Differences in force-time parameters and electromyographic characteristics of two high-velocity, low-amplitude spinal manipulations following one another in quick succession
Bibliographic record
Abstract
BACKGROUND: Spinal manipulative therapy is an effective treatment for neck pain. However, the mechanisms underlying its clinical efficacy are not fully understood. Previous studies have not systematically compared force-time parameters and electromyographic responses associated with spinal manipulation. In this study, force-time parameters and electromyographic characteristics associated with multiple manual high-velocity, low-amplitude cervical and upper thoracic spinal manipulations were investigated. The purpose of this analysis was to compare the force-time parameters and electromyographic characteristics between two spinal manipulations delivered following one another in quick succession if the first thrust was not associated with an audible cavitation. METHODS: Nine asymptomatic and eighteen symptomatic participants received six Diversified-style spinal manipulations to the cervical and upper thoracic spines during data collected February 2018 to September 2019. Peak force, rate of force application and thrust duration were measured using a pressure pad. Bipolar surface electrodes were used to measure the electromyographic responses and reflex delay times in sixteen neck, back and limb outlet muscles bilaterally. Differences in force-time parameters and electromyographic data were analyzed between the first and second thrust. RESULTS: Fifty-two spinal manipulations were included in this analysis. Peak force was greater (p < 0.001) and rate of force application faster (p < 0.001) in the second thrust. Furthermore, peak electromyographic responses were higher following the second thrust in asymptomatic (p < 0.001) and symptomatic (p < 0.001) subjects. Also, electromyographic delays were shorter in the symptomatic compared to the asymptomatic participants for the second thrust (p = 0.039). There were no adverse patient events. CONCLUSION: When a second manipulation was delivered because there was not audible cavitation during the first thrust, the second thrust was associated with greater treatment forces and faster thrust rates. Peak electromyographic responses were greater following the second thrust.
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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".