The deep fascia and its role in chronic pain and pathological conditions: A review
Bibliographic record
Abstract
The deep fascia is a three-dimensional continuum of connective tissue surrounding the bones, muscles, nerves and blood vessels throughout our body. Its importance in chronically debilitating conditions has recently been brought to light. This work investigates changes in these tissues in pathological settings. A state-of-the-art review was conducted in PubMed and Google Scholar following a two-stage process. A first search was performed to identify main types of deep fasciae. A second search was performed to identify studies considering a deep fascia, common pathologies of this deep fascia and the associated alterations in tissue anatomy. We find that five main deep fasciae pathologies are chronic low back pain, chronic neck pain, Dupuytren's disease, plantar fasciitis and iliotibial band syndrome. The corresponding fasciae are respectively the thoracolumbar fascia, the cervical fascia, the palmar fascia, the plantar fascia and the iliotibial tract. Pathological fascia is characterized by increased tissue stiffness along with alterations in myofibroblast activity and the extra-cellular matrix, both in terms of collagen and Matrix Metalloproteases (MMP) levels. Innervation changes such as increased density and sensitization of nociceptive nerve fibers are observed. Additionally, markers of inflammation such as pro-inflammatory cytokines and immune cells are documented. Pain originating from the deep fascia likely results from a combination of increased nerve density, sensitization and chronic nociceptive stimulation, whether physical or chemical. The pathological fascia is characterized by changes in innervation, immunology and tissue contracture. Further investigation is required to best benefit both research opportunities and 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".