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Record W3007003980 · doi:10.1177/1352458520908037

Concussion in adolescence and the risk of multiple sclerosis: A retrospective cohort study

2020· article· en· W3007003980 on OpenAlexafffundabout
Christopher A. Povolo, Jennifer Reid, Salimah Z. Shariff, Blayne Welk, Sarah A. Morrow

Bibliographic record

VenueMultiple Sclerosis Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsWestern UniversityInstitute for Clinical Evaluative SciencesLawson Health Research InstituteLondon Health Sciences Centre
FundersInstitute for Clinical Evaluative SciencesOntario Ministry of Health and Long-Term CareRoche Canada
KeywordsConcussionMedicineRetrospective cohort studyMultiple sclerosisHazard ratioEmergency departmentPoison controlYoung adultInjury preventionCohortCohort studyPhysical therapyPediatricsInternal medicineEmergency medicineConfidence intervalPsychiatry

Abstract

fetched live from OpenAlex

Background: Physical trauma, specifically concussions sustained during adolescence, has been hypothesized to be a risk factor for multiple sclerosis (MS). Objective: To examine the association between adolescent concussions and future MS diagnosis. Methods: This retrospective study using linked administrative databases from Ontario, Canada, identified 97,965 adolescents (age 11–18 years) who sustained ⩾1 concussion and presented to an emergency department between 1992 and 2011. Cases were matched 1:3 with individuals who had not sustained a concussion based on age, sex, address, and index date. The primary outcome was MS diagnosis, using a validated MS diagnosis definition: ⩾1 hospitalization or ⩾5 physician billings within 2 years. Results: A concussion during adolescence was associated with a significantly increased risk of MS (hazard ratio (HR) = 1.29, p = 0.03). Sex-specific analysis revealed that only males who sustained a concussion in adolescence had a raised risk of MS (HR = 1.41, p = 0.04). Conclusion: This study supports an association between concussions in adolescence and future MS diagnoses, highlighting the potentially serious long-term effects of concussions.

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)0.003
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.076
GPT teacher head0.287
Teacher spread0.211 · 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

Citations17
Published2020
Admission routes3
Has abstractyes

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