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CARE Consortium: A data-driven approach to acute concussion assessment

Prominent concussion researchers previously have suggested incorporating levels of certainty into concussion diagnosis based on clinical experience. Gian-Gabriel Garcia, a postdoctoral industrial and operations engineering student at Michigan, led a team of researchers that sought to create a predictive model that could stratify concussion assessment and diagnosis based on objective data rather than clinical experience alone across a range of categories: no concussion, possible, probable or definite. They used data collected in the NCAA-Department of Defense Concussion Assessment, Research and Education Consortium study to develop and validate their framework, and their findings were published in the Journal of Neurotrauma.

What did the study find?

Using results from common concussion assessment tools, including those that measure balance and cognitive abilities, the researchers created an algorithm that accurately classified concussions as probable or definite (sensitivity = 91.07–97.40%). Definite and probable concussions were found to have higher Sport Concussion Assessment Tool symptom scores than unlikely and possible concussions (p < 0.05). Definite concussions were found to have had lower Standard Assessment of Concussion scores and higher Balance Error Scoring System scores (p < 0.05). Baseline to post-injury change scores for the SAC, SCAT symptoms and BESS were significantly different between acute possible and probable concussions and normal performances (p < 0.05). There were no consistent patterns in demographics across risk categories, although a greater proportion of concussions classified as unlikely were reported immediately compared with definite concussions (p < 0.05).

What are the implications?

The algorithm’s relative success suggests that a more refined approach to concussion assessment and classification, one driven by statistical models and data, not merely clinical intuition and experience, warrants further clinical evaluation and interpretation.

What’s next?

“Although clinical interpretation is still needed,” the researchers wrote. “Our data-driven approach to concussion risk stratification provides a promising step toward evidence-based concussion assessment.”