Abstract
Through a partnership with the National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, and Department of Defense, the development of Sport-Related Concussion (SRC) Common Data Elements (CDEs) was initiated. The aim of this collaboration was to increase the efficiency and effectiveness of clinical research studies and clinical treatment outcomes, increase data quality, facilitate data sharing across studies, reduce study start-up time, more effectively aggregate information into metadata results, and educate new clinical investigators. The SRC CDE Working Group consisted of 32 worldwide experts in concussion from varied fields of related expertise divided into three Subgroups: Acute (<72 h post-concussion), Subacute (3 days-3 months post-concussion) and Persistent/Chronic (>3 months post-concussion). To develop CDEs, the Subgroups reviewed various domains, then selected from, refined, and added to existing CDEs, case report forms and field-tested data elements from national registries and funded research studies. Recommendations were posted to the NINDS CDE Website for Public Review from February 2017 to April 2017. Following an internal Working Group review of recommendations, along with consideration of comments received from the Public Review period, the first iteration (Version 1.0) of the NINDS SRC CDEs was completed in June 2017. The recommendations include Core and Supplemental-Highly Recommended CDEs for cognitive data elements and symptom checklists, as well as other outcomes and end-points (e.g., vestibular, oculomotor, balance, anxiety, depression), and sample case report forms (e.g., injury reporting, demographics, concussion history) for domains typically included in clinical research studies. The NINDS SRC CDEs and supporting documents are publicly available on the NINDS CDE website www.commondataelements.ninds.nih.gov . Widespread use of CDEs by researchers and clinicians will facilitate consistent SRC clinical research and trial design, data sharing, and metadata retrospective analysis.