The Toronto Concussion Study: Sense of smell is not associated with concussion severity or recovery
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".