期刊
JOURNAL OF NEUROTRAUMA
卷 29, 期 4, 页码 639-653出版社
MARY ANN LIEBERT, INC
DOI: 10.1089/neu.2011.1952
关键词
clinical studies; common data elements; data coding; data collection; pediatric; standardization; traumatic brain injury
资金
- NIH-NINDS [NS 042691]
- U.S. Department of Education/National Institute on Disability and Rehabilitation Research (DOE/NIDRR)
- National Institute on Disability and Rehabilitation Research
- Department of Veterans Affairs
- Defense and Veterans Brain Injury Center
- Defense Centers of Excellence
The Common Data Elements (CDEs) initiative is a National Institutes of Health (NIH) interagency effort to standardize naming, definitions, and data structure for clinical research variables. Comparisons of the results of clinical studies of neurological disorders have been hampered by variability in data coding, definitions, and procedures for sample collection. The CDE project objective is to enable comparison of future clinical trials results in major neurological disorders, including traumatic brain injury (TBI), stroke, multiple sclerosis, and epilepsy. As part of this effort, recommendations for CDEs for research on TBI were developed through a 2009 multi-agency initiative. Following the initial recommendations of the Working Group on Demographics and Clinical Assessment, a separate workgroup developed recommendations on the coding of clinical and demographic variables specific to pediatric TBI studies for subjects younger than 18 years. This article summarizes the selection of measures by the Pediatric TBI Demographics and Clinical Assessment Working Group. The variables are grouped into modules which are grouped into categories. For consistency with other CDE working groups, each variable was classified by priority (core, supplemental, and emerging). Templates were produced to summarize coding formats, guide selection of data points, and provide procedural recommendations. This proposed standardization, together with the products of the other pediatric TBI working groups in imaging, biomarkers, and outcome assessment, will facilitate multi-center studies, comparison of results across studies, and high-quality meta-analyses of individual patient data.
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