Biomechancial Quantification of Pathologic Manipulable Spinal Lesions: An In Vivo Ovine Model of Spondylolysis and Intervertebral Disc Degeneration
Bibliographic record
Abstract
OBJECTIVE: The purposes of this study were to quantify the biomechanical and pathologic consequences of surgically induced spinal lesions and to determine their response to spinal manipulation (SMT) in an in vivo ovine model. METHODS: Of 24 Merino sheep, 6 received L5 spondylolytic defects, 6 received L1 annular lesions, and 12 served as respective controls. Dorsoventral (DV) stiffness was assessed using oscillatory loads (2-12 Hz). Two SMT force-time profiles were administered in each of the groups using a randomized and repeated-measures design. Stiffness and the effect of SMT on the DV motions and multifidus needle electromyographic responses were assessed using a repeated-measures analysis of variance (α = .05). Postmortem histologic analysis and computed tomography validated the presence of lesions. RESULTS: L5 DV stiffness was significantly increased (40.2%) in the spondylolysis (6.28 N/mm) compared with the L5 control group (4.48 N/mm) (P < 03). Spinal manipulations delivered to the spondylolysis group resulted in less DV vertebral displacement (P < .01) compared with controls. Dorsoventral stiffness of the disc degeneration group was 5.66 N/mm, 94.5% greater than in the L1 control group (2.91 N/mm) (P < .01). One hundred-millisecond SMTs resulted in significantly reduced DV displacements in the disc degeneration group compared with the L1 control group (P < .01). Animals in the disc degeneration group showed a consistent 25% to 30% reduction in needle electromyographic responses to all SMTs. CONCLUSIONS: Quantifiable objective evidence of spinal lesions and their response to SMT were confirmed in this study. Neuromechanical alterations provide novel insights into quantifying manipulable spinal lesions and a means to biomechanically assess SMT outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".