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Record W2981599445 · doi:10.1089/neu.2019.6800

Sex Differences in Cerebral Blood Flow Associated with a History of Concussion

2019· article· en· W2981599445 on OpenAlexafffund
Julia Hamer, Nathan W. Churchill, Michael G. Hutchison, Simon J. Graham, Tom A. Schweizer

Bibliographic record

VenueJournal of Neurotrauma · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsPost-hoc analysisConcussionPost hocCerebral blood flowMedicineAsymptomaticAthletesInternal medicinePhysical medicine and rehabilitationPsychologyPhysiologyPoison controlPhysical therapyInjury prevention

Abstract

fetched live from OpenAlex

Growing evidence suggests that a history of sport concussion may lead to long-term changes in brain physiology, with cerebral blood flow (CBF) being particularly sensitive to injury. However, it is unknown whether these changes are sex specific. The goal of this study was to evaluate sex differences in CBF of asymptomatic athletes, with and without a history of concussion (HOC) using arterial spin labeling (ASL). Scans were acquired for 122 athletes, including those without HOC (33 male, 33 female) and those with HOC (28 male, 28 female). Males with HOC had lower CBF bilaterally than males without HOC, seen predominantly in the temporal lobes. In contrast, females with HOC showed no significant differences relative to females without HOC, although they had significantly higher variability in temporal CBF values compared with males with HOC. Additional analyses within the HOC groups found that females with multiple concussion had lower CBF posteriorly compared with those with a single concussion, whereas males showed no significant effects. This study provides the first evidence of sex differences in CBF associated with HOC.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.109
GPT teacher head0.317
Teacher spread0.208 · 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

Citations43
Published2019
Admission routes2
Has abstractyes

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