Which muscles exhibit increased stiffness in people with chronic neck pain? A systematic review with meta-analysis
Bibliographic record
Abstract
Introduction Chronic neck pain (CNP) substantially impacts quality of life, posing both personal challenges and economic strains. This systematic review sought to discern muscle-specific stiffness differences between CNP patients and individuals without CNP. Methods We searched the PubMed, Scopus, and PEDro databases for studies using ultrasound elastography or myotonometry to compare muscle stiffness between CNP patients and asymptomatic controls. Using a meta-analysis with a random-effects model, we derived the pooled effect as standardized mean difference (SMD). Results Out of the six studies selected, the adjusted Newcastle-Ottawa rating scale for cross-sectional studies denoted three as moderate-quality and three as high-quality. Our findings indicate that the upper trapezius (UT) stiffness was elevated in CNP patients compared to their counterparts without CNP (SMD = 0.39, 95% CI = 0.05 to 0.74; p = 0.03; small effect size). The data for other muscles remained inconclusive. Discussion Given the case-control design of all reviewed studies, a direct causative link between UT stiffness and CNP is yet to be confirmed. As such, recommending a reduction in trapezius muscle stiffness as a primary rehabilitation strategy for CNP patients is still inconclusive and further research is needed.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".