Lumbar Multifidus Muscle Morphology Changes in Patient with Different Degrees of Lumbar Disc Herniation: An Ultrasonographic Study
Bibliographic record
Abstract
Background and Objective: Previous studies demonstrated that the prevalence of lumbar disc herniation (LDH) is relatively high. This investigation aimed to evaluate the size of lumbar multifidus (LM) muscle in patients with different degrees of LDH compared to healthy group, during rest and contraction, using ultrasonography. Materials and Methods: In this non-experimental, analytic, and case control study, ultrasound imaging was used to assess cross-sectional area (CSA) and thickness of the LM muscle in 15 healthy subjects and 60 patients with different stages of LDH (bulging group = 15, protrusion group = 15, extrusion group = 15, sequestration group = 15). Measurements were taken bilaterally at the L4–L5 level, during rest and contraction and results were compared between groups. Results: There was a significant difference between healthy subjects and the extrusion and sequestration groups during rest and contraction for LM muscle CSA and thickness (p = 0.001), as LM muscle CSA and thickness were significantly smaller in extrusion and sequestration patient groups compared to healthy subjects. LM atrophy was greater in patients with extrusion and sequestration groups than in patients with bulging and protrusion, both at rest and during contraction. Significant correlations were also observed between functional disability and intensity of pain with LM CSA and thickness measurements. Conclusions: Patients with extrusion and sequestration LDH had smaller LM muscle at rest and during contraction compared to healthy subjects. Larger LDH lesions were associated with decreased LM muscle size. Patient with more pain, disability, and extrusion and sequestration LDH had greater LM size changes. LM muscle size was not correlated with symptom duration. Further investigation with greater sample size is warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".