Pre-Clinical Traumatic Brain Injury Common Data Elements: Toward a Common Language Across Laboratories

Area of Science:

• Neuroscience and Neurotrauma
• Biomedical Informatics
• Translational Research

Background:

• Traumatic brain injury (TBI) poses a significant global health and economic challenge.
• Big data approaches offer potential to advance understanding of TBI mechanisms and patient outcomes.
• Existing common data elements (CDEs) exist for clinical TBI research, but a gap remains for preclinical studies.

Purpose of the Study:

• To address the lack of standardized data elements in preclinical TBI research.
• To create a defined set of CDEs to foster inter-laboratory collaboration and enable data meta-analysis.
• To facilitate a common language for preclinical TBI research by providing an overview of TBI models and pertinent CDEs.

Main Methods:

• Convened a committee of experts to develop a standardized set of data elements for preclinical TBI research.
• Subdivided CDEs into a Core module (generalizable) and Injury-Model-Specific modules (non-generalizable).
• Compiled an overview of established TBI models and their associated CDEs.

Main Results:

• A comprehensive set of CDEs has been established for preclinical TBI research.
• The CDEs are organized into core and model-specific modules to accommodate diverse study designs.
• The developed framework provides a foundation for standardized data collection and analysis across laboratories.

Conclusions:

• The creation of CDEs is crucial for advancing preclinical TBI research through improved data standardization and collaboration.
• This initiative will enable more robust data merging and meta-analysis, accelerating the translation of findings.
• The proposed CDE framework promotes a unified approach to preclinical TBI research, ultimately aiming to improve patient outcomes.