Results of scoping review do not support mild traumatic brain injury being associated with a high incidence of chronic cognitive impairment: Commentary on McInnes et al. 2017


Authors: Grant L. Iverson aff001;  Justin E. Karr aff005;  Andrew J. Gardner aff006;  Noah D. Silverberg aff007;  Douglas P. Terry aff001
Authors place of work: Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, United States of America aff001;  Spaulding Rehabilitation Hospital and Spaulding Research Institute, Charlestown, Massachusetts, United States of America aff002;  MassGeneral Hospital Children Sports Concussion Program, Boston, Massachusetts, United States of America aff003;  Home Base, A Red Sox Foundation and Massachusetts General Hospital Program, Charlestown, Massachusetts, United States of America aff004;  Department of Psychology, University of Victoria, Victoria, British Columbia, Canada aff005;  Hunter New England Local Health District Sports Concussion Program and Centre for Stroke and Brain Injury, School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia aff006;  Division of Physical Medicine & Rehabilitation, University of British Columbia, Vancouver, British Columbia, Canada aff007;  Rehabilitation Research Program, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada aff008
Published in the journal: PLoS ONE 14(9)
Category: Formal Comment
doi: 10.1371/journal.pone.0218997

Summary

A recently published review of 45 studies concluded that approximately half of individuals who sustain a single mild traumatic brain injury (MTBI) experience long-term cognitive impairment (McInnes et al. Mild Traumatic Brain Injury (mTBI) and chronic cognitive impairment: A scoping review. PLoS ONE 2017;12:e0174847). Stratified by age, they reported that 50% of children and 58% of adults showed some form of cognitive impairment. We contend that the McInnes et al. review used a definition of “cognitive impairment” that was idiosyncratic, not applicable to individual patients or subjects, inconsistent with how cognitive impairment is defined in clinical practice and research, and resulted in a large number of false positive cases of cognitive impairment. For example, if a study reported a statistically significant difference on a single cognitive test, the authors concluded that every subject with a MTBI in that study was cognitively impaired–an approach that cannot be justified statistically or psychometrically. The authors concluded that impairment was present in various cognitive domains, such as attention, memory, and executive functioning, but they did not analyze or report the results from any of these specific cognitive domains. Moreover, their analyses and conclusions regarding many published studies contradicted the interpretations provided by the original authors of those studies. We re-reviewed all 45 studies and extracted the main conclusions from each. We conclude that a single MTBI is not associated with a high incidence of chronic cognitive impairment.

Keywords:

Biology and life sciences – Neuroscience – Cognitive science – Cognitive neuroscience – Cognitive neurology – Cognitive impairment – Cognitive psychology – Cognition – Memory – Cognitive neuroscience – Cognitive neurology – Cognitive impairment – Learning and memory – Memory – Neuropsychology – Psychology – Cognitive psychology – Neuropsychology – Medicine and health sciences – Neurology – Cognitive neurology – Cognitive impairment – Critical care and emergency medicine – Trauma medicine – Traumatic injury – Head injury – Social sciences – Psychology – Cognitive psychology – Neuropsychology – Research and analysis methods – Research assessment – Systematic reviews

Introduction

A recently published scoping review of the literature concluded that approximately half of individuals who sustain a single mild traumatic brain injury (MTBI) experience long-term cognitive impairment [1]. The authors identified 45 studies that met their inclusion criteria. Through their synthesis and analysis, they reported that “1963 participants out of 3593, or approximately 55% of our sample collapsed across all time points showed cognitive impairment” (page 10). Stratified by age, they reported that 50% of children and 58% of adults showed some form of cognitive impairment (page 11). They asserted that “a large proportion of individuals with a single mTBI will continue to demonstrate measurable impairment in various cognitive domains including executive function, learning/memory, attention, processing speed, and language function long after the initial injury” (page 13). They stated that the published literature to date represents a “gross underestimation” (pages 13 and 14) of the extent of cognitive impairment caused by a single MTBI, and “it is possible that our results represent a further underestimation of the incidence of persistent cognitive impairment following a single mTBI” (page 14).

We disagree with the findings and conclusions summarized above from the scoping review published by McInnes and colleagues [1]. Their conclusions are fundamentally different from, or run counter to, findings from numerous meta-analyses of the MTBI neuropsychological literature [215]. A scoping review is relatively new and still evolving approach to knowledge synthesis. Standardized methodology and reporting guidelines are not yet available [16, 17], but there is consensus that the main purpose of scoping reviews is to examine the extent and nature of available research in a defined subject area [1618]. A scoping review can be helpful for a subject area that has not previously been comprehensively reviewed, often to determine if there is sufficient evidence to conduct a systematic review [18, 19]. This seems to be the reason why McInnes et al. selected this method of knowledge synthesis (i.e., they wrote: “the studies that assess long-term cognitive outcomes in singly-concussed individuals have not been gathered and reviewed”; page 2).

There are essential differences between scoping reviews and systematic reviews. Scoping reviews do not have rigid exclusion criteria and do not formally evaluate the quality of evidence [16, 19], consistent with their goal of summarizing the breadth of literature. In contrast, systematic reviewers perform both of these tasks in order to reduce bias in trying to answer specific research questions, such as prognosis or treatment efficacy. Whereas systematic reviews often include a meta-analysis of aggregated quantitative data, scoping reviews generally provide only a descriptive narrative [16]. Scoping reviews may also include a “descriptive numerical summary” to map the time, location, and source of available research, typically reported as a frequency count of studies with certain characteristics [1720].

McInnes et al. did not exclude studies with a high risk of bias and did not perform quality appraisals of included studies, consistent with scoping review methodology [19]. However, they went well beyond numerically summarizing the number and type studies available. They recoded and synthesized quantitative information, and from these analyses, drew conclusions about the incidence of long-term cognitive impairment following MTBI. This falls outside the purview of a scoping review and exposed McInnes et al. to the risk of flawed conclusions. In their original description of scoping review, Arksey and O’Malley explained that “unlike a systematic review the scoping study does not seek to ‘synthesize’ evidence or to aggregate findings from different studies… because the scoping study does not seek to assess quality of evidence and consequently cannot determine whether particular studies provide robust or generalizable findings”[18]. McInnes et al. used systematic review techniques to synthesize evidence without an assessment of the risk for bias or consideration of how bias might influence their results. A systematic review that omits these elements provides “critically low” confidence in their conclusions and “should not be relied on to provide an accurate and comprehensive summary of the available studies” ([21, page 6].

We have three primary concerns regarding the methodology used to synthesize and summarize data in their scoping review. First, their definition of “cognitive impairment” was idiosyncratic, not applicable to individual patients or subjects, and inconsistent with how cognitive impairment is defined in clinical practice and research. Their definition resulted in a large number of false positive cases of “cognitive impairment.” In the McInnes et al. review, participants in the original studies were dichotomized into “cognitively impaired” and “cognitively unimpaired” groups. McInnes et al. [1] defined individuals as having cognitive impairment “if their outcome measure score significantly differed from those of the control groups or the normative data, or if they were below author-identified cut-off scores” (page 7). Of the 45 original studies, only 9 studies (20%) were dichotomized based on author-identified definitions of cognitive impairment [2230]. The remaining studies did not define “cognitive impairment” in their text and were dichotomized by McInnes et al. based on differences on significance testing between the MTBI and control groups. Two original studies that defined cognitive impairment in an a priori manner did not report the incidence of cognitive impairment in their sample, and those studies were classified by McInnes et al. based on group comparisons [31, 32]. If a study reported a statistically significant difference on a single cognitive test, the authors concluded that every subject in that study with a MTBI was cognitively impaired. This method represents a misunderstanding or misapplication of statistical significance testing. A statistically significant difference between an MTBI group and a control group means that the difference between the means of groups is not likely to be zero, thus the associated term in statistical testing is null hypothesis testing. A p-value does not provide us information regarding the practical or clinical significance of the difference, the magnitude of the difference, or whether the difference is large enough to classify people into one group or another. A statistically significant difference between groups on a test or tests cannot be used to accurately or reliably classify individual subjects as cognitively impaired. Classifying every subject in the MTBI group as cognitively impaired in these instances also does not make sense from a practical standpoint. There are likely several individuals in the MTBI groups who performed better than the mean of the control groups and/or whose scores would be interpreted as broadly normal (e.g., average or better) based on using traditional neuropsychological interpretation schemes. These methods artificially inflate the percentage of individuals classified as cognitively impaired. Second, the authors concluded that impairment was present in various cognitive domains, such as attention, memory, and executive functioning (page 13 of the Discussion), but they did not analyze or report the results from any of these cognitive domains in their review. Third, their analyses and conclusions regarding many published studies contradicted the interpretations provided by the original authors of the studies (e.g., [3335]).

Materials and methods

Review of 45 articles relating to cognitive functioning following a single MTBI

We re-reviewed the 45 articles identified in the McInnes et al. scoping review [1] to examine the sampling strategy and statistical techniques used when determining if participants who experienced an MTBI had cognitive impairment. Further, we thought it would be useful to provide a summary statement for each of these 45 studies based on the data and original authors’ conclusions. We did not seek to complete our own scoping review, systematic review, or meta-analysis of these studies. Prior systematic reviews and meta-analyses have examined this topic in great detail [215].

From each article, we extracted the percentage of the MTBI sample with a complicated MTBI (i.e., macrostructural trauma-related intracranial abnormalities visible on computed tomography or magnetic resonance imaging), as well as the sample size, age (mean and standard deviation), and recruitment settings for the MTBI and control groups. We also extracted the number of group comparisons for cognitive outcomes (i.e., the number of test scores that were analyzed/compared between the MTBI and control groups) and the number of statistically significant group differences. We determined whether the original authors classified individual subjects as cognitively impaired or not, and whether the original authors drew conclusions about whether or not subjects were cognitively impaired. We examined whether other factors that may influence cognitive functioning were reported in the original studies (i.e., whether the original study assessed for pre-morbid or current intellectual functioning, or mental health problems). This does not necessarily mean that these variables were used in statistical models to control for their potential effect when assessing for cognitive differences between groups. Three authors (JK, AG, and DT) with experience conducting systematic reviews [11, 12, 36, 37] completed extractions for all of the articles. Each study was reviewed by two authors. We provided a brief summary of the statistical findings and implications of each article, using quotations from the original articles whenever possible.

Results

The findings were consolidated into Table 1. Several studies summarized in the McInnes et al. scoping review [1] did not include means, SDs, or effect sizes for the statistical comparisons between groups on cognitive testing (e.g., [22, 27, 3842]). As such, it is not possible to draw conclusions from those studies regarding the magnitude of the difference between the MTBI group and the control group. Moreover, for most of the studies it is not known whether a subgroup within the MTBI group met criteria for cognitive impairment. As noted above, the scoping review by McInnes and colleagues [1] came to fundamentally different conclusions in comparison to numerous published meta-analyses of the MTBI neuropsychological literature [215]. McInnes and colleagues [1] identified some more recently published studies, since 2013, that were not included in previous systematic reviews and meta-analyses because they were published after those searches were performed [22, 23, 34, 4350]. However, those more recently published studies, as a rule, did not compute the percentages of the MTBI sample that met criteria for cognitive impairment, nor did they yield results suggestive of chronic cognitive impairment (see Table 1).

Tab. 1.

Summary of studies 3, 6, 12, and >12 months post injury.

<h2>Summary of studies 3, 6, 12, and >12 months post injury.</h2>

McInnes et al. [1] identified 12 studies, at the 3 month post-injury time period, that they thought revealed all subjects to have cognitive impairment [23, 34, 38, 39, 4345, 5155] (demarcated with an asterisk in Table 1), 4 studies that had both cognitively impaired and unimpaired participants [22, 24, 30, 59] and 4 studies that they did not think revealed cognitive impairment in any participants [33, 5658]. The samples and research methods varied considerably across these studies (see Table 1). Only five studies [2224, 30, 59] used a methodology in which individual subjects were classified as having cognitive impairment. None of the original authors of the studies stated or concluded that all subjects with MTBIs were cognitively impaired.

McInnes et al. [1] identified 6 studies, at the 6 month post-injury time period, that they thought revealed all subjects to have cognitive impairment [25, 34, 39, 41, 55, 60] (demarcated with an asterisk in Table 1), 5 studies that revealed cognitive impairment in some subjects [26, 27, 30, 46, 61] and 1 study that they did not think revealed cognitive impairment in any subjects [35]. For two of the studies, multiple statistical comparisons of test scores between the MTBI group and the control group were conducted, with only one statistically significant result [34, 41]. Only three studies [2527] used a methodology in which individual subjects were classified as having cognitive impairment. The original authors of the studies did not state or conclude that all subjects with MTBIs were cognitively impaired.

McInnes et al. [1] identified 11 studies, at the 12 month post-injury time period, that they thought revealed all subjects to have cognitive impairment [28, 31, 3941, 47, 55, 6265] (demarcated with an asterisk in Table 1), 1 study that revealed cognitive impairment in some subjects [46, 61] and 7 studies that they did not think revealed cognitive impairment in any subjects [32, 33, 4850, 58, 66]. None of the original authors of the 20 studies concluded that all subjects with MTBIs were cognitively impaired. Some of these studies conducted numerous statistical comparisons and identified only one or two significantly different test scores [28, 40, 41, 64]. One study that McInnes et al [1] reported all subjects had cognitive impairment actually found no statistically significant differences between the MTBI and control group at the 12-month follow-up [55], and another study cited by McInnes et al [1] as showing evidence of cognitive impairment did not actually present, analyze, or interpret any cognitive test scores [47]. Only four studies [28, 31, 32, 61] used some sort of methodology in which individual subjects were classified as having cognitive impairment. One study enrolled 69 patients with MTBIs but only 16 underwent neuropsychological testing at one year following injury [28]. In this study, the MTBI group had significantly lower scores on only 2 of 23 test scores. The definition of cognitive impairment in this subgroup tested one year following injury was having at least one score that was 1.5 SDs below the normative mean. In the MTBI group, 69% had at least one low score. However, 44% of the control group also had at least one low score.

McInnes et al. [1] identified 8 studies, at greater than one year post-injury time period, that they thought revealed all subjects to have cognitive impairment [4042, 65, 6769] (demarcated with an asterisk in Table 1), 1 study that revealed cognitive impairment in some subjects [29] and 1 study that they did not think revealed cognitive impairment [32]. Several studies conducted numerous statistical tests and reported only one or two significant findings (e.g., [41, 6769]). Only three studies [29, 32, 65] used a methodology in which individual subjects were classified as having cognitive impairment. None of the original authors of the 10 studies concluded that all subjects with MTBIs were cognitively impaired.

Discussion

Low neuropsychological test scores may or may not reflect acquired cognitive impairment

When inferring the cause of low neuropsychological test scores, it is important to appreciate that a person might obtain a low score due to situational factors, such as a lapse of attention, temporary distraction, not fully understanding the instructions, or low enthusiasm or motivation for testing. Moreover, a substantial percentage of healthy people with no prior brain injuries will obtain one or more low test scores when administered a battery of cognitive tests [7081]. Researchers repeatedly have shown that it is very common for children [82], adults [76, 83], and older adults [84], with no known clinical conditions that might affect cognition, to obtain at least one low score when a battery of tests measuring multiple cognitive domains is administered [81]. As the number of test scores increases, the probability of a healthy person obtaining one or more low scores increases [79, 85]. The probability of obtaining a low score varies based on the a priori cutoff for defining a low score. For example, some clinicians and researchers define a low score as greater than 1 standard deviation below the mean, 1.5 standard deviations below the mean, or 2 standard deviations below the mean. Obtaining at least one low test score is also common in healthy people who are administered several tests within a cognitive domain, such as working memory [83, 85], learning and memory [77, 78, 84], speed of processing [83, 85], and executive functioning [86, 87]. Using one study from this review as an example, Rieger et al. [23] classified patients based on whether or not they had a single below average score (i.e., one cognitive test score < 30th percentile). They reported that 96% of the MTBI group met this threshold, but so did 85% of their orthopedic control patients.

Demographic and personal characteristics also are associated with the probability of obtaining low cognitive test scores. African Americans and Hispanics, on average, obtain more low scores than Caucasians [8893]. Level of education is associated with test performance; those with terminal high school diplomas obtain more low scores than those with university degrees [94]. Moreover, intelligence is correlated with neuropsychological test performance, so those with below average intelligence will obtain more low scores than those with average intelligence [78, 81, 9499]. Therefore, low neuropsychological test scores may or may not reflect cognitive impairment following MTBI in individual cases. Per Tables 3–6 in the McInnes et al. review [1], 26.7% (n = 12/45) of the studies attempted to match MTBI patients to controls based on socioeconomic status, 57.8% (n = 26/45) matched for education, and 11.1% (n = 5/45) matched for race. Based on our review of these studies, fewer than half assessed intellectual functioning (see Table 1; n = 21/44 studies; 47.7%). Further, many of the studies that measured intelligence used it as an outcome variable that they thought may have been affected by MTBI. Most of these studies did not match for it between groups, control for it in statistical analyses, or discuss it as a potential confound when interpreting their results [e.g., [65]]. Current mental health problems, such as depression or anxiety, can influence cognitive test scores in patients without a MTBI [100] and in patients following a MTBI [101]. Of the studies in this review, 47.7% (n = 21/44) assessed for emotional symptoms (see Table 1), with very few of these studies accounting for the effect of emotional symptoms in their analyses or their interpretation of cognitive test results.

Conclusions

Cognitive impairment can occur following a TBI of any severity. Even very mild TBIs at least temporarily impact cognition [102]. The risk of persistent or permanent cognitive impairment increases in association with the severity of the brain injury [12, 14, 103106]. There is a considerable risk for long-term cognitive deficits after a moderate or severe TBI [14, 103, 107], though the type and severity of residual cognitive deficits is variable. Following a MTBI, cognitive impairment, as measured by neuropsychological tests, is likely to improve and resolve in the initial days, weeks, or months [2, 12]. Patients with structural abnormalities on computed tomography or magnetic resonance imaging, referred to as having a complicated MTBI, tend to perform somewhat more poorly on neuropsychological tests than patients with uncomplicated MTBIs in the first two months following injury [108112]. However, sustaining a complicated MTBI may not increase the risk of long-term (i.e., >6 months) cognitive deficits [113, 114].

The running header for the scoping review by McInnes and colleagues [1] asserts “A single mTBI chronically impairs cognitive function.” The article has the potential to misinform scientists, clinicians, and the public. Some recently published articles have cited the McInnes scoping review as illustrating a high rate of cognitive impairment following “concussion” or MTBI [115118]. Clinicians who review and accept the findings of McInnes et al. will be misinformed and potentially communicate an inaccurate prognosis to patients with a single MTBI. Some patients may personally misinterpret the literature as suggesting they will suffer long-term cognitive deficits following a single MTBI through their own review of this open access article.

We believe that the review by McInnes et al., especially when taken together with the aggregated literature over the past 50 years, does not support the conclusion that approximately half of individuals who sustain a single mild traumatic brain injury (MTBI) experience long-term cognitive impairment. Their scoping review included quantitative analyses based on flawed methodology. Moreover, they did not assess the quality of included studies or exclude studies with a high risk of bias. We re-reviewed the articles they identified and found that the articles themselves do not support their conclusions. Their scoping review reached conclusions that are discrepant from several prior systematic reviews involving meta-analysis [215], which consistently reached the conclusion that the impact of MTBI on neuropsychological performance becomes undetectable at the group-level by three months post injury. These prior systematic reviews do not provide an estimate of the incidence of chronic cognitive impairment following MTBI (i.e., risk of long-term deficits in an individual patient), but suggest that it is low [2].


Zdroje

1. McInnes K, Friesen CL, MacKenzie DE, Westwood DA, Boe SG. Mild Traumatic Brain Injury (mTBI) and chronic cognitive impairment: A scoping review. PLoS One. 2017;12(4):e0174847. doi: 10.1371/journal.pone.0174847 28399158; PubMed Central PMCID: PMC5388340.

2. Rohling ML, Binder LM, Demakis GJ, Larrabee GJ, Ploetz DM, Langhinrichsen-Rohling J. A meta-analysis of neuropsychological outcome after mild traumatic brain injury: re-analyses and reconsiderations of Binder et al. (1997), Frencham et al. (2005), and Pertab et al. (2009). The Clinical Neuropsychologist. 2011;25(4):608–23. Epub 2011/04/23. doi: 10.1080/13854046.2011.565076 21512956.

3. Belanger HG, Spiegel E, Vanderploeg RD. Neuropsychological performance following a history of multiple self-reported concussions: A meta-analysis. J Int Neuropsychol Soc. 2010;16(2):262–7. doi: 10.1017/S1355617709991287 20003581.

4. Belanger HG, Curtiss G, Demery JA, Lebowitz BK, Vanderploeg RD. Factors moderating neuropsychological outcomes following mild traumatic brain injury: a meta-analysis. J Int Neuropsychol Soc. 2005;11(3):215–27. doi: 10.1017/S1355617705050277 15892898.

5. Belanger HG, Vanderploeg RD. The neuropsychological impact of sports-related concussion: A meta-analysis. Journal of the International Neuropsychological Society. 2005;11(4):345–57. 16209414

6. Binder LM, Rohling ML, Larrabee J. A review of mild head trauma. Part I: Meta-analytic review of neuropsychological studies. J Clin Exp Neuropsychol. 1997;19(3):421–31. doi: 10.1080/01688639708403870 9268816.

7. Broglio SP, Puetz TW. The effect of sport concussion on neurocognitive function, self-report symptoms and postural control: a meta-analysis. Sports Med. 2008;38(1):53–67. doi: 10.2165/00007256-200838010-00005 18081367.

8. Dougan BK, Horswill MS, Geffen GM. Athletes' age, sex, and years of education moderate the acute neuropsychological impact of sports-related concussion: a meta-analysis. J Int Neuropsychol Soc. 2014;20(1):64–80. Epub 2013/02/05. doi: 10.1017/S1355617712001464 23375058.

9. Dougan BK, Horswill MS, Geffen GM. Do injury characteristics predict the severity of acute neuropsychological deficits following sports-related concussion? A meta-analysis. J Int Neuropsychol Soc. 2014;20(1):81–7. doi: 10.1017/S1355617713001288 24331116.

10. Frencham KA, Fox AM, Maybery MT. Neuropsychological studies of mild traumatic brain injury: a meta-analytic review of research since 1995. Journal of Clinical and Experimental Neuropsychology. 2005;27(3):334–51. Epub 2005/06/23. doi: 10.1080/13803390490520328 15969356.

11. Karr JE, Areshenkoff CN, Duggan EC, Garcia-Barrera MA. Blast-related mild traumatic brain injury: a Bayesian random-effects meta-analysis on the cognitive outcomes of concussion among military personnel. Neuropsychol Rev. 2014;24(4):428–44. doi: 10.1007/s11065-014-9271-8 25253505.

12. Karr JE, Areshenkoff CN, Garcia-Barrera MA. The neuropsychological outcomes of concussion: a systematic review of meta-analyses on the cognitive sequelae of mild traumatic brain injury. Neuropsychology. 2014;28(3):321–36. Epub 2013/11/14. doi: 10.1037/neu0000037 24219611.

13. Pertab JL, James KM, Bigler ED. Limitations of mild traumatic brain injury meta-analyses. Brain Injury. 2009;23(6):498–508. Epub 2009/06/02. doi: 10.1080/02699050902927984 19484623.

14. Schretlen DJ, Shapiro AM. A quantitative review of the effects of traumatic brain injury on cognitive functioning. Int Rev Psychiatry. 2003;15(4):341–9. doi: 10.1080/09540260310001606728 15276955.

15. Zakzanis KK, Leach L, Kaplan E. Mild traumatic brain injury. In: Zakzanis KK, Leach L, Kaplan E, editors. Neuropsychological differential diagnosis Lisse, Netherlands: Swets & Zeitlinger; 1999. p. 163–71.

16. Pham MT, Rajic A, Greig JD, Sargeant JM, Papadopoulos A, McEwen SA. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synth Methods. 2014;5(4):371–85. doi: 10.1002/jrsm.1123 26052958; PubMed Central PMCID: PMC4491356.

17. Colquhoun HL, Levac D, O'Brien KK, Straus S, Tricco AC, Perrier L, et al. Scoping reviews: time for clarity in definition, methods, and reporting. J Clin Epidemiol. 2014;67(12):1291–4. doi: 10.1016/j.jclinepi.2014.03.013 25034198.

18. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. International journal of social research methodology. 2005;8(1):19–32.

19. Peters MD, Godfrey CM, Khalil H, McInerney P, Parker D, Soares CB. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc. 2015;13(3):141–6. doi: 10.1097/XEB.0000000000000050 26134548.

20. Levac D, Colquhoun H, O'Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010;5:69. doi: 10.1186/1748-5908-5-69 20854677; PubMed Central PMCID: PMC2954944.

21. Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008. doi: 10.1136/bmj.j4008 28935701; PubMed Central PMCID: PMC5833365 at http://www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.

22. Su SH, Xu W, Li M, Zhang L, Wu YF, Yu F, et al. Elevated C-reactive protein levels may be a predictor of persistent unfavourable symptoms in patients with mild traumatic brain injury: a preliminary study. Brain Behav Immun. 2014;38:111–7. doi: 10.1016/j.bbi.2014.01.009 24456846.

23. Rieger BP, Lewandowski LJ, Callahan JM, Spenceley L, Truckenmiller A, Gathje R, et al. A prospective study of symptoms and neurocognitive outcomes in youth with concussion vs orthopaedic injuries. Brain Inj. 2013;27(2):169–78. doi: 10.3109/02699052.2012.729290 23384214.

24. de Boussard CN, Lundin A, Karlstedt D, Edman G, Bartfai A, Borg J. S100 and cognitive impairment after mild traumatic brain injury. J Rehabil Med. 2005;37(1):53–7. Epub 2005/03/25. AL2LTNRXDRBN7LAP [pii] doi: 10.1080/16501970410015587 15788333.

25. Wong MN, Murdoch B, Whelan B-M. Language disorders subsequent to mild traumatic brain injury (MTBI): Evidence from four cases. Aphasiology. 2010;24(10):1155–69. doi: 10.1080/02687030903168212

26. Miles L, Grossman RI, Johnson G, Babb JS, Diller L, Inglese M. Short-term DTI predictors of cognitive dysfunction in mild traumatic brain injury. Brain Injury. 2008;22(2):115–22. doi: 10.1080/02699050801888816 18240040.

27. Muller K, Ingebrigtsen T, Wilsgaard T, Wikran G, Fagerheim T, Romner B, et al. Prediction of time trends in recovery of cognitive function after mild head injury. Neurosurgery. 2009;64(4):698–704; discussion doi: 10.1227/01.NEU.0000340978.42892.78 19349827.

28. Stalnacke BM, Elgh E, Sojka P. One-year follow-up of mild traumatic brain injury: Cognition, disability and life satisfaction of patients seeking consultation. Journal of Rehabilitation Medicine. 2007;39(5):405–11. ISI:000246962400011. doi: 10.2340/16501977-0057 17549333

29. Konrad C, Geburek AJ, Rist F, Blumenroth H, Fischer B, Husstedt I, et al. Long-term cognitive and emotional consequences of mild traumatic brain injury. Psychol Med. 2011;41(6):1197–211. Epub 2010/09/24. doi: 10.1017/S0033291710001728 20860865.

30. Bohnen N, Twijnstra A, Jolles J. Persistence of postconcussional symptoms in uncomplicated, mildly head-injured patients: A prospective cohort study. Neuropsychiatry, Neuropsychology, and Behavioral Neurology. 1993;6(3):193–200.

31. Kashluba S, Hanks RA, Casey JE, Millis SR. Neuropsychologic and functional outcome after complicated mild traumatic brain injury. Archives of Physical Medicine and Rehabilitation. 2008;89(5):904–11. Epub 2008/05/03. doi: 10.1016/j.apmr.2007.12.029 18452740.

32. Jaffe KM, Polissar NL, Fay GC, Liao S. Recovery trends over three years following pediatric traumatic brain injury. Arch Phys Med Rehabil. 1995;76(1):17–26. 7811169.

33. Levin HS, Fletcher JM, Kusnerik L, Kufera JA, Lilly MA, Duffy FF, et al. Semantic memory following pediatric head injury: relationship to age, severity of injury, and MRI. Cortex. 1996;32(3):461–78. 8886522.

34. Phillipou A, Douglas J, Krieser D, Ayton L, Abel L. Changes in saccadic eye movement and memory function after mild closed head injury in children. Dev Med Child Neurol. 2014;56(4):337–45. doi: 10.1111/dmcn.12345 24350895.

35. Barrow IM, Collins JN, Britt LD. The influence of an auditory distraction on rapid naming after a mild traumatic brain injury: a longitudinal study. J Trauma. 2006;61(5):1142–9. doi: 10.1097/01.ta.0000241238.70269.c1 17099520.

36. Smart CM, Karr JE, Areshenkoff CN, Rabin LA, Hudon C, Gates N, et al. Non-Pharmacologic Interventions for Older Adults with Subjective Cognitive Decline: Systematic Review, Meta-Analysis, and Preliminary Recommendations. Neuropsychol Rev. 2017. doi: 10.1007/s11065-017-9342-8 28271346.

37. Iverson GL, Gardner AJ, Terry DP, Ponsford JL, Sills AK, Broshek DK, et al. Predictors of clinical recovery from concussion: a systematic review. Br J Sports Med. 2017;51(12):941–8. doi: 10.1136/bjsports-2017-097729 28566342.

38. Tay SY, Ang BT, Lau XY, Meyyappan A, Collinson SL. Chronic impairment of prospective memory after mild traumatic brain injury. J Neurotrauma. 2010;27(1):77–83. doi: 10.1089/neu.2009.1074 19698071.

39. Rotarescu V, Ciurea AV. Quality of life in children after mild head injury. J Med Life. 2008;1(3):307–22. 20108508.

40. Anderson V, Catroppa C, Morse S, Haritou F, Rosenfeld J. Outcome from mild head injury in young children: a prospective study. J Clin Exp Neuropsychol. 2001;23(6):705–17. doi: 10.1076/jcen.23.6.705.1015 11910538.

41. Wrightson P, McGinn V, Gronwall D. Mild head injury in preschool children: evidence that it can be associated with a persisting cognitive defect. J Neurol Neurosurg Psychiatry. 1995;59(4):375–80. doi: 10.1136/jnnp.59.4.375 7561915; PubMed Central PMCID: PMC486072.

42. McCauley SR, Levin HS. Prospective memory in pediatric traumatic brain injury: a preliminary study. Dev Neuropsychol. 2004;25(1–2):5–20. doi: 10.1080/87565641.2004.9651919 14984326.

43. Siman R, Giovannone N, Hanten G, Wilde EA, McCauley SR, Hunter JV, et al. Evidence That the Blood Biomarker SNTF Predicts Brain Imaging Changes and Persistent Cognitive Dysfunction in Mild TBI Patients. Front Neurol. 2013;4:190. doi: 10.3389/fneur.2013.00190 24302918; PubMed Central PMCID: PMC3831148.

44. Kinsella GJ, Olver J, Ong B, Gruen R, Hammersley E. Mild traumatic brain injury in older adults: early cognitive outcome. J Int Neuropsychol Soc. 2014;20(6):663–71. doi: 10.1017/S1355617714000447 24834461.

45. Hanten G, Li X, Ibarra A, Wilde EA, Barnes A, McCauley SR, et al. Updating memory after mild traumatic brain injury and orthopedic injuries. J Neurotrauma. 2013;30(8):618–24. doi: 10.1089/neu.2012.2392 23227898; PubMed Central PMCID: PMC3638547.

46. Babikian T, McArthur D, Asarnow RF. Predictors of 1-month and 1-year neurocognitive functioning from the UCLA longitudinal mild, uncomplicated, pediatric traumatic brain injury study. Journal of the International Neuropsychological Society. 2013;19(2):145–54. Epub 2012/11/20. doi: 10.1017/S135561771200104X 23157821.

47. Romero K, Lobaugh NJ, Black SE, Ehrlich L, Feinstein A. Old wine in new bottles: validating the clinical utility of SPECT in predicting cognitive performance in mild traumatic brain injury. Psychiatry Res. 2015;231(1):15–24. doi: 10.1016/j.pscychresns.2014.11.003 25466236.

48. Waljas M, Iverson GL, Lange RT, Hakulinen U, Dastidar P, Huhtala H, et al. A prospective biopsychosocial study of the persistent post-concussion symptoms following mild traumatic brain injury. J Neurotrauma. 2015;32(8):534–47. doi: 10.1089/neu.2014.3339 25363626.

49. Zhou Y, Kierans A, Kenul D, Ge Y, Rath J, Reaume J, et al. Mild traumatic brain injury: longitudinal regional brain volume changes. Radiology. 2013;267(3):880–90. doi: 10.1148/radiol.13122542 23481161; PubMed Central PMCID: PMC3662902.

50. Croall ID, Cowie CJ, He J, Peel A, Wood J, Aribisala BS, et al. White matter correlates of cognitive dysfunction after mild traumatic brain injury. Neurology. 2014;83(6):494–501. doi: 10.1212/WNL.0000000000000666 25031282; PubMed Central PMCID: PMC4142001.

51. Kwok FY, Lee TM, Leung CH, Poon WS. Changes of cognitive functioning following mild traumatic brain injury over a 3-month period. Brain Inj. 2008;22(10):740–51. doi: 10.1080/02699050802336989 18787983.

52. Ponsford J, Cameron P, Fitzgerald M, Grant M, Mikocka-Walus A. Long-term outcomes after uncomplicated mild traumatic brain injury: a comparison with trauma controls. Journal of Neurotrauma. 2011;28(6):937–46. Epub 2011/03/18. doi: 10.1089/neu.2010.1516 21410321.

53. Pare N, Rabin LA, Fogel J, Pepin M. Mild traumatic brain injury and its sequelae: characterisation of divided attention deficits. Neuropsychol Rehabil. 2009;19(1):110–37. doi: 10.1080/09602010802106486 18609010.

54. Marsh NV, Smith MD. Post-concussion syndrome and the coping hypothesis. Brain Inj. 1995;9(6):553–62. 7581351.

55. Heitger MH, Jones RD, Dalrymple-Alford JC, Frampton CM, Ardagh MW, Anderson TJ. Motor deficits and recovery during the first year following mild closed head injury. Brain Inj. 2006;20(8):807–24. doi: 10.1080/02699050600676354 17060148.

56. Ponsford J, Willmott C, Rothwell A, Cameron P, Ayton G, Nelms R, et al. Cognitive and behavioral outcome following mild traumatic head injury in children. Journal of Head Trauma Rehabilitation. 1999;14(4):360–72. 10407209.

57. Ponsford J, Willmott C, Rothwell A, Cameron P, Kelly AM, Nelms R, et al. Factors influencing outcome following mild traumatic brain injury in adults. Journal of the International Neuropsychological Society. 2000;6(5):568–79. 10932476.

58. Maillard-Wermelinger A, Yeates KO, Gerry Taylor H, Rusin J, Bangert B, Dietrich A, et al. Mild traumatic brain injury and executive functions in school-aged children. Dev Neurorehabil. 2009;12(5):330–41. doi: 10.3109/17518420903087251 20477562; PubMed Central PMCID: PMC3013371.

59. Xu Z, Lv XA, Wang JW, Chen ZP, Qiu HS. Predictive value of early decreased plasma ghrelin level for three-month cognitive deterioration in patients with mild traumatic brain injury. Peptides. 2014;54:180–5. doi: 10.1016/j.peptides.2014.01.021 24508379.

60. Ellemberg D, Leclerc S, Couture S, Daigle C. Prolonged neuropsychological impairments following a first concussion in female university soccer athletes. Clin J Sport Med. 2007;17(5):369–74. doi: 10.1097/JSM.0b013e31814c3e3e 17873549.

61. Babikian T, Satz P, Zaucha K, Light R, Lewis RS, Asarnow RF. The UCLA longitudinal study of neurocognitive outcomes following mild pediatric traumatic brain injury. J Int Neuropsychol Soc. 2011;17(5):886–95. doi: 10.1017/S1355617711000907 21813031; PubMed Central PMCID: PMC4579245.

62. Catale C, Marique P, Closset A, Meulemans T. Attentional and executive functioning following mild traumatic brain injury in children using the Test for Attentional Performance (TAP) battery. J Clin Exp Neuropsychol. 2009;31(3):331–8. doi: 10.1080/13803390802134616 18608644.

63. Lee H, Wintermark M, Gean AD, Ghajar J, Manley GT, Mukherjee P. Focal lesions in acute mild traumatic brain injury and neurocognitive outcome: CT versus 3T MRI. J Neurotrauma. 2008;25(9):1049–56. doi: 10.1089/neu.2008.0566 18707244.

64. Polissar NL, Fay GC, Jaffe KM, Liao S, Martin KM, Shurtleff HA, et al. Mild pediatric traumatic brain injury: adjusting significance levels for multiple comparisons. Brain Inj. 1994;8(3):249–63. 8004083.

65. Chadwick O, Rutter M, Brown G, Shaffer D, Traub MU. A prospective study of children with head injuries: II. Cognitive sequelae. Psychol Med. 1981;11(1):49–61. 7208746.

66. Dikmen S, Machamer J, Temkin N. Mild head injury: facts and artifacts. Journal of Clinical and Experimental Neuropsychology. 2001;23(6):729–38. doi: 10.1076/jcen.23.6.729.1019 11910540.

67. Mangels JA, Craik FI, Levine B, Schwartz ML, Stuss DT. Effects of divided attention on episodic memory in chronic traumatic brain injury: a function of severity and strategy. Neuropsychologia. 2002;40(13):2369–85. 12417466.

68. Geary EK, Kraus MF, Pliskin NH, Little DM. Verbal learning differences in chronic mild traumatic brain injury. Journal of the International Neuropsychological Society. 2010;16(3):506–16. Epub 2010/03/02. doi: 10.1017/S135561771000010X 20188015.

69. Vanderploeg RD, Curtiss G, Belanger HG. Long-term neuropsychological outcomes following mild traumatic brain injury. Journal of the International Neuropsychological Society. 2005;11(3):228–36. ISI:000229005900002. doi: 10.1017/S1355617705050289 15892899

70. Axelrod BN, Wall JR. Expectancy of impaired neuropsychological test scores in a non-clinical sample. Int J Neurosci. 2007;117(11):1591–602. doi: 10.1080/00207450600941189 17917928.

71. Heaton RK, Grant I, Matthews CG. Comprehensive norms for an extended Halstead-Reitan Battery: Demographic corrections, research findings, and clinical applications. Odessa, FL: Psychological Assessment Resources, Inc.; 1991.

72. Heaton RK, Miller SW, Taylor MJ, Grant I. Revised comprehensive norms for an expanded Halstead-Reitan Battery: Demographically adjusted neuropsychological norms for African American and Caucasian adults professional manual. Lutz, FL: Psychological Assessment Resources; 2004.

73. Ingraham LJ, Aiken CB. An empirical approach to determining criteria for abnormality in test batteries with multiple measures. Neuropsychology 1996;10:120–4.

74. Iverson GL, Brooks BL, Holdnack JA. Misdiagnosis of cognitive impairment in forensic neuropsychology. In: Heilbronner RL, editor. Neuropsychology in the courtroom: Expert analysis of reports and testimony. New York: Guilford Press; 2008. p. 243–66.

75. Palmer BW, Boone KB, Lesser IM, Wohl MA. Base rates of "impaired" neuropsychological test performance among healthy older adults. Arch Clin Neuropsychol. 1998;13(6):503–11. 14590634.

76. Schretlen DJ, Testa SM, Winicki JM, Pearlson GD, Gordon B. Frequency and bases of abnormal performance by healthy adults on neuropsychological testing. Journal of the International Neuropsychological Society. 2008;14(3):436–45. doi: 10.1017/S1355617708080387 18419842

77. Brooks BL, Iverson GL, White T. Substantial risk of "Accidental MCI" in healthy older adults: Base rates of low memory scores in neuropsychological assessment. Journal of the International Neuropsychological Society. 2007;13(3):490–500. doi: 10.1017/S1355617707070531 17445298

78. Brooks BL, Iverson GL, Holdnack JA, Feldman HH. Potential for misclassification of mild cognitive impairment: a study of memory scores on the Wechsler Memory Scale-III in healthy older adults. J Int Neuropsychol Soc. 2008;14(3):463–78. doi: 10.1017/S1355617708080521 18419845.

79. Crawford JR, Garthwaite PH, Gault CB. Estimating the percentage of the population with abnormally low scores (or abnormally large score differences) on standardized neuropsychological test batteries: a generic method with applications. Neuropsychology. 2007;21(4):419–30. Test Software http://homepages.abdn.ac.uk/j.crawford/pages/dept/PercentAbnormKtests.htm. doi: 10.1037/0894-4105.21.4.419 17605575.

80. Iverson GL, Brooks BL, White T, Stern RA. Neuropsychological Assessment Battery (NAB): Introduction and advanced interpretation. In: Horton AM Jr., Wedding D, editors. The Neuropsychology Handbook. 3rd ed. New York: Springer Publishing Inc; 2008. p. 279–343.

81. Binder LM, Iverson GL, Brooks BL. To err is human: “Abnormal” neuropsychological scores and variability are common in healthy adults. Archives of Clinical Neuropsychology. 2009;24:31–46. doi: 10.1093/arclin/acn001 19395355

82. Brooks BL, Sherman EM, Iverson GL. Healthy children get low scores too: prevalence of low scores on the NEPSY-II in preschoolers, children, and adolescents. Archives of Clinical Neuropsychology. 2010;25(3):182–90. Epub 2010/02/25. doi: 10.1093/arclin/acq005 20179013.

83. Iverson GL, Brooks BL, Holdnack JA. Evidence-based neuropsychological assessment following work-related injury. In: Bush SS, Iverson GL, editors. Neuropsychological assessment of work-related injuries. New York: Guilford Press; 2012. p. 360–400.

84. Brooks BL, Iverson GL, White T. Advanced interpretation of the Neuropsychological Assessment Battery (NAB) with older adults: Base rate analyses, discrepancy scores, and interpreting change. Archives of Clinical Neuropsychology. 2009;24(7):647–57. doi: 10.1093/arclin/acp061 19749192

85. Brooks BL, Iverson GL, Holdnack JA. Understanding and using multivariate base rates with the WAIS-IV/WMS-IV. In: Holdnack JA, Drozdick LW, Weiss LG, Iverson GL, editors. WAIS-IV/WMS-IV/ACS: Advanced clinical interpretation. San Diego, CA: Elsevier Science; 2013. p. 75–102.

86. Brooks BL, Iverson GL, Lanting SC, Horton AM, Reynolds CR. Improving test interpretation for detecting executive dysfunction in adults and older adults: prevalence of low scores on the test of verbal conceptualization and fluency. Appl Neuropsychol Adult. 2012;19(1):61–70. Epub 2012/03/06. doi: 10.1080/09084282.2012.651951 22385381.

87. Crawford JR, Garthwaite PH, Sutherland D, Borland N. Some supplementary methods for the analysis of the Delis-Kaplan Executive Function System. Psychol Assess. 2011;23(4):888–98. doi: 10.1037/a0023712 21574720.

88. Manly JJ, Echemendia RJ. Race-specific norms: using the model of hypertension to understand issues of race, culture, and education in neuropsychology. Arch Clin Neuropsychol. 2007;22(3):319–25. doi: 10.1016/j.acn.2007.01.006 17350797.

89. Brickman AM, Cabo R, Manly JJ. Ethical issues in cross-cultural neuropsychology. Appl Neuropsychol. 2006;13(2):91–100. doi: 10.1207/s15324826an1302_4 17009882.

90. Ardila A. Directions of research in cross-cultural neuropsychology. J Clin Exp Neuropsychol. 1995;17(1):143–50. doi: 10.1080/13803399508406589 7608296.

91. O'Bryant SE, O'Jile JR, McCaffrey RJ. Reporting of demographic variables in neuropsychological research: trends in the current literature. Clin Neuropsychol. 2004;18(2):229–33. doi: 10.1080/13854040490501439 15587670.

92. Patton DE, Duff K, Schoenberg MR, Mold J, Scott JG, Adams RL. Performance of cognitively normal African Americans on the RBANS in community dwelling older adults. Clin Neuropsychol. 2003;17(4):515–30. doi: 10.1076/clin.17.4.515.27948 15168916.

93. Casaletto KB, Umlauf A, Marquine M, Beaumont JL, Mungas D, Gershon R, et al. Demographically Corrected Normative Standards for the Spanish Language Version of the NIH Toolbox Cognition Battery. J Int Neuropsychol Soc. 2016;22(3):364–74. doi: 10.1017/S135561771500137X 26817924.

94. Brooks BL, Holdnack JA, Iverson GL. Advanced clinical interpretation of the WAIS-IV and WMS-IV: prevalence of low scores varies by level of intelligence and years of education. Assessment. 2011;18(2):156–67. Epub 2010/10/16. doi: 10.1177/1073191110385316 20947705.

95. Horton AM Jr. Above-average intelligence and neuropsychological test score performance. Int J Neurosci. 1999;99(1–4):221–31. 10495218.

96. Warner MH, Ernst J, Townes BD, Peel J, Preston M. Relationships between IQ and neuropsychological measures in neuropsychiatric populations: within-laboratory and cross-cultural replications using WAIS and WAIS-R. J Clin Exp Neuropsychol. 1987;9(5):545–62. doi: 10.1080/01688638708410768 3667899.

97. Tremont G, Hoffman RG, Scott JG, Adams RL. Effect of intellectual level on neuropsychological test performance: A response to Dodrill (1997). The Clinical Neuropsychologist. 1998;12:560–7.

98. Steinberg BA, Bieliauskas LA, Smith GE, Ivnik RJ, Malec JF. Mayo's Older Americans Normative Studies: Age- and IQ-Adjusted Norms for the Auditory Verbal Learning Test and the Visual Spatial Learning Test. Clin Neuropsychol. 2005;19(3–4):464–523. doi: 10.1080/13854040590945193 16120537.

99. Steinberg BA, Bieliauskas LA, Smith GE, Ivnik RJ. Mayo's Older Americans Normative Studies: Age- and IQ-Adjusted Norms for the Trail-Making Test, the Stroop Test, and MAE Controlled Oral Word Association Test. Clin Neuropsychol. 2005;19(3–4):329–77. doi: 10.1080/13854040590945210 16120535.

100. McClintock SM, Husain MM, Greer TL, Cullum CM. Association between depression severity and neurocognitive function in major depressive disorder: a review and synthesis. Neuropsychology. 2010;24(1):9–34. doi: 10.1037/a0017336 20063944.

101. Terry DP, Iverson GL, Panenka W, Colantonio A, Silverberg ND. Workplace and non-workplace mild traumatic brain injuries in an outpatient clinic sample: A case-control study. PLoS One. 2018;13(6):e0198128. doi: 10.1371/journal.pone.0198128 29856799; PubMed Central PMCID: PMC5983513 individuals who have sustained mild TBIs. He acknowledges unrestricted philanthropic support from the Mooney-Reed Charitable Foundation and ImPACT Applications, Inc. Noah Silverberg has a clinical practice in forensic neuropsychology and William Panenka has a clinical practice in forensic neuropsychiatry involving individuals who have sustained mild TBIs. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

102. McCrea M, Iverson GL, McAllister TW, Hammeke TA, Powell MR, Barr WB, et al. An integrated review of recovery after mild traumatic brain injury (MTBI): implications for clinical management. Clin Neuropsychol. 2009;23(8):1368–90. doi: 10.1080/13854040903074652 19882476.

103. Christensen BK, Colella B, Inness E, Hebert D, Monette G, Bayley M, et al. Recovery of cognitive function after traumatic brain injury: a multilevel modeling analysis of Canadian outcomes. Arch Phys Med Rehabil. 2008;89(12 Suppl):S3–15. doi: 10.1016/j.apmr.2008.10.002 19081439.

104. Ruttan L, Martin K, Liu A, Colella B, Green RE. Long-term cognitive outcome in moderate to severe traumatic brain injury: a meta-analysis examining timed and untimed tests at 1 and 4.5 or more years after injury. Arch Phys Med Rehabil. 2008;89(12 Suppl):S69–76. doi: 10.1016/j.apmr.2008.07.007 19081444.

105. Draper K, Ponsford J. Cognitive functioning ten years following traumatic brain injury and rehabilitation. Neuropsychology. 2008;22(5):618–25. doi: 10.1037/0894-4105.22.5.618 18763881.

106. Levin HS, Grossman RG, Rose JE, Teasdale G. Long-term neuropsychological outcome of closed head injury. J Neurosurg. 1979;50(4):412–22. doi: 10.3171/jns.1979.50.4.0412 311378.

107. Millis SR, Rosenthal M, Novack TA, Sherer M, Nick TG, Kreutzer JS, et al. Long-term neuropsychological outcome after traumatic brain injury. J Head Trauma Rehabil. 2001;16(4):343–55. 11461657.

108. Iverson GL. Complicated vs uncomplicated mild traumatic brain injury: acute neuropsychological outcome. Brain Inj. 2006;20(13–14):1335–44. 17378225.

109. Lange RT, Iverson GL, Franzen MD. Neuropsychological functioning following complicated vs. uncomplicated mild traumatic brain injury. Brain Injury. 2009;23(2):83–91. doi: 10.1080/02699050802635281 19191087.

110. de Guise E, Lepage JF, Tinawi S, LeBlanc J, Dagher J, Lamoureux J, et al. Comprehensive clinical picture of patients with complicated vs uncomplicated mild traumatic brain injury. The Clinical Neuropsychologist. 2010;24(7):1113–30. Epub 2010/08/24. doi: 10.1080/13854046.2010.506199 20730678.

111. Lange RT, Brickell TA, French LM, Merritt VC, Bhagwat A, Pancholi S, et al. Neuropsychological outcome from uncomplicated mild, complicated mild, and moderate traumatic brain injury in US military personnel. Archives of Clinical Neuropsychology. 2012;27(5):480–94. Epub 2012/07/07. doi: 10.1093/arclin/acs059 22766317.

112. Panenka WJ, Lange RT, Bouix S, Shewchuk JR, Heran MK, Brubacher JR, et al. Neuropsychological outcome and diffusion tensor imaging in complicated versus uncomplicated mild traumatic brain injury. PLoS One. 2015;10(4):e0122746. doi: 10.1371/journal.pone.0122746 25915776; PubMed Central PMCID: PMC4411162.

113. Yuh EL, Cooper SR, Mukherjee P, Yue JK, Lingsma HF, Gordon WA, et al. Diffusion Tensor Imaging for Outcome Prediction in Mild Traumatic Brain Injury: A TRACK-TBI Study. Journal of Neurotrauma. 2014;31(17):1457–77. Epub 2014/04/20. doi: 10.1089/neu.2013.3171 24742275; PubMed Central PMCID: PMC4144386.

114. Beauchamp MH, Beare R, Ditchfield M, Coleman L, Babl FE, Kean M, et al. Susceptibility weighted imaging and its relationship to outcome after pediatric traumatic brain injury. Cortex. 2013;49(2):591–8. doi: 10.1016/j.cortex.2012.08.015 23062584.

115. Manzanero S, Elkington LJ, Praet S, Lovell G, Waddington G, Highes DC. Post-concussion recovery in children and adolescents: A narrative review. Journal of Concussion. 2017;1:2059700217726874.

116. Bhowmick S, D'Mello V, Ponery N, Abdul-Muneer PM. Neurodegeneration and Sensorimotor Deficits in the Mouse Model of Traumatic Brain Injury. Brain Sci. 2018;8(1). doi: 10.3390/brainsci8010011 29316623; PubMed Central PMCID: PMC5789342.

117. Grandhi R, Tavakoli S, Ortega C, Simmonds MJ. A Review of Chronic Pain and Cognitive, Mood, and Motor Dysfunction Following Mild Traumatic Brain Injury: Complex, Comorbid, and/or Overlapping Conditions? Brain Sci. 2017;7(12). doi: 10.3390/brainsci7120160 29211026; PubMed Central PMCID: PMC5742763.

118. Morse AM, Garner DR. Traumatic Brain Injury, Sleep Disorders, and Psychiatric Disorders: An Underrecognized Relationship. Med Sci (Basel). 2018;6(1). doi: 10.3390/medsci6010015 29462866; PubMed Central PMCID: PMC5872172.


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