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External Multicenter Study of Reliability and Reproducibility for Lower Cervical Spine Injuries Classification Systems-Part 1: A Comparison of Morphological Schemes.

Andrey GrinVladimir KrylovIvan LvovAleksandr TalypovDmitriy DzukaevAnton KordonskiyVladimir SmirnovVasily KaranadzeBoburmirzo AbdukhalikovUlugbek KhushnazarovIrina AleynikovaElza KazakovaOlesya BogdanovaAlexander PeykerVitaliy SemchenkoAndrey AksenovAnton BorzenkovVladimir GulyySoslan TorchinovSergey BagaevAnton ToporskiyAndrey NikitinSevak ArakelyanAvetik MartikyanStanislav OshchepkovDmitriy HovrinAslan KojevMusheg Khalatyan
Published in: Global spine journal (2019)
We found the highest values of interobserver agreement and reproducibility among surgeons with different levels of experience with Argenson and AOSpine classifications. The AOSpine scale additionally incorporated more detailed description of compression injuries and facet-joint fractures. Agreement levels reached for Allen-Fergusson and Harris scales were fair and moderate, respectively, indicating difficulty of their application in clinical practice, especially by junior specialists.
Keyphrases
  • clinical practice
  • machine learning
  • deep learning
  • quality improvement
  • thoracic surgery