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Record W4386287855 · doi:10.3389/fspor.2023.1172514

Which muscles exhibit increased stiffness in people with chronic neck pain? A systematic review with meta-analysis

2023· review· en· W4386287855 on OpenAlexaboutno aff
Manca Opara, Žiga Kozinc

Bibliographic record

VenueFrontiers in Sports and Active Living · 2023
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAsymptomaticMeta-analysisNeck painPhysical therapyRehabilitationMuscle stiffnessPhysical medicine and rehabilitationScopusQuality of life (healthcare)Trapezius muscleSystematic reviewStrictly standardized mean differenceInternal medicineStiffnessMEDLINEElectromyographyPathologyAlternative medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.285
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations21
Published2023
Admission routes1
Has abstractyes

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