Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-05T04:20:54.823Z Has data issue: false hasContentIssue false
  • English
  • Français

Cognition in the Emergency Department as a Predictor of Recovery after Pediatric Mild Traumatic Brain Injury

Published online by Cambridge University Press:  20 January 2016

Brian L. Brooks ,
Hussain Daya ,
Samna Khan ,
Helen L. Carlson ,
Angelo Mikrogianakis  and
Karen M. Barlow
Brian L. Brooks*
Affiliation:
Neurosciences (Brain Injury and Vi Riddell Rehabilitation Program), Alberta Children’s Hospital, Calgary, Alberta, Canada Departments of Paediatrics and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Department of Psychology, Faculty of Arts, University of Calgary, Calgary, Alberta, Canada Alberta Children’s Hospital Research Institute for Child & Maternal Health, University of Calgary, Calgary, Alberta, Canada
Hussain Daya
Affiliation:
Department of Psychology, University of Lethbridge, Lethbridge, Alberta, Canada
Samna Khan
Affiliation:
Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
Helen L. Carlson
Affiliation:
Neurosciences (Brain Injury and Vi Riddell Rehabilitation Program), Alberta Children’s Hospital, Calgary, Alberta, Canada Alberta Children’s Hospital Research Institute for Child & Maternal Health, University of Calgary, Calgary, Alberta, Canada
Angelo Mikrogianakis
Affiliation:
Departments of Paediatrics and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Alberta Children’s Hospital Research Institute for Child & Maternal Health, University of Calgary, Calgary, Alberta, Canada Section of Emergency Medicine, Alberta Children’s Hospital, Alberta, Canada
Karen M. Barlow
Affiliation:
Neurosciences (Brain Injury and Vi Riddell Rehabilitation Program), Alberta Children’s Hospital, Calgary, Alberta, Canada Departments of Paediatrics and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Alberta Children’s Hospital Research Institute for Child & Maternal Health, University of Calgary, Calgary, Alberta, Canada
*
Correspondence and reprint requests to: Brian L. Brooks, Neurosciences program, Alberta Children’s Hospital, 2888 Shaganappi Trail NW, Calgary, Alberta, Canada T3B 6A8. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Cognitive abilities can be acutely disrupted in children and adolescents who sustain a mild traumatic brain injury (mTBI), with the potential that these disruptions may be predictive of recovery. The objective of this study was to determine if cognitive abilities in the emergency department (ED) can differentiate and predict poor symptom recovery following a pediatric mTBI. Participants included 77 male and female youth with a mTBI (mean age=13.6; SD=2.6). All participants completed computerized cognitive testing (four subtests from the CNS Vital Signs) when they presented to the ED. Symptom measurement occurred in the ED (for pre-injury), at 7–10 days, 1 month, 2 months, and 3 months post-mTBI using the post-concussion symptom inventory (PCSI). Recovery was determined using reliable change scores for symptom ratings from 28 orthopedic injury controls (mean age=13.9 years; SD=2.1). Significantly worse Reaction Time scores (i.e., rapid information processing) in the ED were found in those who remained symptomatic at 1 month. Performances on the Reaction Time and Cognitive Flexibility domain scores were predictive of symptom outcome at 1 month for youth (above and beyond sex and baseline symptom burden). Youth with low scores on Reaction Time and/or Cognitive Flexibility were nearly 15 times (95%CI=1.8–323.5) more likely to remain symptomatic at 1 month post-mTBI. No significant group differences were found at 7–10 days, 2 months, or 3 months post-injury. Rapid computerized cognitive testing in the ED following a mTBI may help clinicians predict which youth may or may not remain symptomatic at follow-up. (JINS, 2016, 22, 379–387)

Keywords

Brain injuriesTraumaticConcussionMildCognitionOutcomes researchChildPost-concussion syndrome
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 22 , Issue 4 , April 2016 , pp. 379 - 387
Copyright
Copyright © The International Neuropsychological Society 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

American Association for Automotive Medicine (1990). The Abbreviated Injury Scale (AIS) -1990 revision. Des Plaines, IL: American Association for Automotive Medicine.Google Scholar
Babcock, L., Byczkowski, T., Wade, S.L., Ho, M., Mookerjee, S., & Bazarian, J.J. (2013). Predicting postconcussion syndrome after mild traumatic brain injury in children and adolescents who present to the emergency department. JAMA Pediatrics, 167(2), 156–161.CrossRefGoogle ScholarPubMed
Barlow, K.M., Crawford, S., Stevenson, A., Sandhu, S.S., Belanger, F., & Dewey, D. (2010). Epidemiology of postconcussion syndrome in pediatric mild traumatic brain injury. Pediatrics, 126(2), e374–e381.CrossRefGoogle ScholarPubMed
Barlow, K.M., Crawford, S., Brooks, B.L., Turley, B., & Mikrogianakis, A. (2015). The incidence of post concussion syndrome remains stable following mild traumatic brain injury in children. Pediatric Neurology, 53(6), 491–497.CrossRefGoogle Scholar
Belanger, H.G., Spiegel, E., & Vanderploeg, R.D. (2010). Neuropsychological performance following a history of multiple self-reported concussions: A meta-analysis. Journal of the International Neuropsychological Society, 16(2), 262–267.CrossRefGoogle ScholarPubMed
Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32.CrossRefGoogle Scholar
Breiman, L., Friedman, J.H., Olshen, R.A., & Stone, C.J. (1984). Classification and regression trees. New York: Chapman & Hall/CRC.Google Scholar
Brooks, B.L., & Barlow, K.M. (2011). A methodology for assessing treatment response in Hashimoto’s encephalopathy: A case study demonstrating repeated computerized neuropsychological testing. Journal of Child Neurology, 26(6), 786–791.CrossRefGoogle ScholarPubMed
Brooks, B.L., Iverson, G.L., Sherman, E.M., & Roberge, M.C. (2010). Identifying cognitive problems in children and adolescents with depression using computerized neuropsychological testing. Applied Neuropsychology, 17(1), 37–43.CrossRefGoogle ScholarPubMed
Brooks, B.L., Kadoura, B., Turley, B., Crawford, S., Mikrogianakis, A., & Barlow, K.M. (2014). Perception of recovery after pediatric mild TBI is influenced by the ‘good old days’ bias: Implications for clinical practice and outcomes research. Archives of Clinical Neuropsychology, 29(2), 186–193.CrossRefGoogle Scholar
Brooks, B.L., McKay, C., Mrazik, M., Barlow, K.M., Meeuwisse, W., & Emery, C.A. (2013). Subjective, but not objective, lingering effects of multiple past concussions in adolescents. Journal of Neurotrauma, 30(17), 1469–1475.CrossRefGoogle Scholar
Brooks, B.L., Mrazik, M., Barlow, K.M., McKay, C.D., Meeuwisse, W., & Emery, C.A. (2014). Absence of differences between male and female adolescents with a prior sport concussion. Journal of Head Trauma Rehabilitation, 29(3), 257–264.CrossRefGoogle ScholarPubMed
Brooks, B.L., & Sherman, E.M. (2012). Computerized neuropsychological testing to rapidly evaluate cognition in pediatric patients with neurologic disorders. Journal of Child Neurology, 27(8), 982–991.CrossRefGoogle ScholarPubMed
Brooks, B.L., Khan, A., Daya, H., Mikrogianakis, A., & Barlow, K.M. (2014). Neurocognition in the emergency department following a mild traumatic brain injury in youth. Journal of Neurotrauma, 31(20), 1744–1749.CrossRefGoogle Scholar
Cassidy, J.D., Carroll, L.J., Peloso, P.M., Borg, J., von Holst, H., Holm, L., & Coronado, V.G. (2004). Incidence, risk factors and prevention of mild traumatic brain injury: Results of the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. Journal of Rehabilitation Medicine, 36(43 Suppl.), 28–60.CrossRefGoogle Scholar
Centers for Disease Control and Prevention (2011). Nonfatal traumatic brain injuries related to sports and recreation activities among persons aged <19 years - United States, 2001-2009. Atlanta: CDC.Google Scholar
Eisenberg, M.A., Andrea, J., Meehan, W., & Mannix, R. (2013). Time interval between concussions and symptom duration. Pediatrics, 132(1), 8–17.CrossRefGoogle ScholarPubMed
Gioia, G.A., Collins, M., & Isquith, P.K. (2008). Improving identification and diagnosis of mild traumatic brain injury with evidence: Psychometric support for the acute concussion evaluation. Journal of Head Trauma Rehabilitation, 23(4), 230–242.CrossRefGoogle ScholarPubMed
Grubenhoff, J.A., Deakyne, S.J., Brou, L., Bajaj, L., Comstock, R.D., & Kirkwood, M.W. (2014). Acute concussion symptom severity and delayed symptom resolution. Pediatrics, 134(1), 54–62.CrossRefGoogle ScholarPubMed
Grubenhoff, J.A., Kirkwood, M., Gao, D., Deakyne, S., & Wathen, J. (2010). Evaluation of the standardized assessment of concussion in a pediatric emergency department. Pediatrics, 126(4), 688–695.CrossRefGoogle Scholar
Gualtieri, C.T., & Johnson, L.G. (2006). Reliability and validity of a computerized neurocognitive test battery, CNS Vital Signs. Archives of Clinical Neuropsychology, 21(7), 623–643.CrossRefGoogle ScholarPubMed
Haring, R.S., Canner, J.K., Asemota, A.O., George, B.P., Selvarajah, S., Haider, A.H., & Schneider, E.B. (2015). Trends in incidence and severity of sports-related traumatic brain injury (TBI) in the emergency department, 2006-2011. Brain Injury, 29(7--8), 989–992.CrossRefGoogle Scholar
IBM Corporation (2010). IBM SPSS Statistics for Windows, Version 19.0. Armonk, NY: IBM Corp.Google Scholar
Iverson, G.L. (2007). Predicting slow recovery from sports-related concussion: The new simple-complex distinction. Clinical Journal of Sport Medicine, 17(1), 31–37.CrossRefGoogle Scholar
Jacobson, N.S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59(1), 12–19.CrossRefGoogle ScholarPubMed
Khetani, A., Khan, A., Kadoura, B., Narous, M., Brooks, B.L., & Barlow, K.M. (2014). The feasibility of computerized cognitive testing in the emergency room. Brain Injury, 28(5-6), 844.Google Scholar
Kontos, A.P., Elbin, R.J., Lau, B., Simensky, S., Freund, B., French, J., & Collins, M.W. (2013). Posttraumatic migraine as a predictor of recovery and cognitive impairment after sport-related concussion. American Journal of Sports Medicine, 41(7), 1497–1504.CrossRefGoogle ScholarPubMed
Lau, B.C., Collins, M.W., & Lovell, M.R. (2011). Sensitivity and specificity of subacute computerized neurocognitive testing and symptom evaluation in predicting outcomes after sports-related concussion. American Journal of Sports Medicine, 39(6), 1209–1216.CrossRefGoogle ScholarPubMed
Lau, B.C., Collins, M.W., & Lovell, M.R. (2012). Cutoff scores in neurocognitive testing and symptom clusters that predict protracted recovery from concussions in high school athletes. Neurosurgery, 70(2), 371–379; discussion 379.CrossRefGoogle ScholarPubMed
Lemon, S.C., Roy, J., Clark, M.A., Friedmann, P.D., & Rakowski, W. (2003). Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression. Annals of Behavioral Medicine, 26(3), 172–181.CrossRefGoogle ScholarPubMed
Macpherson, A., Fridman, L., Scolink, M., Corallo, A., & Guttman, A. (2014). A population-based study of paediatric emergency department and office visits for concussions from 2003 to 2010. Pediatrics & Child Health, 19(10), 543–546.CrossRefGoogle ScholarPubMed
Mannix, R., Iverson, G.L., Maxwell, B., Atkins, J.E., Zafonte, R., & Berkner, P.D. (2014). Multiple prior concussions are associated with symptoms in high school athletes. Annals of Clinical and Translational Neurology, 1(6), 433–438.CrossRefGoogle ScholarPubMed
McCauley, S.R., Wilde, E.A., Anderson, V.A., Bedell, G., Beers, S.R., Campbell, T.F., & Yeates, K.O. (2012). Recommendations for the use of common outcome measures in pediatric traumatic brain injury research. Journal of Neurotrauma, 29(4), 678–705.CrossRefGoogle ScholarPubMed
McNally, K.A., Bangert, B., Dietrich, A., Nuss, K., Rusin, J., Wright, M., & Yeates, K.O. (2013). Injury versus noninjury factors as predictors of postconcussive symptoms following mild traumatic brain injury in children. Neuropsychology, 27(1), 1–12.CrossRefGoogle ScholarPubMed
Meehan, W.P. III, & Mannix, R. (2010). Pediatric concussions in United States emergency departments in the years 2002 to 2006. Journal of Pediatrics, 157(6), 889–893.CrossRefGoogle ScholarPubMed
Meehan, W.P. III, Mannix, R., Monuteaux, M.C., Stein, C.J., & Bachur, R.G. (2014). Early symptom burden predicts recovery after sport-related concussion. Neurology, 83(24), 2204–2210.CrossRefGoogle ScholarPubMed
Morgan, C.D., Zuckerman, S.L., Lee, Y.M., King, L., Beaird, S., Sills, A.K., & Solomon, G.S. (2015). Predictors of postconcussion syndrome after sports-related concussion in young athletes: A matched case-control study. Journal of Neurosurgery: Pediatrics, 15(6), 589–598.Google ScholarPubMed
Nance, M.L., Polk-Williams, A., Collins, M.W., & Wiebe, D.J. (2009). Neurocognitive evaluation of mild traumatic brain injury in the hospitalized pediatric population. Annals of Surgery, 249(5), 859–863.CrossRefGoogle ScholarPubMed
R Core Team. (2012). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
Rieger, B.P., Lewandowski, L.J., Callahan, J.M., Spenceley, L., Truckenmiller, A., Gathje, R., & Miller, L.A. (2013). A prospective study of symptoms and neurocognitive outcomes in youth with concussion vs orthopaedic injuries. Brain Injury, 27(2), 169–178.CrossRefGoogle ScholarPubMed
Sady, M.D., Vaughan, C.G., & Gioia, G.A. (2014). Psychometric characteristics of the postconcussion symptom inventory in children and adolescents. Archives of Clinical Neuropsychology, 29(4), 348–363.CrossRefGoogle ScholarPubMed
Scopaz, K.A., & Hatzenbuehler, J.R. (2013). Risk modifiers for concussion and prolonged recovery. Sports Health, 5(6), 537–541.CrossRefGoogle ScholarPubMed
Sheedy, J., Geffen, G., Donnelly, J., & Faux, S. (2006). Emergency department assessment of mild traumatic brain injury and prediction of post-concussion symptoms at one month post injury. Journal of Clinical and Experimental Neuropsychology, 28(5), 755–772.CrossRefGoogle ScholarPubMed
Sheedy, J., Harvey, E., Faux, S., Geffen, G., & Shores, E.A. (2009). Emergency department assessment of mild traumatic brain injury and the prediction of postconcussive symptoms: A 3-month prospective study. Journal of Head Trauma Rehabilitation, 24(5), 333–343.CrossRefGoogle ScholarPubMed
Strobl, C., Boulesteix, A.L., Kneib, T., Augustin, T., & Zeileis, A. (2008). Conditional variable importance for random forests. BMC Bioinformatics, 9, 307.CrossRefGoogle ScholarPubMed
Therneau, T.M., & Atkinson, E.J. (2014). An Introduction to Recursive Partitioning Using the RPART Routines. Retrieved from http://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf Google Scholar
Zemek, R.L., Farion, K.J., Sampson, M., & McGahern, C. (2013). Prognosticators of persistent symptoms following pediatric concussion: A systematic review. JAMA Pediatrics, 167(3), 259–265.CrossRefGoogle ScholarPubMed