==== Front Arch Dis Child Arch Dis Child archdischild adc Archives of Disease in Childhood 0003-9888 1468-2044 BMJ Publishing Group BMA House, Tavistock Square, London, WC1H 9JR 37001968 archdischild-2022-325202 10.1136/archdischild-2022-325202 Original Research 1506 Factors related to adverse long-term outcomes after mild traumatic brain injury in children: a scoping review http://orcid.org/0000-0001-5727-1790 Ijaz Sharea 1 Scott Lauren 1 Dawson Sarah 1 Wilson Rebecca 1 Jackson Joni 1 Birnie Kate 2 Redaniel Maria Theresa 1 Savović Jelena 1 Wright Ingram 3 http://orcid.org/0000-0002-8634-7210 Lyttle Mark D 45 http://orcid.org/0000-0002-0306-4750 Mytton Julie 6 1 NIHR ARC West, Population Health Sciences, University of Bristol, Bristol, UK 2 Population Health Sciences, University of Bristol, Bristol, UK 3 School of Psychological Science, University of Bristol, Bristol, UK 4 Emergency Department, Bristol Royal Hospital for Children, Bristol, UK 5 Research in Emergency Care Avon Collaborative Hub (REACH), University of the West of England, Bristol, Avon, UK 6 School of Health and Social Wellbeing, University of the West of England, Bristol, UK Correspondence to Dr Sharea Ijaz, NIHR ARC West, Population Health Sciences, University of Bristol, Bristol BS8 1QU, UK; s.ijaz@bristol.ac.uk MDL and JM are joint senior authors. 6 2023 31 3 2023 108 6 492497 04 12 2022 16 3 2023 © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ. 2023 https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. Objective To identify demographic, premorbid and injury-related factors, or biomarkers associated with long-term (≥3 months) adverse outcomes in children after mild traumatic brain injury (mTBI). Design Scoping review of literature. Patients Children and adolescents with mTBI. Risk factors Any demographic, premorbid and injury-related factors, or biomarkers were included. We excluded genetic and treatment-related factors. Main outcome measures Postconcussion syndrome (PCS), recovery. Results Seventy-three publications were included, reporting 12 long-term adverse outcomes, including PCS in 12 studies and recovery in 29 studies. Additional outcomes studied were symptom scores/severity (n=22), quality of life (n=9) and cognitive function (n=9). Forty-nine risk factors were identified across studies. Risk factors most often assessed were sex (n=28), followed by age (n=23), injury mechanism = (n=22) and prior mTBI (n=18). The influence of these and other risk factors on outcomes of mTBI were inconsistent across the reviewed literature. Conclusions The most researched risk factors are sex, age and mechanism of injury, but their effects have been estimated inconsistently and did not show a clear pattern. The most studied outcomes are recovery patterns and symptom severity. However, these may not be the most important outcomes for clinicians and patients. Future primary studies in this area should focus on patient-important outcomes. Population-based prospective studies are needed that address prespecified hypotheses on the relationship of risk factors with given outcomes to enable reliable prediction of long-term adverse outcomes for childhood mTBI. adolescent health child health syndrome NIHR ARC West special-featureunlocked ==== Body pmcWHAT IS ALREADY KNOWN ON THIS TOPIC Mild traumatic brain injury (mTBI) is common in childhood and can lead to prolonged symptoms in about one-third of children. Persisting symptoms can hinder development and reduce quality of life. There is a dearth of predictive tools and limited evidence on factors placing a child at risk of developing prolonged symptoms. WHAT THIS STUDY ADDS This study collated potential demographic, premorbid and injury-related factors, or biomarkers for long-term adverse outcomes of childhood mTBI. Forty-nine risk factors for 12 different outcomes were identified across 73 studies. The associations between any of the risk factors and adverse outcomes were not consistent. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY The inconsistency of findings indicates a need for consensus on definitions underpinning measurement. Robust primary studies that follow-up children with mTBI long-term are required to reliably predict adverse outcomes. Introduction Almost half a million children attend hospital annually after a traumatic brain injury (TBI) in the UK.1 More than 90% are mild,2 although the definition of ‘mild’ varies, and there is no consensus on severity thresholds based on symptoms and signs.3 Symptoms of mild TBI (mTBI) can persist for several months (postconcussion syndrome (PCS))4 in up to one-third of patients. PCS lacks a widely accepted definition, with different criteria used for diagnosis (Diagnostic and Statistical Manual of Mental Disorders, fourth edition and International Classification of Diseases 10).5 It presents with subjective physical complaints (eg, headache, dizziness), and cognitive, emotional and behavioural changes. These symptoms can appear early or late after the injury, may become chronic or permanent and negatively impact development and quality of life for affected children.6 Research on mTBI pathophysiology has explored links between symptoms and potential individual or environmental factors.4 7 8 mTBI can result in disturbed neurotransmission which, when combined with personal or environmental characteristics, can lead to different types and durations of symptoms post injury (figure 1). Figure 1 Mild traumatic brain injury (mTBI) and how potential factors may affect symptoms after mTBI. PCS, postconcussion syndrome. There is no widely accepted, validated prediction tool to identify children at risk of developing long-term sequelae of mTBI. Limited evidence on syndrome characterisation precludes developing interventions for PCS.9 Knowing who to target would help develop and refine interventions to prevent or treat symptoms and lower morbidity. In this review, we aimed to identify factors associated with long-term adverse outcomes of mTBI from published research and identify key areas for future research. Objective To identify from the literature the demographic, premorbid and injury-related factors, or biomarkers associated with long-term (≥3 months) adverse outcomes in children after mTBI. Methods We followed accepted methods for scoping reviews and used an iterative process to define research questions, extract data and summarise results.10–12 We report the review as per accepted guidelines.13 We included observational studies reporting any demographic, premorbid and injury-related factors, or biomarker risk factors for adverse outcomes 3 months or longer after mTBI in children under 18 years. We searched three electronic databases and references lists of included studies and published systematic reviews to identify peer reviewed and grey literature in January 2022. Screening of titles and abstracts and full texts was done in duplicate. Data extraction was done by one author, and the data items included study design, author, location, year of publication, participants, risk factors identified or studied and outcome(s). We did not extract effect estimates and did not perform risk of bias assessments. Findings were summarised into a table of risk factors studied for each outcome and in figures presenting long-term adverse outcomes and risk factors studied in literature respectively. A stakeholder consultation helped refine the synthesis and findings. Detailed methods are available in online supplemental file. 10.1136/archdischild-2022-325202.supp1 Supplementary data Results Search results and selection Of 8039 unique references, 678 underwent full-text assessment, and 73 publications were included (see online supplemental table of characteristics of included studies). Most (n=42) originated from the USA, followed by Canada (n=14), Europe (n=6) and Australia (n=5), and most were from secondary care settings (n=50). The median sample size was 146 participants (IQR 72–285). Publication dates ranged from 1999 to 2022, with the latest cohort enrolled between 2015 and 2021. Male participants were more common (>50% males) in 46 studies. Median age was 13.6 years (IQR 12–15) across the 64% of included studies reporting mean age. Half the studies reported race, in which participants were mostly white (median 75%; IQR 68%–84%). Outcomes assessed Our primary outcome PCS was reported in 12 studies only, though descriptions and definitions of PCS differed (table 1). Table 1 Definitions of postconcussion syndrome used across included studies reporting this outcome Study ID: author date PCS definition and measurement reported Babcock 2013 Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSMIV): presence of three or more symptoms on the Rivermead Post Concussion Symptoms Questionnaire (RPQ) that were rated as worse (score of >2) than before mTBI at 3 months Chendrasekar 202036 Author defined: questionnaire assessing presence of any concussion symptoms; measured 4–68 months after mTBI Corwin 2020 International Classification of Diseases (ICD) 10 definition: symptoms that persisted beyond 28 days following mTBI; measured at 28 days and 3 months Durish 2019 ICD 10 definition; presence of one or more symptoms reported to be associated with the concussion that persist for longer than 1 month post-mTBI; measured at 28 days and 3 months Gravel 2020 ICD 10 definition: an increase of at least three symptoms on the child Post-Concussion Symptom Inventory as compared with the child’s baseline behaviour prior to mTBI at 1 week; measured at 1, 4 and 12 weeks Haase 2015 DSMIV definition: presence of three to six symptom categories occurring within 3 months post-mTBI and evidence of neuropsychological dysfunction Howell 201814 ICD definition: symptoms lasting more than 28 days; measured at 3 months post-mTBI Jeckell 201937 DSMIV definition: presence of 3 or more symptoms that lead to impairment in functioning and last no less than 3 months post-mTBI Kelmendi 2021 DSMIV definition: the presence of 3 or more symptoms on the RPQ scaler that rated as worse (score of ≥2) than at preinjury, at 3 months post-mTBI Olsson 2013 DSMIV definition: a measure of PCS was derived from parent’s responses on the Child Behaviour Checklist (CBCL), by scoring only the items on CBCL that matched on face validity to one of the Post-Concussion Disorder (PCD) symptoms in criterion C of PCD research criteria in DSMIV Preiss-Farzanegan 2009 DSMIV definition: the presence, nature and extent of postconcussive symptoms on RPQ scale, administered over the telephone 3 months post-mTBI Riemann 2021 ICD 10 definition; at least 3 of the following symptoms: headaches, dizziness, sleep disturbance, fatigue, being irritable/easily angered, forgetfulness/poor memory and poor concentration on RPQ scale (severity rating score ≥2); measured at 3 and 6 months mTBI, mild traumatic brain injury; PCS, postconcussion syndrome. Symptom severity or scores (rather than presence of a set of symptoms) were reported in 22 studies, using various scales. Recovery was reported in 29 studies. Other outcomes were reported less frequently (figure 2). Figure 2 Map of long-term outcomes of childhood mTBI in literature. The size of the block indicates the relative size of literature on the outcome, with numbers of studies reporting each. mTBI, mild traumatic brain injury. Follow-up schedules varied, with 3-month outcomes reported most often (n=43); the longest follow-up was 7 years. Risk factors Forty-nine risk factors were reported across 73 studies, of which sex (28; 37%), age (23; 31%) and injury mechanism (22; 30%) were most frequently assessed. Fourteen factors were assessed in single studies only (figure 3). Figure 3 Risk factors for long-term outcomes of childhood mTBI in literature. mTBI, mild traumatic brain injury; PCS, postconcussion syndrome; 5P risk score.Predicting and Preventing Post-concussive Problems in Pediatrics risk score; SES, Socioeconomic status; A&E, Accident and Emergnecy; GCS, Glasgow coma scale; CT/MRI, Computerised tomography/Magnetic resonance imaging. Relationship of outcomes with risk factors Postconcussion syndrome Twelve studies assessed effect of risk factors on PCS occurrence. Evidence was inconsistent for age and sex, assessed in three and four studies, respectively. Premorbid anxiety and depression were assessed in two studies each and were unrelated to PCS in both. All other factors were assessed in single studies (see online supplemental table of risk factors). Severity of symptoms Twenty-two studies reported symptom severity scores. Evidence was inconsistent for sex, age, parental education, SES, prior mTBI, prior mental ill health, mechanism of injury and ADHD. Immediate postinjury sleep problems, low resilience, high PTSD symptoms and high serum S100B levels within 6 hours of injury in single studies were reported as related to greater PCS symptoms. Other factors were unrelated to symptom severity ((see online supplemental table of risk factors). Recovery Twenty-nine studies reported recovery trajectory (online supplemental table of risk factors), exploring factors including prior mTBIs, injury mechanism, age, sex, premorbid headaches, prior learning difficulties and loss of consciousness. Studies reporting poor recovery found it to be predicted by high postinjury PCS scores (n=2) and postinjury parental distress (n=3). Single studies assessing delayed recovery found this was predicted by higher composite post-mTBI risk scores (5P score),14 delayed diagnosis, low resilience, higher depression and internalising symptoms, amnesia, continued activity participation, injury severity and acute post-mTBI fatigue. Cognitive function Nine studies reported cognitive outcomes. Evidence was inconsistent on age, sex, SES, ethnicity and MRI findings. Rural residence, preinjury attention deficit hyperactivity disorder (ADHD), prior cognitive problems, absence of headache at presentation and higher serum S100B after mTBI were linked to poor cognitive outcome in single studies (online supplemental table of risk factors). Quality of life (QOL) Nine studies reported QoL. High immediate post-mTBI PCS symptoms, prior parental distress and poor parent child interactions were associated with poor QoL outcomes. Evidence was inconsistent on age, sex, SES and injury mechanism. Mental health outcomes Poor mental health outcomes, reported by seven studies, were predicted by high immediate post-mTBI PCS symptoms in two studies and by premorbid anxiety/depression, low SES, low resilience, and weaker connectivity on MRI in single studies. There was inconsistent evidence on effect of sex and prior mTBI (online supplemental table of risk factors). All other outcomes and associated risk factors are listed in online supplemental table of risk factors. Risk factors not assessed for any outcome Predefined risk factors that we did not identify in the literature for any outcome were parental drug or alcohol abuse, family size or social services involvement. Discussion We identified 49 risk factors across 73 publications, of which 14 were only assessed in single studies. Four factors, preidentified as potentially relevant, were not evaluated in any studies. While sex and age were reported in more than 20 studies each, findings across studies were disparate. Overall, girls seemed to have poorer outcomes, similar to recent evidence indicating girls are more likely to suffer symptoms after mTBI and recover later.15 Results for age were more varied: four studies reported either older or younger age as a risk factor for poorer outcomes, while five found age was not associated with outcomes. Different cut-offs for age groups (eg, <10 vs ≥10 years; <13 vs ≥13 years) have been tested in primary studies, creating difficulties in evaluating the influence of age on consequences of mTBI across studies. To enable reliable predictions of outcomes by age we need large follow-up studies with a priori hypotheses and agreement across researchers for appropriate age cut-offs. Data on some demographic factors such as SES, family function and ethnicity were sparse, and findings were inconsistent. Since these wider determinants are known to modify many health outcomes and behaviours,16–18 these should be better examined in future studies, for example, by defining these a priori, measuring at baseline using valid scales and testing their causal relationship with different adverse outcomes. Including these measures as a minimum data set in future studies (or routine data collection at healthcare interaction) would amplify potential for meta-analyses of future work, even if individual studies are not sufficiently powered. The next most commonly studied factor was mechanism of injury (n=22). There were inconsistent effects from different mechanisms of mTBI, although road traffic injuries were found by some to be predictive of poorer outcome. Prior mTBI was unrelated to poor outcomes in 12 out of 18 studies assessing this, and the only outcome it consistently predicted was persistent headaches (n=3). Evidence on all other risk factors was also inconsistent; presence or absence of these factors did not always predict similar outcome patterns across studies. Several injury-related factors are easily measurable at presentation postinjury. However, measurement is often variable, for example, proxy versus self-rated symptoms versus clinician assessment, which may explain inconsistent findings. Blood biomarkers have been increasingly suggested as potential predictors for recovery from mTBI.19 However, this is based on animal or in vitro models. Restricted to human studies, evidence on biomarkers was scarce (n=2) with higher levels of S100B postinjury related to poor outcomes. Several others (eg, IL6, glial fibrillar acidic protein; ubiquitin C-terminal hydrolase-L1; myelin basic protein; neuron-specific enolase; and prostaglandin D synthase) can be measured using blood tests at presentation. A recent evidence review to inform guidance on prognosticating long-term adversity using blood and MRI found limited evidence,20 with a consequent recommendation that biomarkers be researched as potential indicators of later outcomes in robust studies.20 21 An ongoing study is assessing their prognostic potential in delayed recovery from mTBI in children presenting at hospital emergency departments.22 Similar studies in other settings and populations for important outcomes are needed to fill the gaps in the evidence base. Most studies relied on retrospective accounts of preinjury difficulties, which have inherent potential for recall bias. From included studies and stakeholder consultations, it seems symptoms commonly reported after mTBI (sleep/concentration problems, headaches) may already be present prior to injury. Baseline (preseason) testing, as undertaken in some sports in regions such as the USA, allows assessment of change in symptoms on comparable measures and recording of any existing risk factors. Such prospective surveillance (measuring demographic and potential risk factors as well as current existence of any symptoms such as headaches that can be considered a post mTBI outcome) in school level sports and its use in future research can improve reliability of post mTBI findings as new or worse symptoms, facilitating reliable relating of postinjury findings to baseline risk factors. Healthcare services in many settings do not currently follow-up children long-term post-mTBI; were this to happen, the understanding of the natural progression of outcomes following mTBI would be greatly enriched. These measurements could be part of a core outcome set for implementation in the UK and other healthcare systems – either collated by the clinician in Electronic Health Records or by patients/families in a mobile device application (as was done during COVID). Comparison with other reviews We found 15 systematic reviews of one or more risk factors for various mTBI outcomes.20–34 Eligibility criteria for these reviews varied and follow-up was not well defined, leading to diverse findings. For example, two reported older children had poorer outcomes15 16; however, these included different age ranges (>20 years vs 2–18 years), outcomes (PCS vs quality of life) and methods, so comparisons are more nuanced. All reviews found the quality low and data sparse for any risk factor and outcome relationship, and these also recommended large representative cohort studies to establish risk factors. Because some factors (eg, known to social services, benefit receipt, social class) have different meanings across the world, we consider it important that country or region-specific cohort studies are conducted to establish the value of risk factors for specific outcomes. As most children recover within 3 months, future studies to identify children less likely to recover should have longer follow-up periods after mTBI. To this end, our review’s findings will inform a study using UK primary and secondary care records.35 This scoping review explored evidence reporting associations of demographic, premorbid and injury-related factors with adverse outcomes following mTBI and whether biomarkers are potential predictors. The inconsistency of findings indicates a need for consensus on definitions underpinning measurement of potential risk factors and outcomes and for studies specifying a priori hypotheses and including baseline measures where feasible. The role of biomarkers appears under-researched as does our understanding of behavioural responses of children, their parents and healthcare providers to post-mTBI symptoms, which may improve our understanding of why such variation has been found to date. Limitations This was not a systematic review. As such, we did not perform study bias assessments or pooling of effects across studies. Our aim was to scope existing literature for all factors studied to date as potential risk factors for specific outcomes. While we identified 49 potential factors, the evidence is limited for any of these, and several prespecified potentially relevant factors are missing from existing research. We included all ‘author-defined mTBI’ to scope the full breadth of the evidence, but a disadvantage of this is substantial heterogeneity across studies (eg, different inclusion thresholds for CT abnormalities). We did not address moderate or severe TBI as these often require active management, whereas mTBI is expected to resolve spontaneously. mTBI is especially important to study as this is the severity ascribed to most children, and identifying those who will experience long-term symptoms is challenging for clinicians. Conclusion In the substantial research on risk factors associated with poor long-term outcomes of mTBI, the three most researched are sex, age and mechanism of injury. However, their effects have been measured variably and do not show a clear pattern. The most commonly reported outcomes of recovery and symptom severity may not be the most important outcomes for clinicians and patients, and a collaborative core outcome set should be developed. Future studies should correlate risk factors with prioritised outcomes in high-quality primary observational studies with follow-up of several months duration. True quantification of the impact of mTBI in childhood will only be possible if preinjury data are routinely collected, either by healthcare systems, organised sports or self-report. Research is also needed to clarify the severity of some risk factor categories, such as some age groups or some injury mechanisms for relationship with worse outcomes. We are grateful for the contribution of our patient stakeholders in the interpretation of review findings. Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information. Ethics statements Patient consent for publication Not applicable. Ethics approval Not applicable. Twitter: @mdlyttle Contributors: SI, LS, SD, JM, MDL, MTR and JS contributed to design of the review and searches; SI, LS, SD and RW contributed to selection and data extraction. SI led the synthesis and drafting of paper with all authors contributing in both stages and approving the final manuscript. JM and MDL are joint senior authors. SI is the guarantor of the study. Funding: This work was funded by the The National Institute for Health and Care Research (NIHR) Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston National Health Service (NHS) Foundation Trust. Disclaimer: The views expressed in this article are those of the authors and do not necessarily represent those of the NHS, the NIHR, or the Department of Health and Social Care. Competing interests: SI, LS, RW, SD, JJ, MTR, and JS report grant funding from NIHR (NIHR ARC West) during the conduct of the study. JS reports personal fees from Core Models Limited, UK (for teaching introductory systematic review methods at an online course), unrelated to the submitted work. Provenance and peer review: Not commissioned; externally peer reviewed. Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise. ==== Refs References 1 National Clinical Guideline C . National Institute for Health and Clinical Excellence: guidance. head injury: triage, assessment, investigation and early management of head injury in children, young people and adults. London: National Institute for Health and Care Excellence (UK) Copyright © National Clinical Guideline Centre, 2014. 2 Cassidy JD , Carroll L , Peloso P , et al . Incidence, risk factors and prevention of mild traumatic brain injury: results of the who collaborating centre task force on mild traumatic brain injury. J Rehabil Med 2004;36 :28–60. 10.1080/16501960410023732 15074435 3 Crowe LM , Hearps S , Anderson V , et al . Investigating the variability in mild traumatic brain injury definitions: a prospective cohort study. Arch Phys Med Rehabil 2018;99 :1360–9. 10.1016/j.apmr.2017.12.026 29407521 4 Kobeissy F . Brain neurotrauma. In: Kobeissy F , ed. Pathophysiology of mild TBI: implications for altered signaling pathways. Boca Raton (FL): CRC Press/Taylor & Francis, 25 February 2015. 10.1201/b18126 5 Permenter CM , Syndrome SAP . Postconcussive syndrome. In: StatPearls. Treasure Island (FL): StatPearls Publishing LLC, 2019. 6 Sariaslan A , Sharp DJ , D’Onofrio BM , et al . Long-Term outcomes associated with traumatic brain injury in childhood and adolescence: a nationwide Swedish cohort study of a wide range of medical and social outcomes. PLOS Med 2016;13 :e1002103. 10.1371/journal.pmed.1002103 27552147 7 Kenzie ES , Parks EL , Bigler ED , et al . The dynamics of concussion: mapping pathophysiology, persistence, and recovery with causal-loop diagramming. Front Neurol 2018;9 :203. 10.3389/fneur.2018.00203 29670568 8 Kenzie ES , Parks EL , Bigler ED , et al . Concussion as a multi-scale complex system: an interdisciplinary synthesis of current knowledge. Front Neurol 2017;8 :513. 10.3389/fneur.2017.00513 29033888 9 Maas AIR , Menon DK , Adelson PD , et al . Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research. Lancet Neurol 2017;16 :987–1048. 10.1016/S1474-4422(17)30371-X 29122524 10 Arksey H , O’Malley L . Scoping studies: towards a methodological framework. International Journal of Social Research Methodology 2005;8 :19–32. 10.1080/1364557032000119616 11 Gottlieb M , Haas MRC , Daniel M , et al . The scoping review: a flexible, inclusive, and iterative approach to knowledge synthesis. AEM Educ Train 2021;5 :e10609. 10.1002/aet2.10609 34222749 12 Levac D , Colquhoun H , O’Brien KK . Scoping studies: advancing the methodology. Implement Sci 2010;5 :69. 10.1186/1748-5908-5-69 20854677 13 Tricco AC , Lillie E , Zarin W , et al . PRISMA extension for scoping reviews (PRISMA-scr): checklist and explanation. Ann Intern Med 2018;169 :467–73. 10.7326/M18-0850 30178033 14 Howell DR , Zemek R , Brilliant AN , et al . Identifying persistent postconcussion symptom risk in a pediatric sports medicine clinic. Am J Sports Med 2018;46 :3254–61. 10.1177/0363546518796830 30265817 15 Bretzin AC , Covassin T , Wiebe DJ , et al . Association of sex with adolescent soccer concussion incidence and characteristics. JAMA Netw Open 2021;4 :e218191. 10.1001/jamanetworkopen.2021.8191 33904911 16 Marmot M , Allen J , Boyce T , et al . Health equity in england: the marmot review 10 years on. BMJ 2020;368 :m693. 10.1136/bmj.m693 32094110 17 Wen LM , Simpson JM , Baur LA , et al . Family functioning and obesity risk behaviors: implications for early obesity intervention. Obesity (Silver Spring) 2011;19 :1252–8. 10.1038/oby.2010.285 21127478 18 Zimmerman FJ , Bell JF . Income inequality and physical and mental health: testing associations consistent with proposed causal pathways. J Epidemiol Community Health 2006;60 :513–21. 10.1136/jech.2005.040154 16698982 19 Gan ZS , Stein SC , Swanson R , et al . Blood biomarkers for traumatic brain injury: a quantitative assessment of diagnostic and prognostic accuracy. Front Neurol 2019;10 :446. 10.3389/fneur.2019.00446 31105646 20 Fineblit S , Selci E , Loewen H , et al . Health-Related quality of life after pediatric mild traumatic brain injury/concussion: a systematic review. J Neurotrauma 2016;33 :1561–8. 10.1089/neu.2015.4292 26916876 21 Goreth MB , Palokas M . Association between premorbid neuropsychological conditions and pediatric mild traumatic brain injury/concussion recovery time and symptom severity: a systematic review. JBI Database System Rev Implement Rep 2019;17 :1464–93. 10.11124/JBISRIR-2017-004008 22 Hung R , Carroll LJ , Cancelliere C , et al . Systematic review of the clinical course, natural history, and prognosis for pediatric mild traumatic brain injury: results of the international collaboration on mild traumatic brain injury prognosis. Arch Phys Med Rehabil 2014;95 :S174–91. 10.1016/j.apmr.2013.08.301 24581904 23 Cancelliere C , Donovan J , Cassidy JD . Is sex an indicator of prognosis after mild traumatic brain injury: a systematic analysis of the findings of the World Health Organization collaborating centre task force on mild traumatic brain injury and the international collaboration on mild traumatic brain injury prognosis. Arch Phys Med Rehabil 2016;97 :S5–18. 10.1016/j.apmr.2014.11.028 25666784 24 Carroll LJ , Cassidy JD , Peloso PM , et al . Prognosis for mild traumatic brain injury: results of the WHO collaborating centre task force on mild traumatic brain injury. J Rehabil Med 2004:84–105. 10.1080/16501960410023859 15083873 25 Emery CA , Barlow KM , Brooks BL , et al . A systematic review of psychiatric, psychological, and behavioural outcomes following mild traumatic brain injury in children and adolescents. Can J Psychiatry 2016;61 :259–69. 10.1177/0706743716643741 27254800 26 Ludwig R , D’Silva L , Vaduvathiriyan P , et al . Sleep disturbances in the acute stage of concussion are associated with poorer long-term recovery: a systematic review. PM R 2020;12 :500–11. 10.1002/pmrj.12309 31876086 27 Lugones M , Parkin G , Bjelosevic S , et al . Blood biomarkers in paediatric mild traumatic brain injury: a systematic review. Neurosci Biobehav Rev 2018;87 :206–17. 10.1016/j.neubiorev.2018.02.006 29462640 28 Mayer AR , Kaushal M , Dodd AB , et al . Advanced biomarkers of pediatric mild traumatic brain injury: progress and perils. Neurosci Biobehav Rev 2018;94 :149–65. 10.1016/j.neubiorev.2018.08.002 30098989 29 Silverberg ND , Gardner AJ , Brubacher JR , et al . Systematic review of multivariable prognostic models for mild traumatic brain injury. J Neurotrauma 2015;32 :517–26. 10.1089/neu.2014.3600 25222514 30 Zemek RL , Farion KJ , Sampson M , et al . Prognosticators of persistent symptoms following pediatric concussion: a systematic review. JAMA Pediatr 2013;167 :259–65. 10.1001/2013.jamapediatrics.216 23303474 31 Merezhinskaya N , Mallia RK , Park D , et al . Photophobia associated with traumatic brain injury: a systematic review and meta-analysis. Optom Vis Sci 2021;98 :891–900. 10.1097/OPX.0000000000001757 34354013 32 Yumul JN , Crowe L , Catroppa C , et al . Post-concussive signs and symptoms in preschool children: a systematic review. Neuropsychol Rev 2022;32 :631–50. 10.1007/s11065-021-09518-z 34390464 33 Iverson GL , Williams MW , Gardner AJ , et al . Systematic review of preinjury mental health problems as a vulnerability factor for worse outcome after sport-related concussion. Orthop J Sports Med 2020;8 :2325967120950682. 10.1177/2325967120950682 33614790 34 Cook NE , Iaccarino MA , Karr JE , et al . Attention-Deficit/Hyperactivity disorder and outcome after concussion: a systematic review. J Dev Behav Pediatr 2020;41 :571–82. 10.1097/DBP.0000000000000808 32317560 35 NIHR ARC WEST . Identifying which children are most at risk of post-concussion syndrome. 2021. Available: https://arc-w.nihr.ac.uk/research/projects/predicting-which-children-are-most-at-risk-of-concussion-and-post-concussion-syndrome/ 36 Chendrasekhar A , Kuczabski B , Cohen D , et al . Delayed sequelae related to mild traumatic brain injury in children. Glob Pediatr Health 2020;7 :2333794X20947988. 10.1177/2333794X20947988 37 Jeckell AS , Brett BL , Totten DJ , et al . Team versus individual sport participation as a modifying factor in the development of post-concussion syndrome after first concussion: a pilot study. Appl Neuropsychol Child 2019;8 :199–205. 10.1080/21622965.2017.1421464 29351382