Susan M Wojcik1. 1. Department of Emergency Medicine, Upstate Medical University , Syracuse, NY , USA.
Abstract
OBJECTIVE: To identify factors that can predict which emergency department (ED) patients with mTBI are likely to develop persistent post-concussion symptoms (PPCS). DESIGN: A matched case-control study was conducted at a Level 1 trauma centre between June 2006 and July 2009. Patients diagnosed with mTBI in the ED and diagnosed at a concussion management programme with at least one PPCS (85 cases) were compared to patients diagnosed with mTBI in the ED (340 controls) to determine if factors assessed at the time of ED presentation could predict patients likely to develop persistent symptoms. RESULTS: Multivariable hierarchical logistic regression with variables indicating increased risk for PPCS (prior mTBI, history of depression, history of anxiety, multiple injury, forgetfulness/poor memory, noise sensitivity, or light sensitivity) resulted in a final predictive model including prior mTBI, history of anxiety, forgetfulness/poor memory and light sensitivity. The final model had a specificity of 87.9% and a sensitivity of 69.9%. CONCLUSIONS: A strong prediction model to identify those ED patients with mTBI at risk for PPCS was developed and could be easily implemented in the ED; therefore, helping to target those patients who would potentially benefit from close follow-up.
OBJECTIVE: To identify factors that can predict which emergency department (ED) patients with mTBI are likely to develop persistent post-concussion symptoms (PPCS). DESIGN: A matched case-control study was conducted at a Level 1 trauma centre between June 2006 and July 2009. Patients diagnosed with mTBI in the ED and diagnosed at a concussion management programme with at least one PPCS (85 cases) were compared to patients diagnosed with mTBI in the ED (340 controls) to determine if factors assessed at the time of ED presentation could predict patients likely to develop persistent symptoms. RESULTS: Multivariable hierarchical logistic regression with variables indicating increased risk for PPCS (prior mTBI, history of depression, history of anxiety, multiple injury, forgetfulness/poor memory, noise sensitivity, or light sensitivity) resulted in a final predictive model including prior mTBI, history of anxiety, forgetfulness/poor memory and light sensitivity. The final model had a specificity of 87.9% and a sensitivity of 69.9%. CONCLUSIONS: A strong prediction model to identify those ED patients with mTBI at risk for PPCS was developed and could be easily implemented in the ED; therefore, helping to target those patients who would potentially benefit from close follow-up.
Authors: Daniel Shepherd; Jason Landon; Mathew Kalloor; Suzanne Barker-Collo; Nicola Starkey; Kelly Jones; Shanthi Ameratunga; Alice Theadom Journal: Qual Life Res Date: 2019-10-30 Impact factor: 4.147
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