Spinal degeneration is associated with lumbar multifidus morphology in secondary care patients with low back or leg pain
Bibliographic record
Abstract
Associations between multifidus muscle morphology and degenerative pathologies have been implied in patients with non-specific low back pain, but it is unknown how these are influenced by pathology severity, number, or distribution. MRI measures of pure multifidus muscle cross-sectional area (CSA) were acquired from 522 patients presenting with low back and/or leg symptoms in an outpatient clinic. We explored cross-sectional associations between the presence, distribution, and/or severity of lumbar degenerative pathologies (individually and in aggregate) and muscle outcomes in multivariable analyses (beta coefficients [95% CI]). We identified associations between lower pure multifidus muscle CSA and disc degeneration (at two or more levels): - 4.51 [- 6.72; - 2.3], Modic 2 changes: - 4.06 [- 6.09; - 2.04], endplate defects: - 2.74 [- 4.58; - 0.91], facet arthrosis: - 4.02 [- 6.26; - 1.78], disc herniations: - 3.66 [- 5.8; - 1.52], and when > 5 pathologies were present: - 6.77 [- 9.76; - 3.77], with the last supporting a potential dose-response relationship between number of spinal pathologies and multifidus morphology. Our findings could hypothetically indicate that these spinal and muscle findings: (1) are part of the same degenerative process, (2) result from prior injury or other common antecedent events, or (3) have a directional relationship. Future longitudinal studies are needed to further examine the complex nature of these relationships.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".