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Record W2913331433 · doi:10.1186/s12974-019-1402-y

Evidence of a distinct peripheral inflammatory profile in sport-related concussion

2019· article· en· W2913331433 on OpenAlexafffund
Alex P. Di Battista, Nathan W. Churchill, Shawn G. Rhind, Doug Richards, Michael G. Hutchison

Bibliographic record

VenueJournal of Neuroinflammation · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsSt. Michael's HospitalUniversity of TorontoDefence Research and Development Canada
FundersCanadian Institute for Military and Veteran Health ResearchMinistry of Education, IndiaMinistry of Earth Sciences
KeywordsConcussionNeurologyPeripheralMedicineSports medicineNeuroscienceInflammationPhysical medicine and rehabilitationPsychologyPhysical therapyImmunologyInjury preventionPoison controlInternal medicineMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Inflammation is considered a hallmark of concussion pathophysiology in experimental models, yet is understudied in human injury. Despite the growing use of blood biomarkers in concussion, inflammatory biomarkers have not been well characterized. Furthermore, it is unclear if the systemic inflammatory response to concussion differs from that of musculoskeletal injury. The purpose of this paper was to characterize systemic inflammation after injury in athletes with sport-related concussion or musculoskeletal injury. METHODS: A prospective, observational cohort study was conducted employing 175 interuniversity athletes (sport-related concussion, n = 43; musculoskeletal injury, n = 30; healthy, n = 102) from 12 sports at a sports medicine clinic at an academic institution. High-sensitivity immunoassay was used to evaluate 20 inflammatory biomarkers in the peripheral blood of athletes within 7 days of injury (subacute) and at medical clearance. Healthy athletes were sampled prior to the start of their competitive season. Partial least squares regression analyses were used to identify salient biomarker contributions to class separation between injured and healthy athletes, as well as to evaluate the relationship between biomarkers and days to recovery in injured athletes. RESULTS: In the subacute period after injury, compared to healthy athletes, athletes with sport-related concussion had higher levels of the chemokines' monocyte chemoattractant protein-4 (p < 0.001) and macrophage inflammatory protein-1β (p = 0.001); athletes with musculoskeletal injury had higher levels of thymus and activation-regulated chemokine (p = 0.001). No significant differences in biomarker profiles were observed at medical clearance. Furthermore, concentrations of monocyte chemoattractant protein-1 (p = 0.007) and monocyte chemoattractant protein-4 (p < 0.001) at the subacute time point were positively correlated with days to recovery in athletes with sport-related concussion, while thymus and activation-regulated chemokine was (p = 0.001) positively correlated with days to recovery in athletes with musculoskeletal injury. CONCLUSION: Sport-related concussion is associated with perturbations to systemic inflammatory chemokines that differ from those observed in athletes with a musculoskeletal injury. These results support inflammation as an important facet of secondary injury after sport-related concussion that can be measured systemically in a human model of injury.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.325
Teacher spread0.283 · 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 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

Citations55
Published2019
Admission routes2
Has abstractyes

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