Procedure Selection and Patient Positioning Influence Spine Kinematics During High-Velocity, Low-Amplitude Spinal Manipulation Applied to the Low Back
Bibliographic record
Abstract
OBJECTIVES: This investigation compared indirect 3-dimensional angular kinematics (position, velocity, and acceleration) of the lumbar spine for 2 different high-velocity, low-amplitude (HVLA) spinal manipulation procedures (lumbar spinous pull or push), and altered initial patient lower limb posture. METHODS: Twenty-four participants underwent 6 HVLA procedures directed toward the presumed L4 vertebra, reflecting each combination of 2 variants of a spinal manipulation application technique (spinous pull and push) and 3 initial hip flexion angles (0°, 45°, and 90°) applied using a right lateral recumbent patient position. All contact forces and moments between the patient and the external environment, as well as 3-dimensional kinematics of the patient's pelvis and thorax, were recorded. Lumbar spine angular positions, velocities, and accelerations were analyzed within the preload and impulse stages of each HVLA trial. RESULTS: Lumbar spine left axial rotation was greater for the pull HVLA. The pull HVLA also generated a greater maximum (leftward) and lower minimum (rightward) axial rotation velocity and deceleration and greater leftward and rightward lateral bend velocities, acceleration, and deceleration components. Not flexing the hip produced the greatest amount of extension, as well as the lowest axial rotation and maximum axial rotation acceleration during the impulse. CONCLUSIONS: This investigation provides basic kinematic information for clinicians to understand the similarities and differences between 2 HVLA side-lying manipulations in the lumbar spine. Use of these findings and novel technology can drive future research initiatives that can both affect clinical decision making and influence teaching environments surrounding spinal manipulative therapy skill acquisition.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".