@article{ref1,
title="Optimizing components of the sport concussion assessment tool for acute concussion assessment",
journal="Neurosurgery",
year="2020",
author="Garcia, Gian-Gabriel P. and Yang, Jing and Lavieri, Mariel S. and McAllister, Thomas W. and McCrea, Michael A. and Broglio, Steven P.",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="BACKGROUND: The Sport Concussion Assessment Tool (SCAT) could be improved by identifying critical subsets that maximize diagnostic accuracy and eliminate low information elements.  OBJECTIVE: To identify optimal SCAT subsets for acute concussion assessment.  METHODS: Using Concussion Assessment, Research, and Education (CARE) Consortium data, we compared student-athletes' and cadets' preinjury baselines (n = 2178) with postinjury assessments within 6 h (n = 1456) and 24 to 48 h (n = 2394) by considering demographics, symptoms, Standard Assessment of Concussion (SAC), and Balance Error Scoring System (BESS) scores. We divided data into training/testing (60%/40%) sets. Using training data, we integrated logistic regression with an engineering methodology-mixed integer programming-to optimize models with ≤4, 8, 12, and 16 variables (Opt-k). We also created models including only raw scores (Opt-RS-k) and symptom, SAC, and BESS composite scores (summary scores). We evaluated models using testing data.  RESULTS: At <6 h and 24 to 48 h, most Opt-k and Opt-RS-k models included the following symptoms: do not feel right, headache, dizziness, sensitivity to noise, and whether physical or mental activity worsens symptoms. Opt-k models included SAC concentration and delayed recall change scores. Opt-k models had lower Brier scores (BS) and greater area under the curve (AUC) (<6 h: BS = 0.072-0.089, AUC = 0.95-0.96; 24-48 h: BS = 0.085-0.093, AUC = 0.94-0.95) than Opt-RS-k (<6 h: BS = 0.082-0.087, AUC = 0.93-0.95; 24-48 h: BS = 0.095-0.099, AUC = 0.92-0.93) and summary score models (<6 h: BS = 0.14, AUC = 0.89; 24-48 h: BS = 0.15, AUC = 0.87).  CONCLUSION: We identified SCAT subsets that accurately assess acute concussion and improve administration time over the complete battery, highlighting the importance of eliminating &quot;noisy&quot; elements. These findings can direct clinicians to the SCAT components that are most sensitive to acute concussion.<p /> <p>Language: en</p>",
language="en",
issn="0148-396X",
doi="10.1093/neuros/nyaa150",
url="http://dx.doi.org/10.1093/neuros/nyaa150"
}