Massage Therapy as a Complementary Treatment for Stiffness and Numbness Post Cervical Spinal Cord Injury: a Case Study
Bibliographic record
Abstract
Introduction: Spinal Cord Injuries (SCI) commonly result in pain, stiffness, weakness and numbness. There are limitations in the ability of the standard medical approach to manage many symptoms of SCI. This case study examined the effects of massage therapy as a "complementary" therapy to treat post-operative numbness and stiffness after removal of a cavernous hemangioma intermeshed with a 26-year-old male patient's spinal cord. Methods: The patient received eight, one-hour therapeutic massage sessions over five months. Therapeutic massage techniques were performed by a Board-Certified Therapeutic Massage and Bodywork Therapist and consisted of cranial sacral, Swedish, myofascial release, trigger point therapy, and passive stretching. Symptom intensity was recorded prior to each session on a qualitative scale (1-10) and was trended over the course of the study. Results: There was a slight decrease over time in left-arm and back numbness, as well as neck and upper body stiffness. The patient viewed therapeutic massage to be a beneficial component to his recovery. Discussion/Conclusion: Massage therapy should be considered as an adjunct therapy as part of a rehabilitation plan to address numbness and stiffness post-SCI. Further research is needed to understand the effects of massage therapy on SCI numbness and stiffness.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".