A Randomized Controlled Clinical Trial of Treatment of Lumbar Disc Herniation-induced Sciatica by Acupuncture Stimulation of Sciatic Nerve Trunk
Bibliographic record
Abstract
Objective To observe the efficacy of acupuncture stimulation of the sciatic nerve trunk in the treatment of patients suffering from sciatica induced by lumbar disc herniation(LDH).Methods A total of 60 LDH sciatica patients met the inclusion criteria were randomly divided into treatment group and control group,with 30 cases in each.Patients of the treatment group were treated by directly needling the sciatic nerve and routine acupuncture of Ashi-points,Lumbar Jiaji(EX-B 2),Dachangshu(BL 28),etc.,and those of the control group treated by simple routine acupuncture.The treatment was conducted once a day,5times a week,4weeks altogether.The clinical effect was evaluated according to the"Standards for Diagnosis and Therapeutic Effect Evaluation of Syndromes of Chinese Medicine"and the pain intensity was assessed by using simplified Short-Form McGill Pain Questionnaire(SF-MPQ)containing pain rating index(PRI),visual analogue scale(VAS)and present pain intensity(PPI).Results After the treatment,of the two 30 cases of LDH sciatica patients in the control and treatment groups,11 and 18were cured,7and 7experienced marked improvement,10 and 4were effective,2and 1was invalid,with the effective rate being 93.3% and 96.7%,respectively.The cured+markedly effective rate of the treatment group was significantly higher than that of the control group(P<0.05,83.3% vs 60.0%).Compared with pre-treatment,the scores of PRI,VAS and PPI were evidently lowered in both groups(P<0.01),and the effect of the treatment group was notably better than that of the control group(P<0.01).Conclusion Acupuncture stimulation of the sciatic nerve trunk is effective in relieving sciatica in LDH patients,and is superior to simple routine acupuncture in the clinical efficacy.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".