Global spine journal · 2022
Development of Online Technique for International Validation of the AO Spine Subaxial Injury Classification System.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Ошибки и ограничения
История · было → стало
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Lambrechts Mark J, Schroeder Gregory D, Karamian Brian A, Canseco Jose A, Oner Cumhur, Vialle Emiliano, Rajasekaran Shanmuganathan, Hazenbiller Olesja, Dvorak Marcel R, Benneker Lorin M, Kandziora Frank, Schnake Klaus, Kepler Christopher K, Vaccaro Alexander R, AO Spine Subaxial Classification Group Members
Аннотация
STUDY DESIGN: Global cross-sectional survey.
OBJECTIVE: To develop and refine the techniques for web-based international validation of fracture classification systems.
METHODS: A live webinar was organized in 2018 for validation of the AO Spine Subaxial Injury Classification System, consisting of 35 unique computed tomography (CT) scans and key images with subaxial spine injuries. Interobserver reliability and intraobserver reproducibility was calculated for injury morphology, subtype, and facet injury according to the classification system. Based on the experiences from this webinar and incorporating rater feedback, adjustments were made in the organization and techniques used and in 2020 a repeat validation webinar was performed, evaluating images of 41 unique subaxial spine injuries.
RESULTS: In the 2018 session, the AO Spine Subaxial Injury Classification System demonstrated fair interobserver reliability for fracture subtype (κ = 0.35) and moderate reliability for fracture morphology and facet injury (κ=0.45, 0.43, respectively). However, in 2020, the interobserver reliability for fracture morphology (κ = 0.87) and fracture subtype (κ = 0.80) was excellent, while facet injury was substantial (κ = 0.74). Intraobserver reproducibility for injury morphology (κ =0.49) and injury subtype/facet injury were moderate (κ = 0.42) in 2018. In 2020, fracture morphology and subtype reproducibility were excellent (κ =0.85, 0.88, respectively) while reproducibility for facet injuries was substantial (κ = 0.76).
CONCLUSION: With optimized webinar-based validation techniques, the AO Spine Subaxial Injury Classification System demonstrated vast improvements in intraobserver reproducibility and interobserver reliability. Stringent fracture classification methodology is integral in obtaining accurate classification results.
OBJECTIVE: To develop and refine the techniques for web-based international validation of fracture classification systems.
METHODS: A live webinar was organized in 2018 for validation of the AO Spine Subaxial Injury Classification System, consisting of 35 unique computed tomography (CT) scans and key images with subaxial spine injuries. Interobserver reliability and intraobserver reproducibility was calculated for injury morphology, subtype, and facet injury according to the classification system. Based on the experiences from this webinar and incorporating rater feedback, adjustments were made in the organization and techniques used and in 2020 a repeat validation webinar was performed, evaluating images of 41 unique subaxial spine injuries.
RESULTS: In the 2018 session, the AO Spine Subaxial Injury Classification System demonstrated fair interobserver reliability for fracture subtype (κ = 0.35) and moderate reliability for fracture morphology and facet injury (κ=0.45, 0.43, respectively). However, in 2020, the interobserver reliability for fracture morphology (κ = 0.87) and fracture subtype (κ = 0.80) was excellent, while facet injury was substantial (κ = 0.74). Intraobserver reproducibility for injury morphology (κ =0.49) and injury subtype/facet injury were moderate (κ = 0.42) in 2018. In 2020, fracture morphology and subtype reproducibility were excellent (κ =0.85, 0.88, respectively) while reproducibility for facet injuries was substantial (κ = 0.76).
CONCLUSION: With optimized webinar-based validation techniques, the AO Spine Subaxial Injury Classification System demonstrated vast improvements in intraobserver reproducibility and interobserver reliability. Stringent fracture classification methodology is integral in obtaining accurate classification results.