The Effect of a Stretch and Strength-Based Yoga Exercise Program on Patients with Neuropathic Pain due to Lumbar Disc Herniation
Bibliographic record
Abstract
STUDY DESIGN: Randomized controlled trial. OBJECTIVE: To investigate the effect of a stretch and strengthbased yoga exercise program on neuropathic pain due to LDH. SUMMARY OF BACKGROUND DATA: LDH with neuropathic pain influences treatment outcomes negatively. Most yoga poses include the parameters of spinal training and help reduce pain and disability in patients with low back injuries. We hypothesized that yoga positively affects both LDH and neuropathic pain by increasing mobilization, core muscle strength, and spinal and hamstring flexibility. METHODS: In total, 48 patients with neuropathic pain due to LDH were randomly assigned to a control group and a yoga group. All patients underwent a patient education program. In addition, the selected yoga exercise was taught and performed to the yoga group for one hour twice weekly for 12 weeks. Neuropathic pain (Douleur Neuropathique 4 for diagnosis; Leeds Assessment of Neuropathic Symptoms and Signs for severity), low back pain (the short-form of McGill Pain Questionnaire), disability (Oswestry Disability Index), and function (modified Schober and passive knee extension test) were measured blind before and at the one-, three-, and six-month follow-ups. The patient global assessment was applied at the six-month followup. The intention-to-treat analysis was performed in this study. RESULTS: The intention-to-treat analysis showed a statistically significant difference in neuropathic pain, patient global assess ment, low back pain, disability, and function in favor of the yoga group at post-treatment. The between-group effect sizes were moderate at six-months follow-up. CONCLUSION: It was determined that the selected stretch and strength-based yoga exercise could be a promising treatment option for neuropathic pain due to LDH. LEVEL OF EVIDENCE: 2.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".