Motor unit potential morphology differences in individuals with non-specific arm pain and lateral epicondylitis
Bibliographic record
Abstract
BACKGROUND: The pathophysiology of non-specific arm pain (NSAP) is unclear and the diagnosis is made by excluding other specific upper limb pathologies, such as lateral epicondylitis or cervical radiculopathy. The purpose of this study was to determine: (i) if the quantitative parameters related to motor unit potential morphology and/or motor unit firing patterns derived from electromyographic (EMG) signals detected from an affected muscle of patients with NSAP are different from those detected in the same muscle of individuals with lateral epicondylitis (LE) and/or control subjects and (ii) if the quantitative EMG parameters suggest that the underlying pathophysiology in NSAP is either myopathic or neuropathic in nature. METHODS: Sixteen subjects with NSAP, 11 subjects with LE, eight subjects deemed to be at-risk for developing a repetitive strain injury, and 37 control subjects participated. A quantitative electromyography evaluation was completed using decomposition-based quantitative electromyography (DQEMG). Needle- and surface-detected EMG signals were collected during low-level isometric contractions of the extensor carpi radialis brevis (ECRB) muscle. DQEMG was used to extract needle-detected motor unit potential trains (MUPTs), and needle-detected motor unit potential (MUP) and surface detected motor unit potential (SMUP) morphology and motor unit (MU) firing rates were compared among the four groups using one-way analysis of variance (ANOVA). Post hoc analyses were performed using Tukey's pairwise comparisons. RESULTS: Significant group differences were found for all MUP variables and for MU firing rate (p < 0.006). The post-hoc analyses revealed that patients with NSAP had smaller MUP amplitude and SMUP amplitude and area compared to the control and LE groups (p < 0.006). MUP duration and AAR values were significantly larger in the NSAP, LE and at-risk groups compared to the control group (p < 0.006); while MUP amplitude, duration and AAR values were smaller in the NSAP compared to the LE group. SMUP duration was significantly shorter in the NSAP group compared to the control group (p < 0.006). NSAP, LE and at-risk subjects had lower mean MU firing rates than the control subjects (p < 0.006). CONCLUSION: The size-related parameters suggest that the NSAP group had significantly smaller MUPs and SMUPs than the control and LE subjects. Smaller MUPs and SMUPs may be indicative of muscle fiber atrophy and/or loss. A prospective study is needed to confirm any causal relationship between smaller MUPs and SMUPs and NSAP as found in this work.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".