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Towards the Development of an Integrative, Evidence-Based Suite of Indicators for the Prediction of Outcome Following Mild Traumatic Brain Injury: Results from a Pilot Study

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Curtin Health Innovation Research Institute, Curtin University, Bentley, WA 6102, Australia
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Perron Institute for Neurological and Translational Science, Nedlands, WA 6009, Australia
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Telethon Kids Institute, West Perth, WA 6005, Australia
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School of Biological Sciences, The University of Western Australia, Crawley, WA 6009, Australia
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Emergency Medicine, The University of Western Australia, Crawley, WA 6009, Australia
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Centre for Clinical Research in Emergency Medicine, Harry Perkins Institute of Medical Research, Nedlands, WA 6000, Australia
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Emergency Department, Royal Perth Hospital, Perth, WA 6000, Australia
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Radiology Department, Royal Perth Hospital, Perth, WA 6000, Australia
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School of Medicine, The University of Western Australia, Crawley, WA 6009, Australia
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School of Surgery, The University of Western Australia, Crawley, WA 6009, Australia
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Neurological Intervention and Imaging Service of Western Australia, Sir Charles Gardener Hospital, Nedlands, WA 6009, Australia
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School of Psychological Science, The University of Western Australia, Crawley, WA 6009, Australia
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Author to whom correspondence should be addressed.
Brain Sci. 2020, 10(1), 23; https://doi.org/10.3390/brainsci10010023
Received: 20 November 2019 / Revised: 16 December 2019 / Accepted: 30 December 2019 / Published: 2 January 2020
Background: Persisting post-concussion symptoms (PPCS) is a complex, multifaceted condition in which individuals continue to experience the symptoms of mild traumatic brain injury (mTBI; concussion) beyond the timeframe that it typically takes to recover. Currently, there is no way of knowing which individuals may develop this condition. Method: Patients presenting to a hospital emergency department (ED) within 48 h of sustaining a mTBI underwent neuropsychological assessment and demographic, injury-related information and blood samples were collected. Concentrations of blood-based biomarkers neuron specific enolase, neurofilament protein-light, and glial fibrillary acidic protein were assessed, and a subset of patients also underwent diffusion tensor–magnetic resonance imaging; both relative to healthy controls. Individuals were classified as having PPCS if they reported a score of 25 or higher on the Rivermead Postconcussion Symptoms Questionnaire at ~28 days post-injury. Univariate exact logistic regression was performed to identify measures that may be predictive of PPCS. Neuroimaging data were examined for differences in fractional anisotropy (FA) and mean diffusivity in regions of interest. Results: Of n = 36 individuals, three (8.33%) were classified as having PPCS. Increased performance on the Repeatable Battery for the Assessment of Neuropsychological Status Update Total Score (OR = 0.81, 95% CI: 0.61–0.95, p = 0.004), Immediate Memory (OR = 0.79, 95% CI: 0.56–0.94, p = 0.001), and Attention (OR = 0.86, 95% CI: 0.71–0.97, p = 0.007) indices, as well as faster completion of the Trails Making Test B (OR = 1.06, 95% CI: 1.00–1.12, p = 0.032) at ED presentation were associated with a statistically significant decreased odds of an individual being classified as having PPCS. There was no significant association between blood-based biomarkers and PPCS in this small sample, although glial fibrillary acidic protein (GFAP) was significantly increased in individuals with mTBI relative to healthy controls. Furthermore, relative to healthy age and sex-matched controls (n = 8), individuals with mTBI (n = 14) had higher levels of FA within the left inferior frontal occipital fasciculus (t (18.06) = −3.01, p = 0.008). Conclusion: Performance on neuropsychological measures may be useful for predicting PPCS, but further investigation is required to elucidate the utility of this and other potential predictors. View Full-Text
Keywords: persistent post-concussion symptoms; blood-based biomarkers; neuropsychological assessment; MRI; prediction persistent post-concussion symptoms; blood-based biomarkers; neuropsychological assessment; MRI; prediction
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Gozt, A.; Licari, M.; Halstrom, A.; Milbourn, H.; Lydiard, S.; Black, A.; Arendts, G.; Macdonald, S.; Song, S.; MacDonald, E.; Vlaskovsky, P.; Burrows, S.; Bynevelt, M.; Pestell, C.; Fatovich, D.; Fitzgerald, M. Towards the Development of an Integrative, Evidence-Based Suite of Indicators for the Prediction of Outcome Following Mild Traumatic Brain Injury: Results from a Pilot Study. Brain Sci. 2020, 10, 23.

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