However, past analytical models for vertebral trabecular bone do not take account of the effect of strut taper on the mechanical properties.
Robust fracture prediction models for vertebral fracture risk should not only include BMD, as measured by DXA, but should incorporate a wide range of factors including bone geometry, bone mineral distribution within the vertebral body, daily living activities, and spine musculature.
Logistic regression models for vertebral deformities were constructed using WOD and AHD results using various combinations of age and body weight as independent variables.
This model appears to hold for vertebral, cardiac and renal malformations, but not in the GI tract, where malformations seen in FOXF1 mutation cases are different from those seen in whole cluster deletion patients.
However, these analyses also suggest that the small discrepancy between animal model (h2 = 0.36) and standard generalized mixed model (h2 = 0.29) estimates of heritability for vertebral number could be due to unaccounted maternal effects (m = 0.06) in the animal model estimate.
Large animal models are highly recommended for meaningful preclinical studies, including the optimization of cement augmentation for vertebral body defects by vertebroplasty/kyphoplasty.
The slightly lower estimate for vertebral number in this alternative approach could be due to the fact that animal model estimates did not account for maternal (and common environment; see Methods) effects.
Evidence continues to emerge to substantiate the potential advantages of lateral-projection methods, such as enhanced diagnostic sensitivity for vertebral fracture [ 34] and superior predictive capacity for vertebral failure in ex situ models [ 35].
Reduced vertebral strength is a clear risk factor for vertebral fractures.
These exams showed alterations suspected for vertebral dissection, and a diagnostic angiography confirmed bilateral dissection of vertebral arteries.
