A Multimodal Exertional Test for concussion: a pilot study in healthy athletes
Bibliographic record
Abstract
Introduction Exertional tests have become a promising tool to assist clinicians in the management of concussions, however require expensive equipment, extensive spaces, and specialized clinician expertise. As such, we developed a test with minimal resource requirements encompassing key elements of sport and physical activity. The purpose of this study was to pilot test the Multimodal Exertional Test (MET) protocol in a sample of healthy interuniversity athletes. Methods The MET comprises four stages, each featuring three distinct tasks. The test begins with engaging in squats, alternating reverse lunges, and hip hinges (Stage 1). The next stage progressively evolves into executing these tasks within specified time limits (Stage 2). Following this, the test advances to a stage that incorporates cognitive tasks (Stage 3), and the final stage demands greater levels of physical exertion, cognition, and multi-directional movements (Stage 4). Heart rate (HR) was obtained during each stage of the MET and participants’ symptom severity scores were recorded following each task. Results Fourteen healthy interuniversity athletes (n = 8 female, n = 6 male) participated in the study. HR was obtained for 10 of the 14 athletes (females: n = 6, males: n = 4). Increases in average and maximum HR were identified between pre-MET and Stage 1, and between Stages 3 and 4. Consistent with the tasks in each stage, there were no increases in average and maximum HR observed between MET Stages 1 to 3. Female athletes exhibited higher average and maximum HRs compared to male athletes during all four stages. All 14 athletes reported minimal changes in symptom severity following each task. Conclusion Among healthy athletes, the MET elicits an increase in average and maximum HR throughout the protocol without symptom provocation. Female athletes exhibit higher HRs during all four stages in comparison to male athletes.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".