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Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion
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Developing Insights for Possible and Probable Acute Concussions Using Cluster Analysis.

Gian-Gabriel P Garcia1, Caroline M Schumb2, Mariel S Lavieri2

  • 1MGH Institute for Technology Assessment, Harvard Medical School, Boston, Massachusetts, USA.

Journal of Neurotrauma
|March 8, 2021
PubMed
Summary
This summary is machine-generated.

The Sport Concussion Assessment Tool (SCAT) is useful for diagnosing concussions. Clinicians should prioritize symptom checklists, particularly post-traumatic migraine and cognitive-fatigue symptoms, alongside the Standard Assessment of Concussion and Balance Error Scoring System.

Keywords:
Sport Concussion Assessment Toolclusteringconcussionpossible/probable concussion

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Area of Science:

  • Sports Medicine
  • Neurology
  • Clinical Assessment

Background:

  • The Sport Concussion Assessment Tool (SCAT) is widely used for concussion diagnosis.
  • Assessing concussions in athletes can be challenging, necessitating analysis of SCAT's utility in diverse populations.
  • The Concussion Assessment, Research, and Education (CARE) Consortium provides a valuable dataset for such analyses.

Purpose of the Study:

  • To evaluate the utility of the SCAT in identifying concussions in collegiate athletes and cadets.
  • To characterize athlete performance on SCAT components, including the Standard Assessment of Concussion (SAC) and Balance Error Scoring System (BESS).
  • To identify key variables for differentiating concussions from normal performance.

Main Methods:

  • Utilized a published algorithm to identify possible and probable concussions in collegiate athletes and cadets.
  • Applied cluster analysis to performance data from the SAC, BESS, and SCAT symptom checklist at <6 hours and 24-48 hours post-injury.
  • Analyzed raw scores and change scores for symptom number and post-traumatic migraine.

Main Results:

  • Total symptom number and post-traumatic migraine symptoms (raw and change scores) were the most frequent clustering variables distinguishing concussions from normal performance in both males and females.
  • These symptom-based variables showed the most significant differences between clusters across all time points.
  • The Standard Assessment of Concussion (SAC) and Balance Error Scoring System (BESS) scores also contributed to differentiating concussion groups.

Conclusions:

  • Clinicians should prioritize the assessment of total symptom burden, specifically post-traumatic migraine and cognitive-fatigue symptoms, when evaluating possible and probable concussions.
  • The SCAT symptom checklist, particularly these symptom clusters, appears highly valuable in acute concussion assessment.
  • Integrating symptom checklist findings with SAC and BESS scores can enhance diagnostic accuracy.