Publications by authors named "U Spiegel"
Study Design: A prospective study.
Objective: to evaluate the impact of vertebral body comminution and Posterior Ligamentous Complex (PLC) integrity on the treatment recommendations of thoracolumbar fractures among an expert panel of 22 spine surgeons.
Methods: A review of 183 prospectively collected thoracolumbar burst fracture computed tomography (CT) scans by an expert panel of 22 trauma spine surgeons to assess vertebral body comminution and PLC integrity.
Study Design: Prospective Observational Study.
Objective: To determine the alignment of the AO Spine Thoracolumbar Injury Classification system and treatment algorithm with contemporary surgical decision making.
Methods: 183 cases of thoracolumbar burst fractures were reviewed by 22 AO Spine Knowledge Forum Trauma experts.
Article Synopsis
- This study analyzed data from 183 cases of thoracolumbar burst fractures to understand factors affecting treatment agreement among experts.
- Only 4.4% of cases reached full expert consensus, with 44.3% in the agreement group and 55.7% in the equipoise group, indicating significant uncertainty among the panel.
- The agreement group showed greater certainty regarding PLC disruption and more usage of the M1 modifier, while the equipoise group had a higher proportion of more severe A3/A4 fractures, suggesting a need for further research on how comminution influences treatment decisions.
Study Design: This paper presents a description of a conceptual framework and methodology that is applicable to the manuscripts that comprise this focus issue.
Objectives: Our goal is to present a conceptual framework which is relied upon to better understand the processes through which surgeons make therapeutic decisions around how to treat thoracolumbar burst fractures (TL) fractures.
Methods: We will describe the methodology used in the AO Spine TL A3/4 Study prospective observational study and how the radiographs collected for this study were utilized to study the relationships between various variables that factor into surgeon decision making.
Study Design: Predictive algorithm via decision tree.
Objectives: Artificial intelligence (AI) remain an emerging field and have not previously been used to guide therapeutic decision making in thoracolumbar burst fractures. Building such models may reduce the variability in treatment recommendations.