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Record W4380574899 · doi:10.1136/bjsports-2022-106661

Acute evaluation of sport-related concussion and implications for the Sport Concussion Assessment Tool (SCAT6) for adults, adolescents and children: a systematic review

2023· review· en· W4380574899 on OpenAlexafffund
Ruben J. Echemendía, Joel S. Burma, Jared M. Bruce, Gavin A Davis, Christopher C. Giza, Kevin M. Guskiewicz, Dhiren Naidu, Amanda M. Black, Steven P. Broglio, Simon Kemp, Jon Patricios, Margot Putukian, Roger Zemek, Juan Carlos Arango‐Lasprilla, Christopher M. Bailey, Benjamin L. Brett, Nyaz Didehbani, Gerry Gioia, Stanley A. Herring, David R. Howell, Christina L. Master, Tamara C. Valovich McLeod, William P. Meehan, Zahra Premji, Danielle Salmon, Jacqueline van Ierssel, Neil Bhathela, Michael Makdissi, Samuel R. Walton, James Kissick, Jamie Pardini, Kathryn Schneider

Bibliographic record

VenueBritish Journal of Sports Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of OttawaUniversity of VictoriaUniversity of AlbertaUniversity of Calgary
Funders59th Medical WingColorado Clinical and Translational Sciences InstituteNational Center for Injury Prevention and ControlNational Institute of Mental HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentCenters for Disease Control and PreventionAmerican Medical Society for Sports MedicineFondation Brain CanadaAmerican Psychiatric Nurses AssociationZogenixCanadian Institutes of Health ResearchMitacsInternational Olympic Committee
KeywordsConcussionMedicinePhysical therapySystematic reviewPhysical medicine and rehabilitationPost-concussion syndromeCognitionPoison controlMEDLINEInjury preventionPsychiatryEmergency medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To systematically review the scientific literature regarding the acute assessment of sport-related concussion (SRC) and provide recommendations for improving the Sport Concussion Assessment Tool (SCAT6). DATA SOURCES: Systematic searches of seven databases from 2001 to 2022 using key words and controlled vocabulary relevant to concussion, sports, SCAT, and acute evaluation. ELIGIBILITY CRITERIA: (1) Original research articles, cohort studies, case-control studies, and case series with a sample of >10; (2) ≥80% SRC; and (3) studies using a screening tool/technology to assess SRC acutely (<7 days), and/or studies containing psychometric/normative data for common tools used to assess SRC. DATA EXTRACTION: Separate reviews were conducted involving six subdomains: Cognition, Balance/Postural Stability, Oculomotor/Cervical/Vestibular, Emerging Technologies, and Neurological Examination/Autonomic Dysfunction. Paediatric/Child studies were included in each subdomain. Risk of Bias and study quality were rated by coauthors using a modified SIGN (Scottish Intercollegiate Guidelines Network) tool. RESULTS: Out of 12 192 articles screened, 612 were included (189 normative data and 423 SRC assessment studies). Of these, 183 focused on cognition, 126 balance/postural stability, 76 oculomotor/cervical/vestibular, 142 emerging technologies, 13 neurological examination/autonomic dysfunction, and 23 paediatric/child SCAT. The SCAT discriminates between concussed and non-concussed athletes within 72 hours of injury with diminishing utility up to 7 days post injury. Ceiling effects were apparent on the 5-word list learning and concentration subtests. More challenging tests, including the 10-word list, were recommended. Test-retest data revealed limitations in temporal stability. Studies primarily originated in North America with scant data on children. CONCLUSION: Support exists for using the SCAT within the acute phase of injury. Maximal utility occurs within the first 72 hours and then diminishes up to 7 days after injury. The SCAT has limited utility as a return to play tool beyond 7 days. Empirical data are limited in pre-adolescents, women, sport type, geographical and culturally diverse populations and para athletes. PROSPERO REGISTRATION NUMBER: CRD42020154787.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.544
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.431
Teacher spread0.359 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations100
Published2023
Admission routes2
Has abstractyes

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