[Clinical observation on deep needling at Xiaguan (ST 7) with round sharp needle combined with plum-blossom needle for trigeminal neuralgia of wind and heat].
Bibliographic record
Abstract
OBJECTIVE: To compare the clinical therapeutic effect between deep needling at Xiaguan (ST 7) with round sharp needle combined with plum-blossom needle and conventional acupuncture in patients with trigeminal neuralgia (TN) of wind and heat, and explore its mechanism. METHODS: A total of 60 patients with TN of wind and heat were randomized into an observation group (30 cases) and a control group (30 cases). In the observation group, deep needling with round sharp needle was applied at Xiaguan (ST 7), and tapping with plum-blossom needle was applied at Yangbai (GB 14), Quanliao (SI 18), Dicang (ST 4), Sibai (ST 2), etc. of affected side. In the control group, conventional acupuncture was applied at the same acupoints selected in the observation group. The treatment was given once a day, 5 times a week for 4 weeks in the both groups. Before and after treatment, the scores of short-form McGill pain questionnaire (SF-MPQ), TCM syndrome, patient global impression of change (PGIC) and comprehensive symptom were observed, the serum levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), vasoactive intestinal peptide (VIP) and β-endorphin (β-EP) were detected, and the adverse reaction was observed in the both groups. RESULTS: <0.05). No severe adverse reaction was observed in the both groups. CONCLUSION: Deep needling at Xiaguan (ST 7) with round sharp needle combined with plum-blossom needle can effectively treat the trigeminal neuralgia of wind and heat and relieve pain, its therapeutic effect is superior to conventional acupuncture. The mechanism may be related to the regulation of serum IL-6, TNF-α, VIP and β-EP.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".