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Record W3141843173 · doi:10.1136/bjsports-2020-103696

Concussion in para sport: the first position statement of the Concussion in Para Sport (CIPS) Group

2021· article· en· W3141843173 on OpenAlexaff
Richard Weiler, Cheri Blauwet, David D. Clarke, Kristine Dalton, Wayne Derman, Kristina Fagher, Vincent Gouttebarge, James Kissick, Kenneth Lee, Jan Lexell, Peter Van de Vliet, Evert Verhagen, Nick Webborn, Osman Hassan Ahmed

Bibliographic record

VenueBritish Journal of Sports Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of OttawaUniversity of Waterloo
Fundersnot available
KeywordsConcussionAthletesMedicinePhysical therapyInjury preventionPsychologyPoison controlMedical emergency

Abstract

fetched live from OpenAlex

Concussion is a frequent injury in many sports and is also common in para athletes. However, there is a paucity of concussion research related to para sport, and prior International Concussion in Sport (CIS) consensus papers have not substantively addressed this population. To remedy this and to improve concussion care provided to para athletes, the concussion in para sport (CIPS) multidisciplinary expert group was created. This group analysed and discussed in-depth para athlete-specific issues within the established key clinical domains of the current (2017) consensus statement on CIS. Due to the onset of the COVID-19 pandemic, the group held all meetings by video conferencing. The existing Sport Concussion Assessment Tool 5 (SCAT5) for the immediate on-field and office-based off-field assessment of concussion was evaluated as part of this process, to identify any para athlete-specific concerns. Regular preparticipation and periodic health examinations are essential to determine a baseline reference point for concussion symptoms but pose additional challenges for the interpreting clinician. Further considerations for concussion management for the para athlete are required within the remove, rest, reconsider and refer consensus statement framework. Considering return to sport (RTS), the 2017 CIS consensus statement has limitations when considering the RTS of the para athlete. Case-by-case decision making related to RTS following concussion is imperative for para athletes. Additional challenges exist for the evaluation and management of concussion in para athletes. There is a need for greater understanding of existing knowledge gaps and attitudes towards concussion among athlete medical staff, coaches and para athletes. Future research should investigate the use and performance of common assessment tools in the para athlete population to better guide their clinical application and inform potential modifications. Concussion prevention strategies and sport-specific rule changes, such as in Para Alpine Skiing and Cerebral Palsy Football, also should be carefully considered to reduce the occurrence of concussion in para athletes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0050.003
Scholarly communication0.0050.004
Open science0.0040.008
Research integrity0.0200.021
Insufficient payload (model declined to judge)0.0090.011

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 head0.035
GPT teacher head0.325
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations66
Published2021
Admission routes1
Has abstractyes

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