BACKGROUND: Fractures and dislocations of the subaxial cervical spine may give rise to devastating consequences. Previous algorithms for describing cervical trauma largely depend on retrospective reconstructions of injury mechanism and utilize nonspecific terminology which thus diminish their clinical relevance add to the difficulty of educating doctors and performing prospective research. QUESTIONS/PURPOSES: We characterized the potential benefits of the Subaxial Injury Classification (SLIC) scale which considers three major variables that influence spinal stability: morphology, integrity of the discoligamentous complex, and neurologic status. Each category was assigned a certain number of points based on the severity of the injury which are added together to generate a total score; this value provides prognostic information and may also be useful for directing subsequent management (ie, nonoperative treatment versus operative intervention). METHODS: We examined the individual components that comprise the SLIC paradigm and reviewed the manner in which cervical injuries are scored and stratified. We also critically assessed the preliminary data comparing the SLIC scheme to preexisting classification systems. RESULTS: The results of a preliminary analysis demonstrate that the intraclass coefficients (ICC) for the three primary components range between 0.49 and 0.90, suggesting that the overall reliability of the SLIC system appears to be at least as good as that of other conventional schemes for classifying subaxial cervical spine trauma (ICC between 0.41 and 0.53). CONCLUSIONS: This scheme will hopefully facilitate the development of evidence-based guidelines that may influence other aspects of the therapeutic decision-making process (eg, which operative approach is most appropriate for a particular injury). We anticipate its accuracy and reproducibility will increase over time as surgeons become more familiar with the protocol.
BACKGROUND:Fractures and dislocations of the subaxial cervical spine may give rise to devastating consequences. Previous algorithms for describing cervical trauma largely depend on retrospective reconstructions of injury mechanism and utilize nonspecific terminology which thus diminish their clinical relevance add to the difficulty of educating doctors and performing prospective research. QUESTIONS/PURPOSES: We characterized the potential benefits of the Subaxial Injury Classification (SLIC) scale which considers three major variables that influence spinal stability: morphology, integrity of the discoligamentous complex, and neurologic status. Each category was assigned a certain number of points based on the severity of the injury which are added together to generate a total score; this value provides prognostic information and may also be useful for directing subsequent management (ie, nonoperative treatment versus operative intervention). METHODS: We examined the individual components that comprise the SLIC paradigm and reviewed the manner in which cervical injuries are scored and stratified. We also critically assessed the preliminary data comparing the SLIC scheme to preexisting classification systems. RESULTS: The results of a preliminary analysis demonstrate that the intraclass coefficients (ICC) for the three primary components range between 0.49 and 0.90, suggesting that the overall reliability of the SLIC system appears to be at least as good as that of other conventional schemes for classifying subaxial cervical spine trauma (ICC between 0.41 and 0.53). CONCLUSIONS: This scheme will hopefully facilitate the development of evidence-based guidelines that may influence other aspects of the therapeutic decision-making process (eg, which operative approach is most appropriate for a particular injury). We anticipate its accuracy and reproducibility will increase over time as surgeons become more familiar with the protocol.
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Authors: S Reaungamornrat; T De Silva; A Uneri; J-P Wolinsky; A J Khanna; G Kleinszig; S Vogt; J L Prince; J H Siewerdsen Journal: Proc SPIE Int Soc Opt Eng Date: 2016-03-18
Authors: Sureerat Reaungamornrat; Tharindu De Silva; Ali Uneri; Sebastian Vogt; Gerhard Kleinszig; Akhil J Khanna; Jean-Paul Wolinsky; Jerry L Prince; Jeffrey H Siewerdsen Journal: IEEE Trans Med Imaging Date: 2016-06-02 Impact factor: 10.048
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