Effects of Axial Torsion on Disc Height Distribution: An In Vivo Study
Bibliographic record
Abstract
OBJECTIVES: Axial rotation of the torso is commonly used during manipulation treatment of low back pain. Little is known about the effect of these positions on disc morphology. Rotation is a three-dimensional event that is inadequately represented with planar images in the clinic. True quantification of the intervertebral gap can be achieved with a disc height distribution. The objective of this study was to analyze disc height distribution patterns during torsion relevant to manipulation in vivo. METHODS: Eighty-one volunteers were computed tomography-scanned both in supine and in right 50° rotation positions. Virtual models of each intervertebral gap representing the disc were created with the inferior endplate of each "disc" set as the reference surface and separated into 5 anatomical zones: 4 peripheral and 1 central, corresponding to the footprint of the annulus fibrosus and nucleus pulposus, respectively. Whole-disc and individual anatomical zone disc height distributions were calculated in both positions and were compared against each other with analysis of variance, with significance set at P < .05. RESULTS: Mean neutral disc height was 7.32 mm (1.59 mm). With 50° rotation, a small but significant increase to 7.44 mm (1.52 mm) (P < .0002) was observed. The right side showed larger separation in most levels, except at L5/S1. The posterior and right zones increased in height upon axial rotation of the spine (P < .0001), whereas the left, anterior, and central decreased. CONCLUSIONS: This study quantified important tensile/compressive changes disc height during torsion. The implications of these mutually opposing changes on spinal manipulation are still unknown.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".