The effect of phasic versus combined neuromuscular electrical stimulation using the StimaWELL 120MTRS system on multifidus muscle morphology and function in patients with chronic low back pain: a randomized controlled trial protocol
Bibliographic record
Abstract
BACKGROUND: Neuromuscular electrical stimulation (NMES) is used to improve muscle strength clinically when rehabilitating various musculoskeletal disorders. However, the effects of NMES on muscle morphology and function in individuals with non-specific chronic low back pain (CLBP) have scarcely been investigated. Although research links deficits in the paraspinal musculature with subjective reports of pain and disability, it is unknown if treatment with NMES can help reverse these deficits. Therefore, the primary aim of this study is to compare the effects of two muscle therapy protocols with a medium-frequency electrotherapy device (the StimaWELL 120MTRS system) on multifidus muscle morphology and function in CLBP patients. The secondary aims are to determine the effects of these protocols subjective reports of pain intensity, pain interference, disability, and catastrophizing. METHODS: A total of 30 participants with non-specific CLBP, aged 18-60, will be recruited from local orthopedic clinics and databases. Participants will be randomized (1:1) to either the phasic or combined (phasic + tonic) muscle therapy protocols on the StimaWELL 120MTRS system. Participants will undergo 20 supervised electrotherapy treatments over a 10-week period. The primary outcomes will be multifidus morphology (e.g. cross-sectional area (CSA), fat infiltration) and function (e.g., contraction measured via %thickness change from a rested to contracted state, and stiffness at rest and during contraction). Secondary outcomes will include pain intensity, interference, disability, and catastrophizing. Both primary and secondary outcomes will be obtained at baseline and at 11-weeks; secondary outcomes measured via questionnaires will also be obtained at 6-weeks, while LBP intensity will be measured before and after each treatment. Paired t-tests will be used to assess within-group changes for all primary outcome measures. A two-way repeated-measures analysis of variance will be used to assess changes in secondary outcomes over time. DISCUSSION: The results of this trial will help clarify the role of medium-frequency NMES on lumbar multifidus morphology and function. TRIAL REGISTRATION: NCT04891692, registered retrospectively on May 18, 2021.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".