Introduction
Sport-related concussion (SRC) can be defined as a brain injury resulting from a direct or indirect blow to the head that transmits a force to the brain occurring in the context of sports or other types of physical activities.1 This injury is quite common in active populations, being reported in both children and adults. In fact, its incidence was as high as 1/450 in physically active Canadians aged 12 or older in 2017–2018.2 A wide array of athletes report having sustained at least one concussion during their lifetime or sporting career, with prevalence rates reaching as high as 20% among adolescents3 and as high as 37% among college athletes.4 When a concussive injury occurs, the biomechanical force transmitted to the brain results in damage to the brain’s axons, followed by a neurometabolic cascade and brain inflammation.5 Those rapid changes in the brain lead to a large spectrum of signs and symptoms,1,5 which may be associated with mental impairment or with symptoms of an emotional (e.g., sadness, anxiety, irritability), physical (e.g., headache, fatigue, balance problems, dizziness), or cognitive nature (e.g., memory deficits, difficulty concentrating).6 More precisely, visual complaints that fall into both physical and cognitive categories, such as blurred vision, acuity dysfunction, light sensitivity, reading difficulties, and eye fatigue, are quite a common presentation of SRC.7–9
It is estimated that one-third of athletes report visual deficits in the acute phase of SRC.10 It is believed that these deficits may be attributed to the fact that eye movements, which are essential for clear vision, object tracking, and depth perception, are regulated by the frontal and parietal cortices, which together account for approximately 50% of the brain circuitry.9,11 Since all brain areas are vulnerable to SRC, there is a significant risk of visual system impairment postinjury. The main aspects of eye movement that are at risk of dysfunction after a concussion include (1) smooth pursuit (following a low-speed object with the eyes), (2) saccades (rapid movement of the gaze from one point to another), (3) vestibular ocular reflex (stabilizing vision by directing the eyes in the opposite direction of head movement), (4) convergence (coordinating movement of the eyes toward the center to merge nearby images), and (5) accommodation (adjusting the focus of the eyes to see objects clearly at different distances).9,11,12 These processes are essential for maintaining stable vision and accurate visual perception in everyday life, but most importantly in sports.13 As such, a vigorous evaluation of visual function during the acute phase of SRC is an important pillar of adequate clinical management, contributing to individualized rehabilitation plans, appropriate referrals when needed, and a safe return to play.
Despite growing evidence of the need for a visual assessment post-SRC, little consensus exists on its use. In fact, in the context of SRC, world-renowned experts meet every few years at the International Conference on Concussion in Sport, with the goal of updating current recommendations for SRC and providing evaluation tools for healthcare professionals, such as the Sport Concussion Assessment Tool (SCAT6).1,14 The SCAT6, whose use is suggested to be optimal within 0–72 hours and up to 1 week post-SRC, consists of a multimodal evaluation including different SRC constructs that can be used to assist clinicians in identifying SRC and also tracking recovery.1,14 Measures such as level of consciousness, coordination, memory, symptoms, cognitive screening, and balance are included.14,15 However, the SCAT6 lacks a comprehensive visual evaluation, likely reflecting a limited body of literature,1 as it is restricted to symptoms and basic eye movements, which does not capture the complexity of oculomotor function.14 The SCOAT6, for its part, is a comprehensive assessment tool that can be administered 72 hours postinjury in a clinical setting. It includes a modified version of the Vestibular Ocular Motor Screening (VOMS), thereby also incorporating a partial assessment of the visual system.16
As outlined earlier, concussion is a prevalent issue in athletics, and previous studies have reported that visual dysfunction is a common consequence of SRC.17,18 These impairments, however, are often completely or partially overlooked during the clinical evaluation of SRC, although they could facilitate diagnosis. Therefore, the primary objective of this systematic review was to report visual assessment tools available in the literature that have been used in the context of SRC evaluation within 7 days. The secondary objective was to identify psychometric properties, such as validity, reliability, specificity, and sensitivity, of these tools when available.
Methods
Protocol
The systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.19 The research question intended to be investigated by the current review was initially verified in various systematic review databases, including Cochrane, Campbell Collaboration, PEDro, and Joanna Briggs Institute, to ensure it has not already been addressed. The review protocol was then registered in PROSPERO and accepted on December 14, 2023 (CRD42023487769).
Eligibility criteria
Original, peer-reviewed research articles published in a scientific journal between 2009 and December 2023, written in English or French, were eligible. Specific inclusion criteria related to the research question were as follows: (1) occurring in a sports context, (2) involving adult and/or pediatric athletic populations, and (3) assessing the visual system (completely or partially) within 0 to 7 days after an SRC. Exclusion criteria were as follows: (1) non-English or French documents and articles published before 2009; (2) abstracts, scientific posters, case studies, expert opinions, consensus statements, conference proceedings; (3) military and nonsport populations; (4) specific ophthalmological evaluations using tools or tests that are not accessible to other healthcare professionals (e.g., Goldmann perimetry and visual evoked potentials); (5) preseason visual assessment or postconcussion syndrome (persistent symptoms); (6) visual evaluations using solely the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) battery; and (7) nonsport-related traumatic brain injuries and moderate to severe traumatic brain injuries. The definition of concussion was significantly redefined at the 3rd International Consensus Conference on Concussion in Sport in 2008,20 which supports solely including articles dating as far back as 2009. Moreover, the ImPACT test battery was excluded as it primarily focuses on cognitive mechanisms that may involve the visual system in relation to concussion, rather than directly assessing deficits in the eyes themselves.21
Information sources
The search strategy was designed by the research team and verified by a university librarian specializing in the field of human kinetics and health sciences. It was launched in the following databases: MEDLINE, CINAHL, Academic Search Complete, and SPORTDiscus. Search strategies were performed in January 2024 by EGL.
Search strategy
The search strategy was based on four key concepts: (1) concussion, (2) sport, (3) evaluation, and (4) vision. A detailed example of the search strategy used in the MEDLINE database can be found in Supplementary File 1. Search results were imported into the Covidence platform for reference management, where duplicate records were identified and removed.22
Selection process
After removing duplicates, titles and abstracts were read with a blinded approach, where eligibility was assessed in Covidence by two independent reviewers (EGL and MD). Disagreements between the reviewers were resolved by a third reviewer (VB). Agreement rate was established at 85%, which was deemed acceptable.23 Similarly, full-text selection followed the exact same evaluation.
Data extraction
To ensure standardization of data extraction, we developed an extraction and quality assessment Excel spreadsheet (Microsoft Excel, version 16.100.1) for use. The following data were extracted from the articles that met the eligibility criteria and displayed in an Excel spreadsheet: authors’ names, publication date, journal, study design, study objectives, visual assessment tool(s), evaluation time point(s), population characteristics, sample size, comparison group, biological sex, sport type, sport level, comorbidities, and visual performance outcomes specific to each assessment tool. Data extraction was performed by two separate researchers (EGL and AP). In case of discrepancies between data extracted, VB acted as a third-party moderator.
Risk of bias assessment
Critical appraisal tools provided by the Joanna Briggs Institute (JBI) were used to assess risk of bias among included articles.24–27 Assessment tools were selected according to the study design of the included research articles, where questions are rated as “yes,” “no,” “unclear,” or “not applicable.” Again, EGL and AP assessed each research article separately based on their design, and VB acted as a third-party reviewer.
Data analysis
Due to the heterogeneity of study designs and objectives, as well as the overall low level of evidence, a narrative analysis was chosen. Results will be analyzed separately according to the visual assessment tool.
Results
Study selection
We retrieved 1,353 articles from database searches and imported them into Covidence (see Figure 1 for PRISMA flow diagram).19,22 After the removal of duplicates (n = 595), 758 articles were screened according to the eligibility criteria. Screening agreement between EGL and MD was 95.4%. Following this stage, 106 full-text articles were then screened by EGL and AP, where the agreement rate was 95.3%. A total of 88 articles were excluded for the following reasons: use of ImPACT exclusively for visual components (n = 33), testing vision >7 days postinjury (n = 28), publication before 2009 (n = 11), nonresearch articles (n = 11), failure to include the target population (n = 4), and failure to focus on the target intervention (n = 1). Ultimately, 18 articles were included in this systematic review.
Study characteristics
Articles included in this review were published between 2011 and 2023. The studies were conducted in the United States (n = 15), United Kingdom (n = 1), Australia (n = 1), and New Zealand (n = 1). The following research designs were included: prospective cohort (n = 10),28–37 retrospective cohort (n = 2),38,39 cross-sectional (n = 4),40–43 case–control (n = 1),44 and case series (n = 1).45 Within our included articles, different visual assessment tools were investigated: VOMS (n = 11),30–33,37,38,40–42,44,45 King–Devick (K–D) test (n = 3),28,34,35 Mobile Universal Lexicon Evaluation System (MULES) (n=1),36 monocular ASL eye tracking (n = 1),43 K–D test combined with VOMS (n = 1),39 and K–D test combined with eye tracking (ET) (n = 1).29
The total sample size ranged from 18 to 3,444 participants = 428), while a total of 2,249 sport-related concussions (SRCs) were analyzed (range: 5 to 549). Of these, 42% (3,025/7,239) were female (range: 0–1,889). Participants’ mean age ranged from 15.3 to 26 years; however, one study did not report the upper age limit of its participants.29
Athletes represented in included articles came from a wide range of sports: football (American, Australian, and flag) (n = 775), soccer (n = 509), rugby (n = 243), ice hockey (n = 170), basketball (n = 94), volleyball (field and beach) (n = 52), cross-country and track and field (n = 48), softball (n = 47), swimming (including diving and synchronized swimming) (n = 37), lacrosse (n = 24), wrestling (n = 23), cheerleading (n = 23), baseball (n = 9), and other sports (n = 401). Some studies did not specify the sport they studied (n = 6).31,37,40,41,43,45 A vast representation of sport levels was depicted in the included articles, ranging from amateur to professional and from high school to university level. Study characteristics are depicted in Tables 1 to 4.
Risk of bias
We assessed risk of bias through critical appraisal tools offered by JBI (see Tables 5–8).24–27 Different checklists were used according to study designs (see Supplementary Files 2–5 for assessment questions based on design). The agreement rate between the two reviewers (EGL and AP) was 72%. In general, the quality of studies was good and included a limited amount of bias. General strengths from articles, regardless of study design, were similarity between groups, adequate statistical analyses, and the use of valid outcome measures. Overall, the key challenges among the included studies were reporting how confounding factors were addressed, the lack of description of follow-up, and strategies for managing losses to follow-up.
Vestibular ocular motor screening
In the articles using VOMS (n = 11),30–33,37,38,40–42,44,45 two articles demonstrated a perfect score,37,45 while nine reported missing or unclear information.30–33,38,40–42,44 When looking at individual study designs, in cohort studies (n = 6),30–33,37,38 the most frequently reported bias was the lack of strategies for confounding factors and the omission of descriptions about the follow-up. Similarly, for the cross-sectional studies (n = 3)40–42 and the case–control study (n = 1),44 the main limitation was also regarding confounding factors.
King–Devick test
Articles using the K–D test (n = 3) were all cohort studies and reported missing or unclear information, such as the absence of strategies for confounding factors and for incomplete follow-up.28,34,35
Other or combined tools
In articles using combined or other visual tools (n = 4),29,36,39,41 one article demonstrated a perfect score,41 while three reported missing or unclear information.29,36,39 All three articles shared the same design (cohort), and the major concern was the absence of descriptions and strategies for confounding factors and for incomplete follow-up.
Evidence synthesis of visual assessment tools
Vestibular ocular motor screening
From our included articles, 12 studied VOMS (11 studied VOMS solely30–33,37,38,40–42,44,45 and 1 studied VOMS combined with K–D39). A VOMS assessment consists of seven components: (1) smooth pursuit, (2) horizontal saccades, (3) vertical saccades, (4) convergence, (5) horizontal vestibular ocular reflex (VOR), (6) vertical VOR, and (7) vestibular motion sensitivity (VMS). Convergence is also objectively assessed as the distance (cm) between the target and the tip of the nose, also known as the near point of convergence (NPC) distance. In addition, attention to the outward deviation of one eye during convergence is considered. Patients rated symptoms (headache, dizziness, nausea, and fogginess) on a scale of 0 to 10 prior to the test and following each test item. As per established guidelines, a total symptom score of 2 on any VOMS component and an NPC measure of 5 cm could be identified as a case of concussion.46
Recovery processes
When specifically looking at vestibular ocular recovery in the context of SRC, Glendon and colleagues (2021) suggested that function recovery occurs approximately 8 days postinjury, as VOMS scores were higher than the reliable change index (RCI; VOMS score = 2) at 2 and 4 days, but not at 8 days, in rugby student-athletes.32 However, other included studies suggested that a positive score on VOMS in the acute phase of SRC can anticipate a lengthy recovery process. Indeed, Sufrinko and colleagues (2017) suggested that higher scores on any VOMS item, particularly smooth pursuit, may predict prolonged recovery in pediatric athletes, which was defined as recovery lasting between 30 and 90 days.33 Whitney and colleagues (2020) pointed out that a score of 2 on any VOMS component predicted a longer time until return-to-play clearance in NCAA athletes.40 These results are also supported by the work of Worts and colleagues (2022), which suggests that symptom provocation during smooth pursuit, horizontal saccades, NPC, and VMS is positively associated with prolonged recovery (odds ratios between 1.533 and 2.274).39 When digging deeper into prolonged recovery, Knell and colleagues (2021) analyzed VOMS performance in pediatric athletes based on biological sex. Their results indicated that test threshold scores of 1 in VOMS were significant predictors of longer recovery time in males, and that an increase of one or more symptoms after any test of the VOMS would increase the expected recovery by 1.38 days. Similarly, among female athletes, VOMS threshold scores between 1 and 5 were associated with a longer recovery, and that an increase of one or more symptoms on any VOMS test increased the expected recovery by 1.73 days.45
Clinical cutoffs
The study by Elbin and colleagues (2018) allowed for the identification of more concussed athletes using clinical cutoffs 2 symptoms on any VOMS component and/or an NPC distance of 5cm) than when using the change score method (i.e., the difference between total symptoms on VOMS post- and pretest) between 1 and 7 days post-SRC.30 Similarly, Tomczyk and colleagues (2021) reported that concussed athletes scored higher than clinical cutoffs on the horizontal VOR, vertical VOR, and VMS components, while they scored lower on smooth pursuit and NPC distance.42
Other results
Two studies both demonstrated that when performing VOMS in the acute phase post-SRC, VOMS total scores are higher in the SRC group versus uninjured controls in adolescent and collegiate athletes.37,41 In addition, it was also suggested that VOMS total scores were higher post-SRC (acute phase) than at baseline in both high school and NCAA athletes, whereas NPC distance was significantly higher post-SRC in NCAA athletes when compared to preinjury scores.30,31 However, Ferris and colleagues (2022) mentioned that despite being statistically significant, these changes in NPC scores had moderate to little clinical significance.31 Furthermore, the latter demonstrated that females had higher symptom provocation than males between time points in VOMS, while Teramoto and colleagues (2022) showed that in college varsity athletes, only concussed females had significant changes in smooth pursuit and horizontal and vertical saccade scores after injury compared with concussed males.38
Psychometric data
Elbin and colleagues (2022) presented several VOMS cutoff scores capable of predicting concussed athletes, which are: overall VOMS score 3 (sensitivity = 64%, specificity = 74%) and an NPC distance of 3 cm (sensitivity = 51%, specificity = 74%). They also reported a three-factor model that exhibited moderate accuracy (area under the curve [AUC] = 0.76), consisting of the combination of: (1) an NPC distance of 3 cm, (2) a vertical VOR change score of 1, and (3) a VMS change score of 1.37 These findings are supported by Ferris and colleagues (2022), suggesting that when comparing VOMS total score to concussion identification batteries (SCAT3 and ImPACT), the former had the highest predictive utility for identifying concussion.31 Findings by Kontos and colleagues (2021) partially agree with these findings, suggesting that each individual VOMS component, except for VMS and NPC distance, successfully identified concussed collegiate athletes over healthy controls.44 Finally, Knell and colleagues (2021) studied VOMS validity in identifying protracted or prolonged recovery (defined as >30 days) in pediatric athletes by evaluating the performance of different symptom threshold scores (ranging from 1 to 10). In general, sensitivity is inversely associated with symptom scores, whereas specificity tends to increase alongside symptom increase, but when looking at the predictive ability of VOMS, it was suggested that VOMS does not predict prolonged recovery.45
King–Devick test
Among our included articles, five articles studied K–D (three studied K–D solely,28,34,35 one combined K–D and VOMS,39 one combined K–D and an ET device).29 The K–D test consists of reading aloud three test cards with progressively increasing difficulty, each containing sequences of numbers, as fast as possible without making any errors; time and number of errors are recorded.47 The best score from two error-free trials is compiled at baseline, and a single trial is administered postconcussion.47
Score difference between SRC group and baseline or non-SRC group
Two studies indicated that K–D score is altered in the event of SRC. Indeed, when comparing post-SRC K–D scores to preinjury values, K–D time scores are slower.28,34 In contrast, Hecimovich and colleagues (2022) did not report such differences in recovery time when comparing concussed and nonconcussed individuals from similar populations.29
Recovery processes
When looking at the K–D scores recovery trajectory after SRC, Symons and colleagues (2023) suggested that significant improvements in time occur between 2 and 6 days postinjury.35 Regarding recovery duration, Worts and colleagues (2022) showed that the experimental group of individuals with prolonged recovery exhibited significantly slower time to complete the test measurements than the group consisting of individuals with typical recovery post-SRC.39
Psychometric data
Hecimovich and colleagues (2022), who studied VOMS in collegiate rugby athletes at three distinct time points (baseline, post-SRC, and end of season), indicated that K–D completion time had high specificity (86%) for diagnosing concussion in collegiate athletes but a poor sensitivity (40%).29
Other tools
Eye-tracking devices
Of the included articles, two studied ET devices: one combined ET with the K–D test,29 while the other combined ET and soccer game task on Wii Fit.43 Hecimovich and colleagues (2022) used an infrared-based video-oculographic rig fixated on a computer (120-Hz VT3-Mini; EyeTech Digital Systems) and tracked eye movement while the participants performed the K–D test. Total fixation, total saccades, average saccade velocity, blinks, saccade latency, fixation duration, and fixation polyarea were analyzed.29 Murray and colleagues (2014) used a monocular ASL ET system (model H6, Applied Science Laboratories, Bedford, MA), which captures gaze deviations and percentage of time on center, based on the left eye.43
Hecimovich and colleagues (2022) showed no difference in ET outcome measures between post-SRC and controls in collegiate rugby athletes and concluded that none of these can diagnose concussion because of insufficient specificity and sensitivity.29
Murray and colleagues (2014) reported that the SRC group had a significantly greater number of gaze deviations from the center compared to the nonconcussed group among adolescent and young adult athletes. In addition, they found a high negative correlation between the percentage of time on center and soccer game (Wii Fit) score in the SRC group, indicating that soccer game scores decreased as the percentage of time spent on center increased. In contrast, this correlation was positive for the nonconcussed group.43
Mobile Universal Lexicon Evaluation System
Fallon and colleagues (2019) studied the MULES, which consists of naming out loud 54 pictures of fruits, objects, and animals being presented on a laminated sheet. They found a significant worsening of MULES time score post-SRC compared to that at baseline in a multisport, multilevel group of athletes.36
Discussion
The primary objective of this systematic review was to identify and evaluate visual assessment tools used during the acute phase (<7 days) of SRC. A total of 1,353 articles were retrieved from four databases, of which 18 met the inclusion criteria and were included in this review.28–45 Among the identified articles, VOMS was the tool that was most frequently studied. Four studies suggested that greater symptom provocation score on the VOMS could predict a longer time to return to play and prolonged recovery (>30 days) in athletes.33,39,40,45 These findings align with those of a previous systematic review, which suggested that a positive VOMS appears to predict prolonged recovery in concussion patients.48 However, these results contrast those reported by Glendon and colleagues (2021), who suggested that impairments in vestibular ocular motor function, measured through VOMS should resolve by 8 days post-SRC in a small sample of adult rugby athletes.32 In addition, our results showed that concussed athletes exhibited higher VOMS scores during the acute post-SRC phase compared with healthy individuals, with scores often exceeding clinical cutoff values.37,41,42 These findings are supported by the review conducted by Kaae and colleagues (2022), which reported similar results in individuals postconcussion compared with healthy controls, with similar results with regard to clinical cutoffs.49 Following similar literature trends in the context of SRC, our review suggests that both biological sexes may behave differently on the task, with females exhibiting more significant changes in VOMS than their male counterparts.31,38 This phenomenon could be explained by the discrepancies in symptom reporting across sexes, where females report more symptoms than males after SRC, and seem to report more symptoms related to vision, such as sensitivity to light and dizziness.50,51
The second most frequently used tool in the context of visual assessment in acute SRC was the K–D test. Mixed results were presented by our review,28,29,34 but the majority align with available literature, suggesting that concussed athletes perform the K–D test approximately five seconds slower compared to their baseline scores.47,52 Furthermore, one research group included in this review proposes an association with prolonged recovery and slower time in K–D.39 Those conclusions are in line with a previous study suggesting that a slower time in K–D between 0 and 2 days after injury is associated with a longer return to play.53 In repeated assessments, our findings suggest an improvement in K–D time between 2 and 6 days after SRC in adult athletes,35 a process consistent with concussion recovery timelines.54 However, it remains unclear whether this improvement is attributed to learning effects of the task or natural recovery.55 Limited evidence on ET devices was available, with only two articles identified through this systematic review. Our findings suggest mixed results, where one article reported no significant results between post-SRC group and controls when looking at eye movements during a K–D task,29 while the second article illustrated significant differences in gaze deviations from center between similar groups.43 These last results may in part be explained by a vestibular ocular reflex disruption that can cause blurred vision, balance disorder, or dizziness.56 Finally, the only article that studied MULES36 reported a significant worsening score, measured in time, between post-SRC than baseline. Parallels from our findings to existing literature are limited on this tool due to its relatively recent emergence.57
The secondary objective of this systematic review was to identify psychometric qualities of included visual assessment tools, when available. Among our included articles, 4 articles provided psychometric data for VOMS,31,37,44,45 while one provided psychometric data for the K–D test in combination with an ET device.29 Results from our review suggest that the VOMS is a sensitive tool for concussion assessment, demonstrating the ability to identify concussed athletes during the acute phase following injury.31,37,44 Furthermore, emerging evidence suggests that revised clinical cutoff values may enhance the sensitivity of the assessment.37 Specifically, a total VOMS symptom score of 3, or a combination of three precise cutoff values, has been proposed: (1) an NPC distance of 3 cm, (2) a vertical VOR change score of 1, and (3) a VOMS change score 1. However, it should be noted that an NPC value below 3 cm is generally lower than the typical average observed in the population.58 Therefore, caution is warranted when using this threshold, and a comprehensive VOMS assessment should be ensured. In addition, the results from our study failed to predict prolonged recovery despite evidence suggesting adequate sensitivity for identifying SRC.45 Finally, our findings reported that the K–D test failed to diagnose concussion in one study,29 which contrasts with the meta-analysis published by Galetta and colleagues (2016), proposing that the K–D test has a high sensitivity and specificity for distinguishing concussed athletes from healthy controls.47
Clinical application
Evidence from this systematic review supports the idea that there may also be an added value of visual assessment tools within acute SRC test batteries. Indeed, healthcare professionals, such as athletic trainers, physical therapists, and other professionals involved in sport, may enhance their clinical practice by including a visual assessment tool such as the VOMS when assessing concussed athletes within the first 7 days postinjury. It should, however, be noted that while the VOMS can aid in concussion diagnosis, it does not replace a multimodal evaluation, as all components, including symptoms, memory, concentration, balance, and other domains, are crucial when assessing an athlete with a potential concussion.1 Even though this test could extend the acute evaluation in terms of time, VOMS can provide additional information about deficits and dysfunctions that could provide insightful information to clinicians and should be considered during concussion rehabilitation, particularly in sporting contexts. Furthermore, some athletes, particularly those participating in less structured competitive environments, do not always have access to clinical follow-up after an on-field SRC assessment.59,60 Early evaluation of visual deficits may therefore contribute to improved prognosis. Moreover, because it remains unclear which VOMS component best discriminates concussed athletes, and to ensure a more comprehensive assessment of visual impairments, it may be preferable to include the full VOMS in concussion clinical tools, rather than its abbreviated version. Consequently, it is reasonable to suggest that the VOMS, or other validated objective measures of visual function, should be incorporated into the multimodal assessment of acute SRC.
Summary of limitations and future research perspectives
A few key points with the potential to benefit future research have been highlighted through our systematic review. First, about one-fifth of the included studies came from the same group of researchers, suggesting potential overrepresentation of certain populations in our review. Hence, reproducing the methodologies of these studies in different populations and contexts may contribute to enhancing the applicability of results. Our study identified various discrepancies in literature regarding the visual assessment of concussion across sex, athletic status, and age groups. To allow for better identification and care of SRC, these discrepancies should be further studied. As such, sex differences were noted in only a limited number of studies, as only two articles conducted sex-based analyses, despite it currently being widely recognized that biological sex plays a crucial role in concussion. Future studies should continue to address these potential disparities. Furthermore, when considering the VOMS clinical cutoff scores, concussed athletes generally appear to score above the current clinical cutoffs established. Notably, one article proposed revised cutoff values to improve diagnostic accuracy. We recommend that future research further examine these proposed cutoffs in athletic populations to allow for necessary adjustments, if need be. With regard to age-related differences, future studies should investigate the use of the K–D test in the pediatric population, as a means to establish whether or not the pediatric literature matches the adult literature. Ultimately, more data are needed on ET devices and MULES tool to draw stronger conclusions regarding their effectiveness.
Among the limitations of this systematic review, the heterogeneity of the included studies and their generally low levels of evidence limited the synthesis to a narrative approach. Consequently, despite rigorous efforts to ensure objectivity, the interpretation of the results remains inherently subjective. Finally, despite registration in PROSPERO and providing an overview of the review process, no protocol was published.
Conclusion
Our systematic review suggests that VOMS can identify concussed athletes in the acute phase of SRC, but because of result disparities, its ability to predict prolonged recovery remains inconclusive. It may be beneficial to healthcare professionals to include this tool in their multimodal concussion evaluation battery. More data are needed for K–D, ET, and MULES to establish their role in assessing concussed athletes.
Acknowledgments
The authors acknowledge the support of Véronique Lavergne, librarian at the Université du Québec à Trois-Rivières, for assistance with the literature search.
Disclosures
The authors report no disclosures.
Corresponding author
Laurie-Ann Corbin-Berrigan, Department of Human Kinetics, Université du Québec à Trois-Rivières, Trois-Rivières, QC, Canada, laurie-ann.corbin-berrigan@uqtr.ca
Protocol registration
Our systematic review protocol was accepted on December 14 by PROSPERO (CRD42023487769).
URL: https://www.crd.york.ac.uk/PROSPERO/view/CRD42023487769