• Journal of neurotrauma · May 2021

    Preclinical Common Data Elements for Traumatic Brain Injury Research: Progress and Use Cases.

    • Michelle C LaPlaca, HuieJ RussellJRBrain and Spinal Injury Center, Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA., Hasan B Alam, Adam D Bachstetter, Hűlya Bayir, Patrick F Bellgowan, Diana Cummings, C Edward Dixon, Adam R Ferguson, Chantelle Ferland-Beckham, Candace L Floyd, Stuart H Friess, Aristea S Galanopoulou, Edward D Hall, Neil G Harris, Bridget E Hawkins, Ramona R Hicks, Lindsey E Hulbert, Victoria E Johnson, Patricia A Kabitzke, Audrey D Lafrenaye, Vance P Lemmon, Carrie W Lifshitz, Jonathan Lifshitz, David J Loane, Leonie Misquitta, Vahagn C Nikolian, Linda J Noble-Haeusslein, Douglas H Smith, Carol Taylor-Burds, Nsini Umoh, Olga Vovk, Aaron M Williams, Margaret Young, and Laila J Zai.
    • Department of Biomedical Engineering, Georgia Institute of Technology/Emory University, Atlanta, Georgia, USA.
    • J. Neurotrauma. 2021 May 15; 38 (10): 139914101399-1410.

    AbstractTraumatic brain injury (TBI) is an extremely complex condition due to heterogeneity in injury mechanism, underlying conditions, and secondary injury. Pre-clinical and clinical researchers face challenges with reproducibility that negatively impact translation and therapeutic development for improved TBI patient outcomes. To address this challenge, TBI Pre-clinical Working Groups expanded upon previous efforts and developed common data elements (CDEs) to describe the most frequently used experimental parameters. The working groups created 913 CDEs to describe study metadata, animal characteristics, animal history, injury models, and behavioral tests. Use cases applied a set of commonly used CDEs to address and evaluate the degree of missing data resulting from combining legacy data from different laboratories for two different outcome measures (Morris water maze [MWM]; RotorRod/Rotarod). Data were cleaned and harmonized to Form Structures containing the relevant CDEs and subjected to missing value analysis. For the MWM dataset (358 animals from five studies, 44 CDEs), 50% of the CDEs contained at least one missing value, while for the Rotarod dataset (97 animals from three studies, 48 CDEs), over 60% of CDEs contained at least one missing value. Overall, 35% of values were missing across the MWM dataset, and 33% of values were missing for the Rotarod dataset, demonstrating both the feasibility and the challenge of combining legacy datasets using CDEs. The CDEs and the associated forms created here are available to the broader pre-clinical research community to promote consistent and comprehensive data acquisition, as well as to facilitate data sharing and formation of data repositories. In addition to addressing the challenge of standardization in TBI pre-clinical studies, this effort is intended to bring attention to the discrepancies in assessment and outcome metrics among pre-clinical laboratories and ultimately accelerate translation to clinical research.

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