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Record W2789923795 · doi:10.1080/02699052.2018.1432892

An investigation of neuroinjury biomarkers after sport-related concussion: from the subacute phase to clinical recovery

2018· article· en· W2789923795 on OpenAlexafffund
Alex P. Di Battista, Shawn G. Rhind, Andrew Baker, Rakesh Jetly, Jeff D. Debad, Doug Richards, Michael G. Hutchison

Bibliographic record

VenueBrain Injury · 2018
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of OttawaCanadian Armed ForcesSt. Michael's HospitalUniversity of TorontoDefence Research and Development Canada
FundersMinistère de la Défense NationaleCanadian Armed ForcesDefence Research and Development CanadaHealth Research Board
KeywordsConcussionBiomarkerAthletesMedicineInternal medicineOncologyPhysical therapyPoison controlInjury preventionBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: To characterise a panel of neuroinjury-related blood biomarkers after sport-related concussion (SRC). We hypothesised significant differences in biomarker profiles between athletes with SRC and healthy controls at both subacute and medical clearance time points. METHODS: Thirty-eight interuniversity athletes were recruited over two athletic seasons (n = 19 SRC; n = 19 healthy matched-control). High-sensitivity immunoassay was used to evaluate 11 blood analytes at both the subacute phase after SRC and at medical clearance. RESULTS: Univariate analysis identified elevated circulating peroxiredoxin-6 (PRDX-6) in athletes with SRC compared to healthy controls at the subacute time point. Multivariate analyses yielded similar results in the subacute phase, but identified both PRDX-6 and T-tau as significant contributors to class separation between athletes with SRC and controls at medical clearance. CONCLUSIONS: Our results are consistent with the increasing recognition that physiological recovery after SRC extends beyond clinical recovery. Blood biomarkers appear to be useful in elucidating the biology of brain restitution after SRC. However, their implementation requires mindfulness of factors such as academic stress, exercise, and injury heterogeneity.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.409
Teacher spread0.340 · 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.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations27
Published2018
Admission routes2
Has abstractyes

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