Chronic Low Back Pain Occurring in Association With Hypermobility Spectrum Disorder and Ehlers-Danlos Syndrome
Bibliographic record
Abstract
BACKGROUND: This review paper outlines recent advances in diagnostic criteria for hypermobility spectrum disorder (HSD) and its association with Ehlers-Danlos syndrome (EDS), as well as current literature on the association between joint hypermobility syndrome and lumbar back pain. We outline the optimal multidisciplinary management of lumbar back pain in the context of joint hypermobility syndrome, as well as the indications and possible side effects of surgical management of patients with these conditions.Several studies have suggested a link between chronic low back pain and hypermobility. HSD has been described as an excessive range of motion in a joint, when accounting for patient demographics. The nomenclature surrounding symptomatic joint hypermobility has varied historically, and various groups, including most notably the international EDS consortium, have introduced new classification schemes to acknowledge the systemic effects of joint hypermobility, which were previously poorly understood. METHODS: Narrative literature review. RESULTS: Not applicable. CONCLUSIONS: Lower back pain experienced in patients on the HSD-EDS spectrum is multifactorial in origin and should not be considered solely in anatomical terms. Caution has been advised in the surgical management of patients on the HSD-hEDS spectrum, particularly where the subtype is unclear. The vascular type of EDS has a particular propensity for severe bleeding complications. Rates of perioperative complications after lumbar spinal surgery in the hypermobile EDS population have been reported to be up to 50%. When hypermobility and chronic lumbar back pain coexist, we advocate management in a multidisciplinary setting involving physiotherapists, pain physicians, surgeons, and psychologists.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".