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Record W4213270302 · doi:10.1080/02699052.2022.2037713

The Toronto Concussion Study: Sense of smell is not associated with concussion severity or recovery

2022· article· en· W4213270302 on OpenAlexaffabout
Evan Foster, Mark Bayley, Laura Langer, Cristina Saverino, Tharshini Chandra, Claire Barnard, Paul Comper

Bibliographic record

VenueBrain Injury · 2022
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsConcussionHyposmiaMedicineBiomarkerPopulationPoison controlPhysical therapyInjury preventionPsychiatryPsychologyInternal medicineDiseaseMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine sense of smell as a biomarker for both severity and duration of post-concussion symptoms. METHODS: Participants were recruited prospectively from an outpatient concussion clinic. Sense of smell was assessed using the University of Pennsylvania Smell Identification Test (UPSIT) within 7 days, and 4, 8 - or 16-weeks post-injury. UPSIT normative data were used as normal controls. The main outcomes were: symptom severity on the Sport Concussion Assessment Tool 3 (SCAT3) symptom inventory and time to physician-declared recovery. RESULTS: A total of 167 participants (mean age 32.9 [SD, 12.2] years, 59% female [n = 99]) were classified at 1 week post injury as follows: severe hyposmia in 5 (3%), moderate hyposmia in 10 (6%), mild hyposmia in 48 (29%), and normosmia in 104 (62%) individuals. A convenience sample of 81 individuals with concussion were tested at follow-up. Acute impairment of sense of smell following concussion was not associated with symptom severity on the SCAT3 or time to recovery. Sense of smell was stable from baseline to follow-up in this population. CONCLUSION: This study provides evidence that routine testing of sense of smell in individuals with concussion is not warranted as a biomarker for severity of concussion and concussion recovery.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.345
Teacher spread0.294 · 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 designNot applicable
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

Citations3
Published2022
Admission routes2
Has abstractyes

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