A new approach to predicting postconcussion syndrome after mild traumatic brain injury based upon eye movement function

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Abstract

Following on from our earlier findings of a close relationship between motor function and outcome after mild traumatic brain injury (mTBI), this study examined whether it might be possible to predict poor recovery in the form of postconcussion syndrome (PCS) based upon early eye and arm motor function. Within 1 week post-injury, we assessed 37 mTBI patients on measures of saccades, oculomotor smooth pursuit, upper-limb visuomotor function, neuropsychological status, and self-reported health condition. At 3 months, 8 patients met the criteria for PCS. Using discriminant function analyses, we examined whether this future PCS-group could be identified prospectively based on motor function, neuropsychological status, and self-reported health condition at 1 week post-injury. Early eye movement function was the most effective in distinguishing between PCS and non-PCS patients, achieving a sensitivity and specificity of 100% in the present sample. This was followed by self-reported early health condition (sensitivity: 87%, specificity: 97%), early upper-limb motor performance (87%, 97%), neuropsychological function (62%, 100%), and age, gender, education and clinical measures of trauma severity (37%, 87%). Leave-one-out validation analyses confirmed eye movements as the most robust discriminator (sensitivity: 62%, specificity: 97%). Assessment of eye movement function after mTBI may contribute to a prospective identification of patients who develop PCS, supporting the targeting of early health-care intervention. © 2008 IEEE.

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APA

Heitger, M. H., Jones, R. D., & Anderson, T. J. (2008). A new approach to predicting postconcussion syndrome after mild traumatic brain injury based upon eye movement function. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS’08 - “Personalized Healthcare through Technology” (pp. 3570–3573). IEEE Computer Society. https://doi.org/10.1109/iembs.2008.4649977

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