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1��), but there was no statistical significance (p=0.499). There was also no significant difference in TK and LL between the groups. On the other diglyceride hand, the distance between C7 plumb line and S1 posterosuperior portion revealed significant statistical difference; 66.32 mm in the vertebral fracture group and 22.76 mm in the non-fracture group (p=0.001) (Table 2). Of the 72 patients, 44 patients (18 of the vertebral fracture group versus 26 of the non-fracture group) showed balanced sagittal spine while 28 patients (20 of the vertebral fracture group versus 8 of the non-fracture group) showed imbalanced sagittal spine, there was higher sagittal imbalance of the spine in the vertebral fracture group (p=0.011). Table 2 Comparison of the spinopelvic parameters For evaluation of the fatty infiltration at low lumbar paravertebral muscles, the amount of erector spinae muscle calculated with MRI revealed 2,170 mm2 in the vertebral fracture group and 3,040 mm2 in the non-fracture group, which was statistically significant (p=0.001). The ratio of the muscle, calculated by subtracting fatty infiltration from 100, was 51.05% in the fracture group and 61.72% in the non-fracture group, which was also statistically significant (p=0.001). The amount of flexor muscles, the psoas muscle, and the quadratus Selleck GDC941 lumborum, also revealed significant differences http://www.selleckchem.com/products/AZD0530.html between the two groups; 1,515 mm2 in the vertebral fracture group and 2,110 mm2 in the non-fracture group (p=0.001), however, there was no statistical significance in the ratio of muscle (75.75% and 79.66%, respectively; p=0.216) (Table 3). Table 3 Comparison of the area and fat infiltration ratio of the back muscles Bone mineral density, (mean of lumbar spine T-score 2.94) in the vertebral fracture group was significantly lower than in the non-fracture group (T-score, 0.92). We attributed this result to differences in the ages of the two groups (p=0.001). In statistical analysis of variables, there was linear relationship between spinopelvic parameters and patient's factors (Table 4). Univariate logistic regression analysis for each variable was used to identify fracture risk factors (Table 5), and then multiple logistic regression analysis for the variables of p-value