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Spinal injuries account for more than 20 % of total injuries [1]; of these, thoracic and lumbar spine injuries amount to 50–90 % [2, 3]. Over the past decade, the percentage of spinal cord injuries has increased tenfold, with severe injuries prevailing over minor ones, which is naturally explained by growth of industrial-transport parameters [4, 5]. In this regard, there is an obvious need for a spinal injury classification that optimizes the choice of a treatment approach and predicts treatment outcomes. Furthermore, the classification system should be useful for research purposes and be a tool for communication and training. To date, no uniform classification of spinal injuries has been finally developed [6, 7]. The first attempts to classify thoracic and lumbar spine injuries were made by Böhler in 1929. Since then, more than 10 different classifications of spinal injuries have been proposed, which are based on the anatomy (Böhler and Nicoll, 1949), morphology (Watson-Jones, 1938; AO/Magerl, 1994), injury mechanism (Böhler, Ferguson, Allen, 1984), two column stability concept (Holdsworth, 1963; Kell, Whitesides, 1968), three-column approach (Denis, 1983; Gertzbein, 1992; McAfee, 1993), and scoring assessment system (McCormack, Gaines, 1994; TLISS/TLICS, 2005) [7, 8]. Practice has demonstrated that each classification system has its own advantages and disadvantages. For example, the classifications proposed by Böhler, Watson-Jones, Nicoll, Holdsworth, Kelly, and Whitesides were, on the one hand, simple, easy to use, enabled to some extent choosing a therapeutic approach, but, on the other hand, were not validated and prognostic and were mostly descriptive. The advantage of the Denis classification is its simplicity, widespread use, and reflection of some relation between neurological disorders and stability principles. However, it does not enable clear distinguishing between stable and unstable injuries and predicting the outcome of treatment. Furthermore, the Denis classification is characterized by low inter-expert reliability. The Ferguson and Allen classification, being comprehensive, also does not predict the outcome of treatment and is not validated. The McAfee classification has not been widely used and is not validated. The recognized comprehensive AO/Magerl classification that enables determining the severity and stability of injury is, however, considered extremely complex and has moderate inter-expert reliability. The TLISS/TLICS classification can be used to assess stability of injury and predict the outcome of treatment. At the same time, indicators of inter-expert reliability upon application of TLISS/TLICS demonstrate moderate levels [8–10]. The AOSPine classification (TLCS, 2013) was developed by a large team of authors, with allowance for the advantages and disadvantages of previously used classification systems, primarily as a tool to standardize treatment approaches for spinal injuries. It was based on the two most popular recent classifications: AO/Magerl and AO TLISS/TLICS. The main features of the new AOSpine classification (TLCS) include a reduced Objective. To assess inter-expert agreement among spine surgeons having different levels of clinical experience when working with the AOSpine classification (TLCS, 2013). Materials and Methods. The study involved nine surgeons divided into three equal groups depending on work experience. All respondents were asked to classify the MSCT data of 50 patients with acute injuries to the thoracic and lumbar spine pursuant to TLCS (2013) classification. To evaluate inter-expert agreement, a Kappa coefficient interpreted according to Landis – Koch criteria was used. Results. The overall coefficient of inter-expert agreement for all observations among all groups of respondents was 0.43, which reflects a moderate level of agreement. Moderate inter-expert agreement was revealed for injury types A (0.45) and C (0.56), and satisfactory – for type B (0.34). The highest levels of agreement were obtained for subtypes A1 (0.67) and A4 (0.80) in the group of advanced specialists and for type C (0.70) in the group of specialists with a basic level of experience. Conclusion. The study demonstrated predominantly moderate level of inter-expert agreement when working with the AOSpine classification (TLCS, 2013). The accuracy of its use increases with a gain in practical experience of a surgeon.

Analysis of inter-expert agreement when working with the AOSpine classification (TLCS, 2013): our experience, questions and contradictions