Protocols aiming to increase muscle mass in persons with motor complete spinal cord injury: a systematic review
Bibliographic record
Abstract
PURPOSE: The purpose of this review was to compare all intervention modalities aimed at increasing skeletal muscle mass (SMM) in the paralysed limbs of persons with chronic (>1-year post-injury), motor complete spinal cord injury (SCI). MATERIALS AND METHODS: A systematic review of EMBASE, MEDLINE, Scopus, and SPORTDiscus databases was conducted from inception until December 2021. Published intervention studies aimed to increase SMM (measured by magnetic resonance imaging, computed tomography, ultrasound, muscle biopsy, or lean soft tissue mass by dual X-ray absorptiometry) in the paralysed limbs of adults (>18 years) with SCI were included. RESULTS: Fifty articles were included that, overall, demonstrated a high risk of bias. Studies were categorised into six groups: neuromuscular electrical stimulation (NMES) with and without external resistance, functional electrical stimulation cycling, walking- and standing-based interventions, pharmacological treatments, and studies that compared or combined intervention modalities. Resistance training (RT) using NMES on the quadriceps produced the largest and most consistent increases in SMM of all intervention modalities. CONCLUSIONS: Current evidence suggests that clinical practise aiming to increase SMM in the paralysed limbs of persons with motor complete SCI should perform NMES-RT. However, more high-quality randomised control trials are needed to determine how training variables, such as exercise volume and intensity, can be optimised for increasing SMM. Implications for rehabilitationPersons with spinal cord injury (SCI) experience severe reductions in skeletal muscle mass (SMM) post-injury, which may exacerbate their risk of obesity and metabolic disease.Out of all exercise and non-exercise-based interventions, this systematic review shows that neuromuscular electrical stimulation-based resistance training demonstrates the most robust and consistent evidence for increasing skeletal muscle mass in the paralysed limbs of adults with motor complete spinal cord injury.The findings from this review can be used to inform evidence-based practise for exercise practitioners, as well as direct future research focused on increasing muscle mass in this population.
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".