Heat, cold, and pressure pain thresholds following a sport-related concussion
Bibliographic record
Abstract
Concussions are among the most common sport and recreational injuries. Head and neck pain are commonly reported symptoms following concussion, but pain may also occur at regions secondary to the region of primary injury suggesting central sensitization. Central sensitization may be assessed using quantitative sensory testing (QST) to quantify heat (HPT), cold (CPT), and pressure pain thresholds (PPT). Pain thresholds have shown to predict worse prognosis of whiplash associated disorder. However, changes in pain thresholds as a consequence of SRC have not been well evaluated despite acute and persistent pain commonly occurring following SRC. Here we discuss the feasibility of QST among a consecutive sample of patients aged 13-60 that were seen at the Acute Sport Concussion Clinic (ASCC) and local sport medicine clinics in Calgary, Alberta, Canada, and diagnosed with SRC. Pain thresholds in patients with SRC were compared against orthopaedic injured (OI) and uninjured (UI) controls. There were no adverse reactions to QST in patients with SRC. There were no significant differences in heat, cold, and pressure pain thresholds across groups. Of interest, when looking at the data descriptively, patients with SRC had lower median HPTs and higher median CPTs than OI and UI controls as well as higher PPTs than OI controls. Further research including prospective cohort design is warranted to better understand how heat, cold, and pressure pain thresholds may be altered in patients with SRC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".