Musculoskeletal physical outcome measures in individuals with tension-type headache: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Individuals with tension-type headache (TTH), in addition to headache pain, typically suffer from pericranial muscle tenderness and increased cervical muscle tone. Physical and physiological outcomes related to musculoskeletal function, however, are not commonly assessed in clinical studies and not systematically proposed as outcome measures in headache-related practice guidelines. OBJECTIVES: To review which musculoskeletal outcomes are used in the clinical assessment of patients with TTH and which are associated with headache pain and related dysfunction. METHODS: Literature searches were performed in MEDLINE, PubMed, the Cochrane databases and EMBASE using terms relating to musculoskeletal physical outcomes in TTH. RESULTS: Twenty-six studies met selection criteria. Physiological outcomes typically reported in laboratory studies were trigger points, pressure pain threshold, range of motion and tenderness. A greater number of trigger points and lower pressure pain threshold were reported in patients with episodic TTH in comparison with healthy subjects. Individuals with chronic TTH, when compared with non-headache controls, consistently showed a greater number of trigger points, a lower value of pressure pain threshold and a more severe forward head posture. CONCLUSION: Musculoskeletal outcomes, such as trigger points, pressure pain threshold and forward head posture should inform TTH pathophysiology, diagnosis and interdisciplinary patient care.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".