Global tilt angle in spinal alignment of asymptomatic older women with low bone mass

This study investigated the relationship between sagittal spinal alignment and musculoskeletal health in older women, particularly those exhibiting diminished bone density without apparent symptoms. The study assessed the impact of global tilt (GT) and the presence of coronal malalignment on spinal...

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Published inScientific reports Vol. 14; no. 1; pp. 24840 - 9
Main Authors Tsai, Ping-Chiao, Lee, Ssu-Hsien, Chiu, Yu-Chieh, Wu, Wen-Tien, Lee, Ru-Ping, Yu, Tzai-Chiu, Chen, Ing-Ho, Wang, Jen-Hung, Yeh, Kuang-Ting
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 22.10.2024
Nature Publishing Group
Nature Portfolio
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Summary:This study investigated the relationship between sagittal spinal alignment and musculoskeletal health in older women, particularly those exhibiting diminished bone density without apparent symptoms. The study assessed the impact of global tilt (GT) and the presence of coronal malalignment on spinal health. The research involved 165 asymptomatic older women with an average age of 68.91 ± 7.25 years and average body mass index of 24.26 ± 3.66 kg/m². Comprehensive standing anteroposterior and lateral spine radiographs were used for assessment. Through multivariate linear regression analysis, the study identified significant correlations between increased GT angles and various factors, including coronal malalignment, the C7 slope, and pelvic incidence. This led to the formulation of a predictive GT model: GT = −9.79 + 0.06 × menopausal period + 0.19 × body mass index (BMI)− 0.81 × average T score – 0.11 × grip strength + 3.03 × (presence of coronal malalignment) + 0.08 × sagittal vertical axis (SVA) + 0.12 × C7 slope − 0.35 × upper lumbar lordosis (ULL) − 0.43 × lower lumbar lordosis (LLL) + 0.70 × pelvic incidence (PI), with an adjusted R² of 0.816. The study findings highlight the prevalence of coronal malalignment in this demographic and its significant associations with critical spinal parameters. The proposed GT predictive model may enable development of personalized treatment plans for older women with low bone mass.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-76876-y