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Indexed/Abstracted in: e-psyche, EMBASE, PubMed/MEDLINE, Neuroscience Citation Index, Science Citation Index Expanded (SciSearch), Scopus
Impact Factor 1,651
Online ISSN 1827-1855
John K. YUE 1, Andrew K. CHAN 1, Ethan A. WINKLER 1, Pavan S. UPADHYAYULA 1, William J. READDY 2, Sanjay S. DHALL 1
1 Department of Neurological Surgery, University of California, San Francisco, California, USA; 2 Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
Acute traumatic spinal cord injury (SCI) is a debilitating worldwide disease with an estimated annual incidence of 10 to 83 affected individuals per million inhabitants. These injuries typically impact younger individuals and reduce quality-adjusted life years with estimated lifetime costs exceeding $4 million per person. Hence it is critical to establish and refine clear practice guidelines for acute management of SCI. In 2013 the Joint Section on Disorders of the Spine and Peripheral Nerves of the American Association of Neurological Surgeons (AANS) and the Congress of Neurological Surgeons (CNS) released a revision of the 2002 guidelines for Cervical SCI. In the present report we explore seven subsections for management of specific cervical injury types, review key supporting literature, and provide an update on recent studies since the publication of the 2013 guidelines. Our review finds a paucity of Level I and Level II treatment recommendations for cervical spine injuries, with the exception of subaxial cervical spine injury classification and surgical management for Type II odontoid fractures in the elderly. We recommend the systematic implementation of large randomized controlled studies across diverse demographics and ethnicities, injury mechanisms and morphologies to address pressing limitations in the current literature. The cohesive effort to adopt the 2013 AANS/CNS Guidelines and the National Institutes of Health (NIH)/National Institute of Neurological Disorders and Stroke (NINDS) Common Data Elements for SCI as part of a multicenter international approach will enable reproducible data collection and robust analyses toward achieving this goal.