Ultrasound Evaluation of Upper Limb Sublesional Muscle Morphology in Cervical Spinal Cord Injury
Bibliographic record
Abstract
INTRODUCTION/AIMS: Upper limb paralysis is arguably the most limiting consequence of cervical spinal cord injury (cSCI). There is limited knowledge regarding the early structural changes of muscles implicated in grasp/pinch function and upper extremity nerve transfer surgeries. We evaluated: (1) muscle size and echo intensity (EI) in subacute cSCI (2-6 months) and (2) the influence of lower motor neuron (LMN) damage on these ultrasound parameters. METHODS: Cross-sectional B-mode images were captured bilaterally in individuals with cSCI (injury duration: 3.3 ± 1.2 months; C4-C6 injury levels; American Spinal Injuries Association Impairment Scale A-C; 45.7 ± 13.7 years; 3 females, 14 males) for biceps brachii (BB), extensor carpi ulnaris, extensor indicis proprius, flexor pollicis longus (FPL), and first dorsal interosseous. Each limb was analyzed as an independent event (n = 34). Cross-sectional area (CSA), thickness (MT), and EI were compared to healthy controls (HC). BB and FPL concentric needle electromyography (EMG) data were also obtained. Abnormal LMN health was defined by the presence of pathological spontaneous activity. RESULTS: Relative to HC, forearm and hand muscle size were 15%-41% lower (p < 0.05), while EI was 21%-40% higher (p < 0.05); no significant differences were observed for sublesional BB muscles (n = 16) (p > 0.05). Muscles demonstrating abnormal LMN health displayed reduced BB MT and elevated FPL EI (p < 0.05). DISCUSSION: These results underscore the substantial changes in forearm and hand muscle morphology within the subacute period after cSCI, with preliminary evidence suggesting that these changes are influenced by LMN damage.
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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) | 0.000 | 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".