelling population. Methods: This cross-sectional study enrolled 518 participants from fracture-prevention educational activities held in multiple communities in Taiwan. Assessments included questionnaires, fracture risk assessment tool (FRAX), bone mineral density (BMD) and body composition using dual-energy x-ray absorptiometry (DXA), lateral thoracolumbar spine x-rays (specifically T8-S1), grip strength (GS), walking speed, and fall history. Results: DS was noted in 257 participants (49.6%) and VF was identified in 196 participants (37.8%). A higher prevalence of VF was noted in those with DS. The prevalence of VF was significantly associated with age, gender, FRAX both with and without BMD, osteoporosis, low GS, and DS. In multivariate models accounting for age and sex, the c-index was greater in those with low GS plus osteoporosis as compared to DS alone. Low GS, osteoporosis, and pre-BMD FRAX all had similar c-indexes. Pre-BMD FRAX plus low GS and osteoporosis was superior in predicting VF compared to pre-BMD FRAX plus low GS or osteoporosis alone. Besides the inclusion of age and gender, the nomogram with pre-BMD FRAX major osteoporosis fracture probability (MOF) plus low GS had improved correlation between the estimated and actual VF probability than those with pre-BMD FRAX MOF plus osteoporosis. Conclusions: The constructed nomogram containing pre-BMD FRAX MOF plus low GS may be considered as a first-line prevalent VF screening method. Those with high-risk scores should subsequently undergo vertebral radiography and/or BMD.