Enhancing upper extremity muscle strength in individuals with spinal cord injury using low-intensity blood flow restriction exercise
Bibliographic record
Abstract
OBJECTIVES: This study explores the feasibility and effects of low-intensity blood flow restriction exercise on forearm muscle strength and function in individuals with spinal cord injury. STUDY DESIGN: Pilot randomized clinical trial. PATIENTS AND METHODS: Ten male and female adult participants with chronic cervical and thoracic spinal cord injury underwent an 8-week low-intensity blood flow restriction exercise programme that targeted forearm muscles. Each participant's contralateral forearm served as the control. Grip strength was the primary outcome measure, and participants also provided qualitative feedback on their experiences. RESULTS: The study revealed a significant increase in participants' forearm muscle strength on the experimental side engaged in low-intensity blood flow restriction training, with an average strength gain of 7.5 ± 0.36 kg after 16 exercise sessions (Cohen's d = -6.32, 95% CI -8.34, -6.68). In comparison, the control side, following a conventional high- intensity exercise regimen without BFR, showed a more modest strength increase of 4.4 ± 0.67 kg. A mean Patient's Global Impression of Change score of 2.2 reflected overall improvements in participants' daily activities and health status. CONCLUSION: This study highlights the feasibility and effectiveness of low-intensity blood flow restriction exercise as a safe and promising approach to enhancing forearm muscle strength in individuals with spinal cord injury. The observed positive outcomes, coupled with a high level of participant satisfaction, underscore the potential of this innovative method to significantly improve limb muscle strength, thereby contributing to greater functional independence in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".