Effectiveness and safety of acupotomy on lumbar spinal stenosis
Bibliographic record
Abstract
Abstract Introduction: Lumbar spinal stenosis (LSS) is a pathological condition that causes a variety of neurological symptoms due to narrowing of the anatomical structures; usually, conservative treatment is recommended, rather than surgical treatment. Acupotomy combines conventional acupuncture with small scalpels; the procedure can be considered minimally invasive, and has recently received considerable attention in clinical practice. Still, there is a lack of data and randomized controlled trials regarding acupotomy related to LSS. Additional studies are necessary, considering the low methodological quality and small size of the study. Methods and analysis: This is a pragmatic, pilot, randomized controlled trial. The trial comprises 8 weeks of treatment, with 16 visits and a 4-week follow-up period. Forty participants diagnosed with LSS will be randomly assigned to either the experimental or control groups; both groups will receive acupuncture and interferential current therapy twice a week for 8 weeks, while the experimental group will receive an additional acupotomy intervention once a week for 8 weeks. The primary outcome will be assessed using the visual analog scale; the secondary outcome will be measured by self-rated walking distance, Oswestry Disability Index, and short-form McGill Pain Questionnaire. Measurements will be obtained prior to the start of the clinical trial, 4 weeks after the interventional procedure, 8 weeks after the procedure, and 4 weeks after the end of the interventional procedure. Blood tests and adverse reactions will be performed to ensure safety of the treatments. Conclusion: We expect that this study will provide basic data for future large-scale acupotomy studies regarding LSS.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.004 | 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".