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Pre-Clinical Common Data Elements for Traumatic Brain Injury Research: Progress and Use Cases. | LitMetric

AI Article Synopsis

  • Traumatic brain injury (TBI) is a complex condition with varying causes and effects, making it difficult for researchers to achieve consistent results in both pre-clinical and clinical settings.
  • To tackle this issue, TBI research groups created 913 common data elements (CDEs) that standardize experimental parameters, animal characteristics, and injury models, aimed at improving data consistency and analysis across studies.
  • An analysis of combined legacy datasets revealed significant missing data issues, with around 35% missing values in the Morris water maze and 33% in the Rotarod experiments, highlighting the challenges yet to be overcome in harmonizing research efforts.

Article Abstract

Traumatic 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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082734PMC
http://dx.doi.org/10.1089/neu.2020.7328DOI Listing

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