Prevalence of midline cervical spine tenderness in the non-trauma population
Bibliographic record
Abstract
OBJECTIVE: The Canadian C-Spine Rule (CCR) and the National Emergency X-Radiography Utilization Study (NEXUS) criteria are two commonly used clinical decision rules which use midline cervical spine (c-spine) tenderness on palpation as an indication for c-spine imaging post-trauma. This study was undertaken to determine the prevalence and location of midline c-spine tenderness in the non-trauma population. METHODS: We prospectively evaluated consenting adult patients presenting to an urban ED or university sport medicine clinic in Montreal, Canada between 2018 and 2020 for atraumatic non-head and neck-related reports over a 20-month period. The presence and location of pain during midline c-spine palpation as assessed by two examiners during separate evaluations was recorded. Patient information such as age, neck length and circumference, gender, body mass index (BMI) and scaphoid tenderness was also collected. RESULTS: Of 478 patients enrolled, 286 (59.8%) had midline c-spine tenderness on palpation with both examiners. The majority of those with tenderness were female (70.6%). When examining all patients, tenderness was present in the upper third of the c-spine in 128 (26.8%) patients, middle third in 270 (56.5%) patients and lower third in 6 (1.3%) patients. Factors associated with having increased odds of midline c-spine tenderness on palpation included a lower BMI and the presence of scaphoid tenderness on palpation. CONCLUSIONS: There is a high prevalence of c-spine tenderness on palpation in patients who have not undergone head or neck trauma. This finding may help explain the low specificity in some of the validation studies examining the CCR and the NEXUS criteria.
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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 | 0.002 |
| 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) | 0.002 | 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".