SIDELINE ASSESSMENT

The assessment of an injured player is facilitated by the presence of a certified athletic trainer, team physician, or other health care provider at the venue (e.g., field, gymnasium, or rink) where the injury occurred. However, the vast majority of young athletes practice and play in circumstances where trained personnel are not routinely available to make sideline injury assessments, and the responsibility for determining whether to remove an athlete from play falls on coaches, parents, players, and, perhaps, officials. A further impediment to identification is that symptoms may not become apparent for several hours after injury, and one result of this is that a large number of concussions are not identified until 24 hours or more after the injury (Duhaime et al., 2012; McCrory et al., 2013b). The Centers for Disease Control and Prevention (CDC) Heads Up campaign is designed to educate coaches, parents, and athletes about the prevention and recognition of and response to concussions (CDC, 2012a). A central feature of the campaign is the dissemination of information about the signs and symptoms of concussion (see Table 3-1) along with the message that players suspected of having sustained a concussion should be removed from play for the remainder of the day, referred to a health care provider for evaluation, and not permitted to return to play until they have been cleared by a health professional trained in concussion diagnosis and management (CDC, 2012a).

TABLE 3-1

Signs and Symptoms of Concussions Relevant to Sideline Assessment.

The sideline evaluation of a player's symptoms may be complicated by the tendency of athletes to underreport their symptoms (Anderson et al., 2013; Dziemianowicz et al., 2012; McCrea et al., 2004). A 2004 study of high school football players found that 41 percent of subjects reported not wanting to leave the game as their reason for not reporting a possible concussion, and 66 percent said they did not report their symptoms because they did not think their injury was serious enough to warrant medical attention (McCrea et al., 2004).¹ In a 2012 survey of high school football players, a majority indicated that it was “okay” to play with a concussion and said that they would “play through any injury to win a game,” despite being knowledgeable about the symptoms and dangers of concussions (Anderson et al., 2013; see also Coyne, 2013; Kroshus et al., 2013; Register-Mihalik et al., 2013a,c; Torres et al., 2013). In addition, concussion signs and symptoms may develop and evolve over time, particularly within the first hours following injury (Duhaime et al., 2012; McCrory et al., 2013b). The mantra for laypersons faced with a potentially concussed athlete is “when in doubt, sit them out”: If a player has received “a bump, blow, or jolt to the head or body” and exhibits or reports one or more of the signs or symptoms of concussion, the player may have sustained a concussion (CDC, 2012a).

Appropriately trained personnel have a number of tools available for use in the initial assessment of an individual for a possible concussion (see, e.g., Table 3-2; Appendix C). The Standardized Assessment of Concussion (SAC) and the Sport Concussion Assessment Tool (SCAT) 3 or Child SCAT3 were developed for the sideline evaluation of potentially concussed athletes. The Military Acute Concussion Evaluation (MACE) is a screening tool used to assess service members involved in a potentially concussive event. Such tools as well as balance tests (see Table 3-2) may be used either by trained responders as part of an acute sideline or in-field assessment or by health care providers during subsequent clinical evaluation. It is important to note, however, that because of the natural evolution of concussions, not all concussed athletes will be identified at the time of (presumed) injury even when personnel trained in concussion recognition are present (McCrory et al., 2013b). Duhaime and colleagues (2012) found that 50 percent of a sample of collegiate athletes who sustained a diagnosed concussion (with athletic trainers present for all games and practices) did not experience an “immediate or near immediate” onset of symptoms.

TABLE 3-2

Sideline Concussion Screening Tools.

CLINICAL EVALUATION

Concussion Diagnosis

Given the absence of a diagnostic test or biomarker for concussion, the current cornerstone of concussion diagnosis is confirming the presence of a constellation of signs and symptoms after an individual has experienced a hit to the head or body. Symptoms are self-reported by the athlete, often using a symptom scale. Reliance on an athlete's self-report of symptoms as a fundamental part of diagnosing a concussion is complicated by the subjective nature of the assessment and by the possibility of an athlete underreporting the symptoms (Anderson et al., 2013; Dziemianowicz et al., 2012; McCrea et al., 2004). Using multiple evaluation tools, such as symptom scales and checklists, balance testing, and neurocognitive assessments, may increase the sensitivity and specificity of concussion identification (Broglio et al., 2007b; Guskiewicz and Register-Mihalik, 2011; Harmon et al., 2013; Register-Mihalik et al., 2013b), and this is the current preferred method of diagnosing a concussion, although existing evidence is insufficient to determine the best combination of measures (Giza et al., 2013).

Traditional neuroimaging techniques, such as standard computed tomography (CT) and magnetic resonance imaging (MRI) (see Box 3-1), are used to rule out more severe head and brain injuries, such as skull fractures and intracranial hemorrhages, as well as cerebral swelling that would require surgical intervention (Giza et al., 2013; McCrory et al., 2013b; Suskauer and Huisman, 2009). Because of its accessibility in the emergency room, CT is the most commonly used imaging technique for clinical assessment of head trauma (Belanger et al., 2007; Toledo et al., 2012). CT exposes the individual to radiation, which is an important consideration when evaluating youth. The American Academy of Neurology has recently recommended that CT not be used to evaluate suspected sports-related concussion in the absence of signs or symptoms of more serious traumatic brain injury (TBI) (Giza et al., 2013). Although MRIs avoid the use of ionizing radiation, instead using a magnetic field and pulses of radio wave energy to image different types of brain and body tissue, they too are of little diagnostic value for concussions per se, because structural imaging results are normal in concussions that are uncomplicated by skull fracture or hematoma.

BOX 3-1

Imaging Techniques. A number of imaging techniques have evolved for measuring the structure, function, and connectivity of the developing human brain in vivo. The most commonly used techniques, which are briefly described below, vary in invasiveness (i.e., (more...)

Newer imaging techniques (see Box 3-1), such as magnetic resonance spectroscopy, positron emission tomography, single-photon emission computed tomography, functional magnetic resonance imaging, and diffusion tensor imaging—which all can be used to track metabolic, blood flow, and axonal changes—build on animal work and clinical outcome measures in mild traumatic brain injury (mTBI). Although such techniques may be useful in the future for assessing sports-related concussions, at present they have not been validated for clinical use (Cubon et al., 2011; DiFiori and Giza, 2010; Jantzen et al., 2004; Koerte et al., 2012; Lovell et al., 2007; Vagnozzi et al., 2010; Virji-Babul et al., 2013).

Signs and Symptoms

The signs and symptoms of concussion reported within 1 to 7 days post injury (see Table 3-3) typically fall into four categories—physical (somatic), cognitive, emotional (affective), and sleep—and patients will experience one or more symptoms from one or more categories. A study of high school athletes found that female athletes reported more somatic symptoms (drowsiness and sensitivity to noise) while their male counterparts reported more cognitive symptoms (amnesia and confusion/disorientation), although the number of symptoms reported did not differ by sex (Frommer et al., 2011). Kontos and colleagues (2012) have reported a revised factor structure—cognitive-migraine-fatigue, affective, somatic, and sleep. In their study, high school athletes reported lower levels of the sleep symptom factor than did college athletes, and female athletes reported higher levels of the affective symptom factor than did their male counterparts. There were no age or sex differences for the other factors, and the interaction between age and sex was not significant (Kontos et al., 2012). It should be noted that the symptoms reported differently by males and females in the Frommer study fell within a single factor in the structure presented by Kontos and colleagues.

TABLE 3-3

Concussion Symptoms by Category.

Symptom Scales and Checklists

Concussion symptom checklists survey a broad range of symptoms that are considered to be pathognomonic of concussion. Of the approximately 20 different symptom scales commonly used to evaluate concussion, 14 are variations of 6 core scales,² which include symptoms associated with sports-related concussion, although the number of items on each scale varies (Alla et al., 2009; Valovich McLeod and Leach, 2012). A 2009 review of literature pertaining to the psychometric properties of these self-report concussion scales and checklists found that very few of them had been developed systematically or had published psychometric properties (Alla et al., 2009; Valovich McLeod and Leach, 2012). The recent American Academy of Neurology guideline states that “evidence indicates it is likely that [a symptom scale or checklist] will accurately identify concussion in athletes involved in an event during which biomechanical forces were imparted to the head” (Giza et al., 2013, p. 3). The guideline indicates that the sensitivity of such symptom reporting tools ranges from 64 to 89 percent and their specificity ranges from 91 to 100 percent (Giza et al., 2013).

A 2009 literature review of symptom scales used in the pediatric, adolescent, and young adult populations (ages 5 to 22 years) identified one research-based scale and four scales that were in clinical use; psychometric evidence for the scales was assessed for younger children (5 to 12 years) and for adolescents and young adults (13 to 22 years) (Gioia et al., 2009).³ The psychometric evidence relating to symptom scales is stronger for adolescents than for younger children, and there is reasonable evidence to support the validity of the scales, although data on their reliability is limited and additional research is needed (Gioia et al., 2009). A more recent review by Janusz and colleagues (2012) discussed the psychometric properties of these same symptom scales as well as of the Concussion Symptom Inventory (CSI) (Randolph et al., 2009) and the Acute Concussion Evaluation (ACE) (Gioia et al., 2008a).

Randolph and colleagues (2009) analyzed a large set of data from three separate projects to develop the 12-item CSI, which is the first empirically derived symptom scale for concussion identification and short-term serial use following a sports-related concussion. The CSI was shown to be as effective as longer symptom inventories, such as the Graded Symptom Checklist, at recognizing concussions.

The characteristics of the instruments and their psychometric properties are discussed in Appendix C and summarized in Table 3-4.

TABLE 3-4

Measures of Post-Concussion Symptomatology.

The Health Behavior Inventory and Post-Concussion Symptom Inventory (PCSI) are the only measures that are well studied in children under the age of 12 and have the advantage of having reports from parents and, in the case of the PCSI, teachers. Studies looking at the concordance of symptoms reported by 8- to 15-year-old patients and their parents found that mean symptom ratings tended to be higher for children as compared to their parents (Ayr et al., 2009; Hajek et al., 2011). Gioia has also found that the self-report of symptoms differs between athletes and their parents, with parent reports demonstrating better diagnostic utility than youth self-report (Gioia, 2013).

NEUROPSYCHOLOGICAL TESTING

Introduction to Neuropsychological Testing

Neuropsychology is the study of brain-behavior relationships, that is, the ways in which specific neural (brain) structure and activity are reflected in cognitive and physical behavior. The terms “neuropsychological” and “cognitive” are often used interchangeably (as in neuropsychological testing, cognitive testing, and neurocognitive testing). For the purposes of this document, the terms can be understood as equivalent.

Tests such as Trail Making, Paced Auditory Serial Attention Test, Digit Symbol Substitution, and Digit Span have long been used in documenting cognitive deficits in TBI. The earlier neuropsychological literature on TBI has documented several specific areas of typical deficit, with processing speed, attention and memory typically showing the most significant deficits. Sports concussions may have the following effects:

• Reduced planning and ability to switch mental set (Barth et al., 1983, 1989, 2000; Rimel et al., 1982)
• Impaired memory and learning (Gronwall and Wrightson, 1981; Guskiewicz et al., 2001; Lovell et al., 2003)
• Reduced attention and ability to process information (Maddocks et al., 1995)
• Slowed reaction times and increased variability in response (Collins et al., 2003b; Makdissi et al., 2001)

Although neuropsychological testing is recognized as a powerful tool for understanding the cognitive effects of brain injury, it has inherent limitations and factors that affect the resulting scores and interpretations.

In 2001, Grindel and colleagues reviewed the existing literature on sports concussions and commented on several important issues that needed to be addressed by the field (Grindel et al., 2001). These included the availability of baseline testing, the validity of the test battery, problems involving repeated testing, interpretation of the test, the costs of testing, the presence of severe or prolonged symptoms, the presence of multiple concussions, age, gender, and perhaps the athlete's level of play. Many of these issues have been addressed as newer tools and improved analyses have been published. Baseline testing has become prevalent with the advent of Web-based computerized tests; the validity of the tests themselves has been established, although confounding factors such as symptom load, test administration environment, and comorbid conditions continue to plague the field. Reliable change metrics have improved the problems with repeat testing, and the effects of multiple concussions have been recognized and often used as a covariate in group studies.

Randolph and colleagues (2005) reviewed the state of neuropsychological testing in sports-related concussion management and concluded that the (then) existing tests did not meet necessary standards for use. Issues of reliability and validity as well as poor psychometric controls were felt to render testing useless for this specified purpose. They opined that athletic trainers and sports medicine professionals would do just as well using standardized graded checklists.

In 2010, Comper and colleagues published a systematic review of the methodological features of research in sports concussion, focusing on studies that used neuropsychological tests. They concluded that the methodological quality of studies were highly variable (Comper et al., 2010). In a separate paper, they noted that no prospective studies using control groups had been done to validate the use of neuropsychological tests (Hutchison et al., 2011). Prospective studies with controls are difficult to complete, but there are now some studies with control groups and within-subjects designs that use baseline test performance and the amount of change relative to expectation as dependent variables.

In spite of these concerns, the use of neuropsychological testing in sports has proliferated, with ever more computerized batteries coming on the market, and professional, college, high school, and youth sports teams implementing some form of testing.

Factors Affecting Neuropsychological Testing

The influence of intrinsic and extrinsic factors on neuropsychological test performance has long been studied, and clinicians attempt to minimize the effects of these factors by using standardized procedures and testing environments. McCrory and colleagues (2005) listed a number of individual factors (e.g., genetics, general cognitive level of functioning, gender, ethnicity, mood) and methodological factors (e.g., testing environment, practice and learning effects, administrative expertise) that may influence test outcomes (see Figure 3-1). Other individual factors that may affect test outcomes include learning disabilities, attention deficit hyperactivity disorder, and color blindness. Symptom load as a state factor should also be considered as a factor that affects test performance (McCrory et al., 2005). Score interpretation depends on reliable administration and the proper consideration of all of these factors, some of which are reduced with computerized testing (McCrory et al., 2005).

FIGURE 3-1

Factors that impact the results of neuropsychological tests. SOURCE: McCrory et al., 2005, p. i61. Reproduced with permission from BMJ Group Ltd.

Using trained test administrators and testing in appropriate environments are fairly obvious requirements, but there are no data on the actual training or testing environments that are currently in use. Group testing, the way in which most baseline assessments are administered, appears to systematically lower scores compared to individualized administration (Moser et al., 2011).

Age and sex are well-known contributors to score differences in all educational and psychological tests. Test standardization requires validity studies that determine these differences and allow the presentation of separate norms (see AERA et al., 1999). Most published tests, including Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), CogSport, Concussion Resolution Index (CRI), and Automated Neuropsychological Assessment Metrics, provide age and gender normative standards or references. Unless tests have been shown to be insensitive to gender, they are expected to offer separate scoring parameters.

Higher academic achievement has been linked to higher computerized neuropsychological test scores. One study looked at neuropsychological test scores in more than 300 Division I NCAA schools. Athletes with the highest levels of academic achievement based on the Scholastic Aptitude Test (SAT) had higher scores on the ANAM test battery than did those athletes with lower SAT scores (Brown et al., 2007). Comorbid conditions such as attention deficit hyperactivity disorder, learning disabilities (Collins et al., 1999), and autism also may be reflected in test scores. Some medications can also affect scores, including anti-epileptic drugs and psycho-stimulants (see, e.g., Biederman et al., 2008).

Poor effort is somewhat more difficult to detect and control, but it is a factor that lowers scores. This has been documented in the general TBI literature (Green, 2007; Lange et al., 2010). A major concern in testing for sports-related concussions is the willful lowering of baseline scores in order to establish an easier threshold for “return to baseline” (Pennington, 2013). The ImPACT test has embedded validity indicators to help examiners determine atypically low scores on specific subtests. However, individuals with neurologic or developmental disorders or those who are under acute stress may legitimately score low on these indicators; thus, individual analysis is required before declaring a test invalid. There are also specific tests and profiles within neuropsychological tests that are used to detect poor effort, “malingering,” or suboptimal performance.

Hunt and colleagues (2007) found that 11 percent of their sample of 199 high school athletes exhibited poor effort as indexed by the Dot Counting Test and the Rey 15-Item Test with recognition trial. Statistically significant differences existed between effort groups (p < 0.05) on several of the neuropsychological tests. By comparing a group with unusually low baseline scores versus post-injury scores at 1 week to a group with high baseline scores, Bailey and colleagues (2006) found significantly more improvement from baseline to post injury for athletes who reported “low motivation” on baseline testing. The authors concluded that low motivation exists and that it does affect test scores. However, Erdal (2012) found that it was difficult for athletes to purposely do poorly on the ImPACT test without tripping the validity indicators embedded in the ImPACT test. Nevertheless, the perceived secondary gain of lowering one's baseline test score is a concern when using the baseline-testing paradigm. In the case of large-scale baseline testing sessions, it is particularly difficult to know whether low scores are due to intrinsic factors or poor motivation.

In the clinical pediatric population, sleep debt does not appear to interfere with neuropsychological testing, although it is strongly implicated in poor school performance (see Beebe, 2012, for review). Although sleep does not appear to affect laboratory test performances, one small study indicated that the number of hours of sleep the night before baseline testing was related to higher non-sleep symptom scores (i.e., less sleep was related to higher non-sleep symptom totals; see Maerlender and Alt, 2012).

Mood and anxiety have long been known to affect neuropsychological test performance in clinical patients. Bailey and colleagues (2010) and Maerlender and colleagues (2010) presented data demonstrating that mood and anxiety scores on independent measures were related to specific test score patterns on ImPACT and on a paper-and-pencil neuropsychological battery. The Bailey study administered the Personality Assessment Inventory together with the CRI and found that a significant amount of variance in baseline scores was accounted for by mood and anxiety symptom load. Using the symptom scale that is part of the ImPACT battery, Covassin and colleagues (2012b) found that athletes with high levels of depression reported more concussion-like symptoms and had lower ImPACT test scores on baseline tests.⁴ The ANAM battery has validated a mood scale and demonstrated its relationship to test scores (Johnson et al., 2008). Given the increased use of neuropsychological testing at baseline and post injury, it is important to understand the effect of these factors, and the potential effect of these factors on test results highlights the need for interpretation of the tests by experienced providers. There are several ways in which mood and anxiety can be related to neuropsychological performance in concussed athletes. It could be, for example, that both increased anxiety and decreased performance are the result of the same brain injury, or that the depression and anxiety symptoms are a response to the problems in the cognitive performance, or that depression and anxiety have negatively affected neurocognitive performance. Indeed, there is evidence to support each of these three possibilities (Chen et al., 2007; Pardini et al., 2010). Although most studies of athletes have used older samples and there are no systematic studies in athletes younger than high school age, there is no reason to believe that the state effects of anxiety, mood, or stress would be different in a younger population.

Pain has been shown to affect cognition in some groups of patients. A recent study by Gosselin and colleagues (2012b) compared groups of adolescents with mTBI (n=24, 50 percent of whom had sports-related injuries), non-injured controls (n=16), and athletes with orthopedic injuries (n=29). Levels of pain were the dependent measure and blood oxygen level-dependent activation during working memory task was the outcome. While results were somewhat complicated, the authors interpreted the results as demonstrating that behavioral performance and cerebral function were related to levels of pain.

The validity of neuropsychological tests for interpreting brain-behavior relationships rests on psychometric characteristics, including reliability. The use of the same test multiple times for tracking change or measuring injury (i.e., baseline to post injury) is compromised by several factors, most notably the practice effect of retaking the test. Although multiple forms (using different specific items) can reduce this, the effect of exposure to the procedure (directions, pacing, sequence of tasks) has a greater effect than the likelihood of memorizing specific responses (Heilbronner et al., 2010). To address this issue, several statistical procedures have been developed to account for practice effects, the tendency of scores to “regress to the mean,” and differential pre-injury test scores (for review, see Hinton-Bayre, 2012). The American Academy of Clinical Neuropsychology has issued a position paper that outlines these concerns and discusses the recommended statistical procedures (reliable change indices, regression-based methods) (Bauer et al., 2012; Heilbronner et al., 2010). It recommends that such statistical adjustments be used any time tests are used in a serial fashion.

Neuropsychological Testing and Sports-Related Concussions

Jeffrey Barth and his colleagues are generally credited with originating the use of athletes and teams as a laboratory for studying the nature and outcomes of concussion through sports (the Sports as a Laboratory Assessment Model) and the baseline pre-season testing of athletes with brief neuropsychological batteries for later post-injury comparisons (Barth et al., 1989; Macciocchi et al., 1996). With the growing use of neuropsychological testing in the identification and management of sports-related concussions has come controversy and criticism about the methods and outcomes.

This section considers the following questions concerning neuropsychological assessment in sports-related concussions:

• Can neuropsychological testing assist in the diagnosis of sports-related concussions in youth?
• Does neuropsychological testing have a role in tracking recovery and informing management (e.g., return to school, return to play, return to work)?
• Are computerized tests valid and reliable?
• Does baseline testing improve the utility of neuropsychological testing in the diagnosis and management of sports-related concussion?

Can Neuropsychological Testing Assist in the Diagnosis of Sports-Related Concussions in Youth

In the context of sports-related concussions, an important distinction must be made between the use of neuropsychological tests for diagnosis and their use for tracking recovery (McCrory et al., 2005). Studies of the ability of neuropsychological tests to provide accurate diagnoses of concussion typically involve tests administered within 72 hours of the injury. They include studies comparing group-level score changes in groups of concussed individuals versus groups of non-concussed individuals and studies looking at individual diagnostic accuracy. However, it should be noted that neuropsychological tests are traditionally not used to make diagnoses, but rather to characterize function. So it is a useful question to ask whether these tests can contribute to diagnosis.

An often unmentioned aspect of concussion research and practice is the variability in identification of concussion and the still-limited knowledge of the biological nature of concussions (i.e., the lack of biomarkers for diagnosis and recovery). Although studies typically rely on the identification of concussions by athletic trainers according to generally accepted standards, the validity of these diagnoses has never been established. In one study, 50 percent of diagnosed concussions were identified more than 24 hours after the incident, and 30 percent of this group had no identifiable biomechanical impacts on the day of the reported injury (based on accelerometer readings in the helmets) (Duhaime et al., 2012). Determinations of the diagnostic efficiency of a test will be affected by the validity of actual diagnoses. Thus variability in this process can produce conflicting or limited results in studies of the predictive ability of any tool.

Given the relatively rapid time-course of concussions, the temporal aspects of the injury are also significant factors in studying the phenomena. Indeed, studies have shown that the closer the assessment was to the time of injury, the more pronounced the effect of the biomechanical force on cognition was (Beckwith et al., 2013a,b; McAllister et al., 2012). Broglio and Puetz (2008) questioned whether comparing athletes who are assessed at different time-points from injury likely invalidates the findings. As Hutchinson and colleagues (2011) found, the presence of pain can have an effect on test scores. Controlling for diagnosis and time of testing, baseline exposure to the tests, and other factors adds to the complexity of studying concussions at the group and individual levels, particularly in the immediate aftermath of the injury when symptoms are typically high. McCrory and colleagues (2005) also questioned whether the presence of symptoms could preclude accurate (valid) test results. Symptoms may interfere in test performance through any or all attention mechanisms, reducing arousal, orienting, focus, sustaining focus, and so on, or symptoms may make the individual feel too bad to participate (a type of motivational effect). Unfortunately, the actual evidence is limited, as few studies directly test the hypothesis that symptoms (either in total or individually) account for significant variance in test scores.

As a practical matter the test scores may reflect the overall status of the individual, but, because neuropsychological tests are designed to assess brain function, the inclusion of symptom-related error into the test score interferes in the psychometric accuracy of the test. In other words, poor performance on a neuropsychological test because one feels bad may obscure the test's ability to accurately measure brain function. Studies indirectly point to the correlation of symptoms and test scores (Collins et al., 2003a; Fazio et al., 2007), particularly immediately after injury, when symptoms tend to be highest. Thus, the mediating effect of symptoms on test scores in the immediate aftermath of the injury likely reduces the predictive power of tests alone. The evidence for diagnostic validity and utility comes from group studies and from studies of individual probability. Group studies have employed cross-sectional designs and within-subjects designs using baseline or multiple test points for comparisons. Group studies have been described in two meta-analytic studies (Belanger and Vanderploeg, 2005; Broglio and Puetz, 2008). There was considerable overlap in the groups of studies reviewed in the two analyses, but Broglio and Puetz were interested in the effect of using multimodal assessments, while Belanger and Vanderploeg were focused on neuropsychological assessments only.

Group studies have generally shown that a significant proportion of concussed athletes have neurocognitive decrements compared to controls (or compared to baseline performances) in the initial days following the injury, but scores are back to normal or baseline by 7 days post injury. Belanger and Vanderploeg (2005) analyzed 21 studies from 1994 to 2004. All had multiple assessment points using control groups tested at the same interval. They found significant acute effects (changes in scores reflecting worsening in the first 24 hours after injury) for most cognitive domains (delayed memory: d=1.00; memory acquisition: d=1.03; and global cognitive functioning: d=1.42). However, when analyzed across all studies, no group residual neuropsychological reductions were found when testing was completed beyond 7 days post injury.

The meta-analysis of Broglio and Puetz (2008) included 39 studies from 1970 to 2006 that met their inclusion criteria: studies of concussed athletes who were evaluated using symptom assessment, balance assessment, or neuropsychological/cognitive assessment. One post-injury assessment had to have been completed within 14 days of injury and compared with a baseline measure or control group. Three types of cognitive assessments were included: the SAC, paper-and-pencil batteries, and computerized batteries. They found significant effects of concussion on all three types of assessments immediately after injury. The type of cognitive assessment was determined to be a moderator effect, as was the time from injury to assessment. The largest effect was for the SAC administered immediately after injury.

The usefulness of tests to diagnose a disease entity (e.g., their ability to detect a person with disease or exclude a person without disease) is usually described by such terms as sensitivity, specificity, positive predictive value, and negative predictive value. These various measures describe how well the tests identify people who actually have the disease (or not) as diagnosed by some gold standard method. Sensitivity (the chance that a person with the disease is correctly identified as having it) and specificity (the chance that a person without the disease is correctly identified as being free of it) are the characteristics most reported for a diagnostic test because they reflect the characteristics of the test and not those of the group tested. However, the users of the test are likely to be more interested in the predictive values (the chance that a person identified by the test as concussed actually had a concussion—positive predictive value—and the chance that a person identified as not having a concussion was actually free of a recent concussion—negative predictive value). The predictive value changes depending on what fraction of the athletes tested truly had a concussion.

Van Kampen and colleagues (2006) tested the diagnostic value of adding neuropsychological testing to assessments of symptom load. One hundred twenty-two athletes diagnosed with concussion and 70 without a recent concussion were compared by looking at their post-injury symptoms and their ImPACT test scores. Concussed athletes were tested 2 days after injury. Ninety-three percent of athletes with a reliable increase in symptoms actually had a concussion—a positive predictive value (PPV) of 93 percent—but 41 percent of those without a reliable increase in symptoms also had a concussion—a negative predictive value (NPV) of 59 percent. When ImPACT was used in the absence of symptom data, 83 percent of those having at least one abnormal⁵ neurocognitive test score had a concussion (PPV=83%) and 70 percent of those with no abnormal neurocognitive scores did not have a concussion (NPV=70%). However, when criteria for concussion classification were changed to require at least one abnormal Im-PACT test or a reliable increase in symptoms, 81 percent of those who the tests indicated had a concussion actually did (PPV=81%) and 83 percent of those the tests indicated were free of concussion actually were (NPV=83%). These predictive values are based on 64 percent (122 of 192) of the athletes studied having a recent concussion. If the same diagnostic criteria were used to screen every football player after every game (prevalence under 1 percent), more than 97 percent of the athletes the test identified as having a recent concussion actually would be diagnosed in error.

Several other studies have demonstrated a strong diagnostic efficiency for neuropsychological tests. Schatz and colleagues (2006) obtained 82 percent sensitivity and 89 percent specificity comparing ImPACT tests scores (n=72) within 72 hours of injury to scores of non-concussed athletes (n=66). A similar approach was used by this group analyzing ImPACT data of 81 concussed athletes and 81 controls, ages 13 to 21 (Schatz and Sandel, 2013). High sensitivity (91 percent) and adequate specificity (69 percent) were obtained.

Summary

Neuropsychological tests have the ability to detect cognitive changes in injured athletes, although cognition as indexed by test scores appears to improve for the vast majority of injuries within 2 weeks. There are mixed results of the diagnostic utility of neuropsychological testing immediately (within 48 hours) after injury, although significant differences between concussed and non-concussed individuals are more often found in group studies. There is general agreement that neuropsychological tests should not be used in isolation for diagnosis; symptom levels are the best predictor of diagnosis (i.e., concussion diagnosis is made based on symptom presentation). Although the presence of symptoms can influence test results, potentially obscuring the accurate measurement of brain function, neuropsychological testing is one of several tools (along with symptom assessment, clinical evaluation, and the like) that may aid in concussion diagnosis. It appears that high scores on neuropsychological tests, indicating good cognitive function, are predictive of not having a concussion.

Does Neuropsychological Testing Have a Role in Tracking Recovery and Informing Management

Neuropsychological testing has been used extensively in the rehabilitation setting to document and track cognitive recovery. In the area of sports-related concussions, the standard as promulgated by the Zurich statement and other consensus statements has been that recovery can be said to have taken place when symptoms, cognition, and balance have returned to the athlete's baseline (or typical) performance (Halstead et al., 2010; Harmon et al., 2013; McCrory et al., 2013b). Using that as the benchmark, studies have generally found neuropsychological testing to be a useful aid in determining when an athlete has recovered enough to return to competition. Although the methodological rigor of the studies varies (Comper et al., 2010), the ability of neuropsychological tests to detect subtle changes in cognitive function is well established.

Several studies have documented persistent declines in post-injury neuropsychological scores even after symptoms have resolved (Broglio et al., 2007a; Iverson et al., 2006; Peterson et al., 2003). These studies found improvements in cognitive scores, balance testing, and symptoms over time, with the cognitive scores taking longer to improve than the balance and symptom scores. Iverson and colleagues (2006) included a reliable change methodology and demonstrated that 37 percent of the concussed athletes continued to have at least two ImPACT composite scores significantly lower than expected after 10 days, even though the symptoms had resolved after 5 days. A more recent study using ANAM found that several subtest scores differentiated mild from moderate concussions on the day of injury but not at 8 days post injury (Prichep et al., 2013).

The two meta-analyses noted above also examined the ability of neuropsychological tests to measure changes in cognitive function through recovery. Belanger and Vanderploeg (2005) found significant improvement between days 7 and 10 for verbal memory retention scores only. Broglio and Puetz (2008) examined how the effects of concussion were manifested in three assessment modalities: the SAC, paper-and-pencil batteries, and computerized batteries. They found significant effects of concussion on the scores of all three assessment modalities immediately after injury as well as reduced but still large effects for the cognitive assessment at 14 days post injury interval. The type of cognitive assessment was determined to be a moderator effect, as was the time from the injury to the assessment. The largest effect was seen for the SAC immediately after injury, with the paper-and-pencil batteries having significantly greater effects than the SAC or computer batteries at 14 days.

Summary

There is a long history of neuropsychological tests being used to track recovery from brain injury as they are thought to reflect functional cognitive recovery. Group studies of individuals with sports-related concussions have shown that neuropsychological test scores improve as the time from injury increases. Some studies have found continued cognitive declines on neuropsychological testing, even after individuals' concussion symptoms have resolved, although other studies show symptoms lasting longer than cognitive declines. The persistence of cognitive declines following symptom resolution in some individuals suggests there may be a role for neuropsychological testing in concussion management, for example, to help inform return-to-play decisions in these cases. Such a role for computerized neuropsychological testing has been criticized, however, on the grounds that there currently is no evidence to show that delaying an individual's return to full physical activity on the basis of residual neurocognitive deficits actually improves recovery outcomes or reduces the risk of subsequent injury (Kirkwood et al., 2009; Randolph and Kirkwood, 2009).

Are Computerized Tests Valid and Reliable

All neuropsychological tests require standardized administration and expert interpretation of results. Assuming that these conditions are met, test effectiveness is typically determined by several factors: Is it reliable (does it produce consistent results each time it is administered), is it valid (do the test scores represent the construct of interest, e.g., working memory), and does it measure individuals with respect to the construct of interest (i.e., specific cognitive functions, diagnostic efficiency)? Test developers attempt to show that their tests meet these criteria, but a fourth aspect is also important: Does independent research obtain the same results as the test developers' research? Computerized test batteries are not unique to sports neuropsychology, but it is important to examine their role in concussions because of how extensively they are used.

A complete neuropsychological assessment of the multiple cognitive functions of an individual can take between 4 and 8 hours (Lezak et al., 2012). Screening tools that focus on functions typically affected by brain injuries were developed to reduce the length of the typical neuropsychological batteries and to focus on identifying acute cognitive dysfunction. Such targeted batteries also made larger-scale testing feasible, which in turn created the opportunity to implement the Sports as a Laboratory Assessment Model (SLAM) for sports-related concussion.

Collie and colleagues (2001) raised concerns about paper-and-pencil testing that centered on interrater reliability issues, the general lack of alternative forms, and the effect of practice in repeat testing. McCrory and colleagues (2005) noted that computerized testing offered advantages such as standardized and randomized presentation of stimuli, shorter administration time, central data storage, and more sensitive and accurate detection of reaction times. Furthermore, standard paper-and-pencil tests did not typically have normative standards developed specifically for athletes, and computerized tests allowed for easier repeat (serial) testing to track cognitive recovery. Indeed, an entire industry, with its corresponding potential financial conflicts of interest, has developed around providing baseline and serial post-injury testing to thousands of athletes. By 2003, the brief paper-and-pencil test battery was becoming replaced by computerized test batteries such as ImPACT, CogSport, ANAM, and CRI (see, e.g., Cernich et al., 2007; Collie et al., 2003; Collins et al., 2003b; Erlanger et al., 2003).

Between 1999 and 2002 there were 10 studies using paper-and-pencil batteries and only one using computer testing; between 2003 and 2008 there were 8 studies utilizing paper-and-pencil batteries and 15 using computer testing (Comper et al., 2010). Thus, in terms of research, there was a dramatic shift in focus. The shift in research focus also appears to have been mirrored by practice. In 2009, Covassin and colleagues reported that 95 percent of the 266 athletic trainers who participated in a survey said they administered baseline computerized neurocognitive testing to their athletes. However, only 51.9 percent examined the baseline test validity indices. The researchers concluded that the athletic trainers in the study appeared to rely more on symptoms than on neurocognitive test scores when making return-to-play decisions (Covassin et al., 2009). When Meehan and colleagues (2011) reviewed data from the High School RIO™ database of athletic injuries for the 2009-2010 school year (1,056 sports-related concussions), they found that computerized neuropsychological testing was used for 41.2 percent of concussions. Although there are concerns with the use of such testing, it continues to represent a large portion of concussion management activity. At this point, all of the computerized tests have some peer-reviewed research to support their use.

Psychometric tests are judged on their reliability and validity as documented in their manuals and published studies. Reliability is usually assessed as a test-retest correlation or in terms of an intraclass correlation coefficient (ICC). A Pearson correlation can be a valid estimator of interrater reliability (i.e., test-retest reliability), but only when there are meaningful pairings between two and only two raters. A test of internal stability (Chronbach's alpha) is a test of the function of the number of test items and the average intercorrelation among the items (see Anastasi and Urbina, 1997). These are statistical tests that provide information about the ability of the test to maintain its performance and psychometric characteristics over time.

Evidence to support test interpretation (validity) may come from various forms: evidence based on test content, evidence based on response processes, evidence based on internal structure, evidence based on relations to other variables, and evidence based on the consequences of testing. Establishing validity is seen as a long-term process, and no one study can make that determination. Test development practice calls for documentation of some form of reliability and validity (see AERA et al., 1999). All of the major computerized tests have demonstrated some level of reliability and validity. Other aspects of their structure may make them more suitable for some situations than others, and practitioner preference, experience, and knowledge are important factors. It should be noted that the Department of Defense currently uses ANAM to assess post-concussion neurocognitive changes in service members in all branches of the military. Table 3-5 outlines the basic features of several of the currently available computerized tests.

TABLE 3-5

Common Computerized Neuropsychological Tests.

Reliability of computerized tests

The ability of a test to perform consistently is important to having confidence in its scores. Table 3-6 lists published reliability studies of several different computerized neuropsychological tests used in concussion management. Several approaches to reliability can be taken: Internal consistency can be measured using Chronbach's alpha test or one can examine the correlation between half of the items and the other half (split-half reliability). Test-retest reliabilities are used to determine consistency across test administration: a Pearson correlation or an ICC can be calculated. The ICC has become the preferred measure as it is a type of interrater reliability. However, there is no agreement on the minimum ICC value that is considered “acceptable” for computerized neuropsychological tests. Some authors find a minimum correlation of 0.60 to be acceptable (e.g., Baumgartner and Chung, 2001; Weir, 2005), while others employ a higher standard of 0.70 (e.g., Anastasi and Urbina, 2007) and still others may consider 0.80 or 0.90 to be the mark of a good, reproducible automated test.

TABLE 3-6

Reliability Studies on Common Neuropsychological Tests.

As Table 3-6 demonstrates, ICCs for different composite scores within tests are quite variable, and low intraclass correlations are frequently found. If there is a trend across tests, it appears to be that speeded tests have better reliability than do tests of other functions such as memory. This may have to do with the inherent nature of computerized tests and the manner in which tasks must be presented in this format.

Reliability studies are quite variable, with some studies demonstrating adequate reliability and some indicating less than adequate reliability. There are many possible reasons for the variability, including different sample sizes, unknown testing conditions, and variable item pools. Most computerized tests produce multiple forms through a quasi-randomization of items. All of the commercial test batteries that were reviewed had some studies indicating acceptable reliability. Tests involving speed appear to be more reliable than those involving memory or accuracy. This may be due to computer-format constraints. Clinicians and researchers need to be aware of the variability in reliability studies with these tools.

Validity of computerized tests

The presentation format of a computer-based test presents different limitations and strengths than those of paper-and-pencil testing. For instance, memory is a complex function and computerized tests of memory are limited to recognition formats. This format limitation may be one reason for the difficulty in isolating specific cognitive functions, as there may be overlap between (for example) processing speed and working memory (Maerlender et al., 2010). However, answering questions about identification and recovery may not require such construct specification.

As the previous sections document, a large number of studies have demonstrated the various aspects of validity of these computerized batteries. Table 3-7 lists published validity studies of several different computerized neuropsychological tests used in concussion management. Concurrent validity (comparing the scores from one test to those from another similar test) and criterion and predictive validity (predicting a criterion such as the diagnosis of concussion) are the most frequently cited methods of establishing validity. Construct validity attempts to establish the underlying cognitive mechanisms that the test is actually measuring (e.g., memory, attention). There is overlap in these types and methods for understanding validity.

TABLE 3-7

Validity Studies on Common Neuropsychological Tests.

Concurrent validity has been demonstrated for each of the batteries when compared with paper-and-pencil neuropsychological tests. Most studies show high correlations with tests thought to measure similar constructs. Only two studies mention the discriminating ability of the tests, that is, whether a particular test shows low correlations with other tests that it should not be highly correlated with. For example, although the ImPACT test has high correlations between the composite scores and similar paper-and-pencil tests (convergent construct validity), the same sample showed high correlations with dissimilar paper-and-pencil measures (Maerlender et al., 2010). On the other hand, Newman and colleagues (2013) found that the new Pediatric ImPACT test showed good discrimination between speed of processing and memory tests. Using a factor-analytic approach, Allen and Gfeller (2011) also demonstrated construct validity for ImPACT. ANAM (Bleiberg et al., 1997, 2000, 2004; Prichep et al., 2013), CogSport (Collie et al., 2003; Makdissi et al., 2010; Moriarity et al., 2012), and CRI (Erlanger et al., 2003) also have been shown to possess various types of validity.

In group studies, neuropsychological test scores have generally not been shown to predict prolonged recovery. Most recently, McCrea and colleagues (2013) analyzed data obtained from 570 high school and college athletes with concussions at several time-points after injury. The study divided the athletes into groups in which symptoms had resolved within 7 days (typical) and had lasted more than 7 days (prolonged recovery). Neuropsychological test scores at less than 2 days post injury were not predictive of which recovery group an athlete would be in. This finding was similar to findings in the two meta-analytic studies described previously (Belanger and Vanderploeg, 2005; Broglio and Puetz, 2008). It should be noted that because in 90 percent of concussion cases the individuals recover by the end of 2 weeks (typical), group analyses may obscure the effects in those 10 percent of cases in which scores continue to suggest injury.

Summary

All of the computerized neuropsychological test batteries present some evidence of concurrent validity with traditional paper-and-pencil tests. Direct comparisons between tests provide some strong relationships, typically for the speeded tests rather than the memory tests. Within-battery reliabilities tend to be better for speeded tests as well. The CRI does not include a memory component. CogSport has demonstrated good reliability for working memory speed, but not for accuracy.

The generally poorer performance of “memory” tasks is unfortunate because working memory has long been identified as a significant cognitive function that declines in all forms of TBI; the poorer performance may be a function of the computer presentation of the tests. The trend of speeded tests showing better performance than the accuracy measures may be reflecting the strengths of the computerized platform.

Does Baseline Testing Improve the Utility of Neuropsychological Testing in the Diagnosis and Management of Sports-Related Concussion

Baseline testing has become commonplace and often is considered an invaluable part of sports concussion management as it allows for more accurate interpretation of post-injury scores (McCrory et al., 2005). In 2011, Congress mandated that the Department of Defense develop and implement a comprehensive policy on consistent neurological cognitive assessments of service members before and after deployment (P.L. 111-383, sec. 722). The Department of Defense now mandates pre-deployment baseline testing to be performed on all service members within 12 months of their deployment (DoD, 2013). Comparing a post-injury score to an individual's baseline allows a comparison that controls for many of the individual factors that can affect test performance, and several papers have called for its (continued) use (Barth et al., 1989; Gardner et al., 2012; Hinton-Bayre et al., 1997, 1999; Lovell and Collins, 1998). Only a few empirical studies have examined the potential benefit of using baseline test scores instead of comparing post-injury scores to normative standards. Baseline testing is costly and, as indicated previously, is not without its logistical and administration problems, which can sometimes lead to questionable results. Furthermore, the use of baseline testing automatically presumes repeat testing; with that, appropriate statistical procedures are needed for interpreting results (Heilbronner et al., 2010; McCrory et al., 2005). Test scores are known to “regress to the mean” after multiple exposures, practice effects can inflate scores, and baseline scores on the extremes of the distribution will have different effects with repeat testing. Although having different “forms” of a test (different items) reduces the test taker's ability to memorize responses, the test procedures are the same, so practice increases test familiarity, which can enhance performance.

Schmidt and colleagues (2012) analyzed retrospective data for 1,060 collegiate athletes with baseline neuropsychological test (ANAM), balance, and symptom checklist results. The study used reliable-change methodology for the baseline comparisons and difference from mean baseline score for the normative comparison. An analysis of variance comparing the number of correct identifications between methods found that the baseline comparison was significantly better (fewer misidentifications) for a reaction time score, and the normative comparison was better for a mathematical reasoning score. The authors noted that individual differences in baseline performance on math processing may have caused the high rate of misidentifications. This is a drawback of the reliable-change method as opposed to a regression-based method. No other significant neuropsychological score disagreements were observed, nor were there any score disagreements for postural control or symptom severity.

Summary

Baseline testing has been called for and recommended for many years. It was a cornerstone of Barth's original SLAM model and has been seen as an answer to the limitations of normative comparisons for detecting clinical change. However, very few studies have specifically examined the value of baseline testing, and establishing the validity of baseline testing is difficult. The consensus statement from the Fourth International Conference on Concussion in Sport held in Zurich has taken the lack of evidence for baseline testing as an indication that baseline testing should not be required (McCrory et al., 2013b). Baseline testing is a common practice in schools and programs for many sports (Covassin et al., 2009), and it has a theoretical foundation. On the other hand, there are drawbacks to conducting large-scale baseline assessments; as Moser and colleagues (2011) have pointed out, group testing has its disadvantages. In addition, baseline testing is expensive and time-consuming, and there is the question of whether the use of baseline testing in concussion management actually reduces risks of recurrent injury or long-term functional deficits.

Randolph and Kirkwood (2009) provided a comprehensive review of the evidence to that date regarding the use of different strategies in sports concussion management. They acknowledged that few prospective studies had been done regarding risks and means for minimizing them. Their review of the literature on football concussions (as the paradigmatic sport) noted potential risks of death or permanent disability, delayed recovery, same-season repeat concussion, and the late-life consequences of multiple concussions. They observed that catastrophic outcomes associated with sports-related concussion are extremely rare, and less serious short-term adverse outcomes also are rare and generally transient. In addition, they argued that current management strategies, including baseline testing, did not modify these risks. The same group followed up with a critique of baseline testing specifically. They argued that the utility of using baseline tests rests on the function (real-world) outcomes derived from the procedure. They note:

The primary justification for the baseline method is that it helps to ensure that athletes are fully recovered from a concussion and are therefore “safe” to [return to play]. At present, however, little to no empirical evidence is available to demonstrate that such testing actually reduces any known risk associated with concussive injury. (Kirkwood et al., 2009, p. 1410)

The 2013 position statement of the American Medical Society for Sports Medicine states that most concussions can be managed appropriately without neuropsychological testing and also notes the lack of evidence that use of baseline testing in the clinical management of concussions improves short- or long-term outcomes (Harmon et al., 2013).

ACUTE CONCUSSION MANAGEMENT

The time-course of the effects of a concussive blow or blows appears to take place on the order of minutes, hours, and days. Within the period of recovery, the brain is thought to be vulnerable to further injury, which can be more severe and may complicate recovery (Cantu, 1998; Cantu and Voy, 1995; Eisenberg et al., 2013; McCrory and Berkovic, 1998; Saunders and Harbaugh, 1984). Thus, although the initial injury may be mild, acute management is still needed to protect the individual from more significant harm.

In 80 to 90 percent of high-school- and college-age patients, concussion symptoms resolve within 2 weeks without any overt intervention (McClincy et al., 2006; McCrea et al., 2004, 2013). McCrea and colleagues (2013) examined 570 high school and college athletes with concussions⁶ and 166 non-concussed athlete controls. Only 10 percent of the concussed athletes (n=57) took longer than 7 days to recover. In an earlier study, McCrea and colleagues (2004) reported on the recovery from concussions in 94 concussed college football players and 56 non-concussed controls. On average the athletes reverted to baseline by day 7, and there were no symptomatic or functional differences between the two groups by 3 months. This study also found that neuropsychological recovery tended to lag 2 to 3 days behind symptomatic recovery. McClincy and colleagues (2006) documented symptom and ImPACT test scores at baseline and at 2, 7, and 14 days post injury in 104 concussed high school and college athletes. They found significant differences in symptom and ImPACT scores through 7 days post injury, although the magnitude of differences dropped over time. There was no significant difference between symptom scores at baseline and at 14 days post injury. In addition, at day 14, only the verbal memory composite score of the ImPACT test was significantly different from baseline, although this suggests that at least some areas of neuropsychological recovery may persist in asymptomatic individuals. However, no adjustments for baseline scores or repeat testing were made. Makdissi and colleagues (2010) reported on the natural history of concussion in Australia elite junior and senior football players. The mean time to return to play was 4.8 days, with 18 percent showing symptoms for more than 7 days. Again, computerized neuropsychological testing revealed that abnormalities in neurocognitive performance persisted for 2 to 3 days after the athletes no longer were asymptomatic.

In a study comparing concussion recovery times of high school and college athletes through 7 days post injury, Field and colleagues (2003) found that high school athletes recovered more slowly within the first week after injury, but there was no difference in performance by 7 days in most areas tested. Unlike their college counterparts, high school athletes with a concussion still exhibited a significant decrease in memory performance at 7 days compared with controls (Field et al., 2003).

There is no body of literature on sports-related concussion recovery times for younger children (5 to 12 years). Eisenberg and colleagues (2013) found that concussion symptoms in children 11 to 13 years old presenting to the emergency department (ED) resolved more quickly than in those age 13 and older. It is important to note that the sample in the Eisenberg study was drawn from patients presenting to the ED with acute concussions, raising the possibility that participants may have experienced a more severe injury or a higher initial symptom load than did individuals with acute concussion who do not seek care in an ED. Almost 64 percent of those included in the study sustained their concussions playing sports, 22 percent experienced loss of consciousness, and 43 percent experienced amnesia.

In most studies, the majority of youth adjust well after an mTBI, but in studies that had a non-head-injury control group and good sample retention, around 10 to 13 percent were still symptomatic at 3 months and 1 year after the injury (Barlow et al., 2010; McCrea et al., 2013; Yeates et al., 2009, 2012). Chapter 4 includes recovery curves for reported symptoms, postural stability, and cognitive function (see Figures 4-1, 4-2, and 4-3).

In the acute phase of concussion management, in addition to symptom resolution, the goals include protecting the brain from additional injury and stress, avoiding potential long-term cognitive sequelae of repeated injury, and avoiding the risk of second impact syndrome. The current consensus statements put forth by the international Concussion in Sport Group (McCrory et al., 2013b), the American Medical Society for Sports Medicine (Harmon et al., 2012), the American Academy of Pediatrics (Halstead et al., 2010), and the American Academy of Neurology (Giza et al., 2013) state that athletes who sustain a concussion should not return to play on the same day as the injury. There is evidence that high school and college athletes may have a delayed onset in symptoms and demonstrate post-injury neuropsychological deficits that may not be apparent on the sideline of an athletic event, and therefore the athletes would benefit from immediate removal from play for their protection (Collins et al., 1999, 2003b; Duhaime et al., 2012; Guskiewicz et al., 2003; Lovell et al., 2003; McCrea et al., 2003). This suggests that same-day return would place that athlete at higher risk for adverse outcomes.

During the acute phase, clinical management strategies to limit physical and cognitive activity are emphasized. The more aggressive medical management of symptoms typically does not begin until 2 to 4 weeks post injury, when an athlete may be said to be experiencing prolonged recovery (see Chapter 4).

Return to Physical Activity

The return of an individual to physical activity following a concussion is typically governed by his or her symptom load. Consensus opinion (McCrory et al., 2013b) and practice guidelines (Giza et al., 2013; Halstead et al., 2010; Harmon et al., 2013) state that individuals who have sustained a concussion should avoid physical activity during the acute phase of recovery until they are symptom-free at rest and without medication (see also Buzzini and Guskiewicz, 2006; Canadian Academy of Sport Medicine Concussion Committee, 2000; Herring et al., 2011; Hunt and Asplund, 2010; Kutcher and Eckner, 2010; Lee, 2006; Moser et al., 2007; Poirier, 2003; Purcell and Canadian Paediatric Society, 2012; Putukian et al., 2009). Before returning to activity, individuals should also be back to either their own baseline or the appropriate population norm with regard to neuropsychological/cognitive functioning (McCrory et al., 2013b). When this is measured or obtained by computerized testing, it is important that interpreting providers consider reliable change in test scores rather than exclusively focusing on the numbered scores or percentile scores.

The Department of Defense requires that all deployed service members who are diagnosed with their first concussion observe a mandatory minimum 24-hour recovery period, which may be extended on the basis of subsequent clinical evaluation (DoD, 2012).⁸ Similar concussion management policies are being developed for concussed service members in the non-deployed setting as well (Tsao, 2013).

During the period when the patient denies symptoms but when metabolic changes presumably are still in effect, symptoms may be induced by rigorous exercise. Therefore, team physicians and athletic trainers may use exercise as a “symptom stress test” to determine whether a player is ready to return to play. Furthermore, evidence that the resolution of neurocognitive impairment following concussion may take longer than the resolution of physical symptoms (Broglio et al., 2007a; Iverson et al., 2006; Peterson et al., 2003; Sandel et al., 2012) and that moderate exercise may induce cognitive declines in athletes who are asymptomatic and have returned to neurocognitive baseline following concussion (McGrath et al., 2013) highlight the importance of appropriately managing an individual's return to physical activity.

Once individuals are symptom-free, it is frequently recommended that they follow a graded return-to-play protocol (see Table 3-8), progression through which is governed in part by recurrence of symptoms (Canadian Academy of Sport Medicine Concussion Committee, 2000; Halstead et al., 2010; Herring et al., 2011; McCrory et al., 2013b). The protocol calls for individuals to proceed to the next level if they remain asymptomatic at the current stage. If concussion symptoms reappear, the athlete should revert back to the previous asymptomatic stage and resume the progression after 24 hours (Canadian Academy of Sport Medicine Concussion Committee, 2000). The Department of Defense is also in the process of developing a gradual return-to-duty guideline (personal communication with Jack W. Tsao, October 8, 2013).

TABLE 3-8

Graded Return-to-Play Protocol.

However, aside from evidence supporting refraining from activities that risk additional injury or re-injury during the temporally undefined “window of cerebral vulnerability” following a concussion, there is little empirical evidence to support the timing of return to physical activity or the use of graded approaches for doing so.

FINDINGS

The committee identified the following findings on concussion recognition, diagnosis, and management:

• Currently concussion diagnosis is based primarily on symptoms reported by the individual rather than on objective diagnostic markers, which might also serve as objective markers of recovery.
• The signs and symptoms of concussion typically fall into four categories—physical, cognitive, emotional, and sleep—with patients experiencing one or more symptoms from one or more categories.
• The use of multiple evaluation tools, such as symptom scales and checklists, balance testing, and neurocognitive testing, may increase the sensitivity and specificity of concussion identification, although existing evidence is insufficient to determine the best combination of measures.
• Traditional neuroimaging techniques, such as computerized tomography and magnetic resonance imaging, are of little diagnostic value for concussions per se, because structural imaging results are normal in the case of concussions uncomplicated by skull fracture or hematoma.
• Newer imaging techniques, such as magnetic resonance spectroscopy, positron emission tomography, single-photon emission computed tomography, functional magnetic resonance imaging, and diffusion tensor imaging may be useful in the future for assessing sports-related concussions, but at present they have not been validated for clinical use.
• There is some consensus in the literature that both quantitative electroencephalograph and event-related potential procedures can detect differences in performance and neural responses in concussed versus non-concussed student athletes in high school and college even when behavior measures fail. However, these findings are true for a relatively small set of tasks that assess a limited array of cognitive abilities. Use of a broader range of tasks that measure different aspects of cognitive processes is necessary to provide a comprehensive view of behaviors most likely affected and those more likely spared by concussion.
• There is little research on the use of serum biomarkers in pediatric concussion. Although appropriately sensitive and specific serum biomarkers could be of great diagnostic and prognostic value in sports-related concussion, there currently is no evidence to support their use. There is some evidence, however, to suggest that normal levels of S100B following head injury may predict individuals who do not have intracranial injury.
• Neuropsychological testing has a long tradition in measuring cognitive function after traumatic brain injury and is one of several tools (along with symptom assessment, clinical evaluation, and the like) that may aid in the diagnosis and management of concussions in youth. Studies of the effectiveness of these tests to predict diagnosis and track recovery have had mixed results, and the performance of individuals on neuropsychological tests can be influenced by many factors, including effort and the presence of concussion symptoms (e.g., fatigue resulting from sleep disturbance). It appears that high scores on neuropsychological tests, indicating good cognitive function, are predictive of not having a concussion. In group studies these tests have been shown to be useful for tracking cognitive recovery for up to 2 weeks post injury, with a majority of concussions considered to be resolved by that time. There are no data on the effectiveness of monitoring recovery in individuals whose symptoms persist beyond the typical recovery period.
• Reliability studies for computerized neuropsychological tests are quite variable, with some studies demonstrating adequate reliability and some indicating less than adequate reliability. There are many possible reasons for the variability, including different sample sizes, unknown testing conditions, and variable item pools. Most computerized tests produce multiple forms through a quasirandomization of items. All commercial test batteries reviewed had some studies indicating acceptable reliability.
• Expert consensus opinion is that an individualized treatment plan including physical and cognitive rest is beneficial for recovery from concussion. There is little empirical evidence to indicate the optimal degree and duration of physical rest needed to promote recovery or the best timing and approach for returning to full physical activity, including the use of graded return-to-play protocols. However, there is evidence that the brain is more susceptible to injury while recovering; thus, common sense dictates reducing the risks of a repeat injury. Similarly, there is little evidence regarding the efficacy of cognitive rest following concussion or to inform the best timing and approach for return to cognitive activity following concussion, including protocols for returning students to school.
• Randomized controlled trials or other appropriately designed studies on the management of concussion youth are needed in order to develop empirically based clinical guidelines, including studies to determine the efficacy of physical and cognitive rest following concussion, the optimal period of rest, and the best protocol for returning individuals to full physical activity as well as to inform the development of evidence-based protocols and appropriate accommodations for students returning to school.

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Footnotes

1

The reasons for athletes not reporting concussion were not mutually exclusive. The subjects were asked to select all that applied.

2

The core scales are the Pittsburgh Steelers Post-Concussion scale (17 items), Post-Concussion Symptom Assessment Questionnaire (10 items), Concussion Resolution Index post-concussion questionnaire (15 items), Signs and Symptoms Checklist (34 items), Sport Concussion Assessment Tool (SCAT) post-concussion symptom scale (25 items), and Concussion Symptom Inventory (12 items).

3

The research-based scale is the Health and Behavior Inventory; the four clinical scales are the Post-Concussion Symptom Scale, Graded Symptom Checklist/Scale, Rivermead Post-Concussion Symptom Questionnaire, and Post-Concussion Symptom Inventory/Acute Concussion Evaluation (Gioia et al., 2009).

4

High school athletes reported more somatic or migraine symptoms than did college athletes, whereas college athletes reported more emotional and sleep symptoms than did their high school counterparts.

5

Abnormal here means a change from baseline to post-injury score outside the 80 percent confidence interval for reliable change: abnormal reliable change index. This does not necessarily imply clinical abnormality.

6

Of the injuries, 60.5 percent were in high school athletes, and 39.5 percent were in college athletes.

7

The report reflects information that was available at the time it went to press. A prospective study of the effect of cognitive activity level on the duration of symptoms following sports-related concussions in 335 youth ages 8 to 23 years subsequently was published in January 2014 (Brown et al., 2014).

8

Service members who receive a second concussion diagnosis within 12 months are not returned to full duty for 7 days following symptom resolution (DoD, 2012). Individuals who sustain 3 or more concussions within 12 months are required to undergo a “recurrent concussion evaluation,” which is used in determining return-to-duty status (DoD, 2012).