[Comparison of the analgesic effect of acupuncture between otopoint-penetrative needling and otopoint-straight needling for cervical type and nerve-root type cervicospondylopathy].
Bibliographic record
Abstract
OBJECTIVE: To confirm the better analgesic effect of otopoint-penetrative needling for cervical type and nerve-root type cervicospondylopathy. METHODS: A total of 98 cervicospondylopathy outpatients (50 cases of cervical type and 48 cases of nerve-root type) were randomly divided into treatment group (otopoint-penetrative needling) and control group (otopoint-straight needling) in the light of paring method of comprehensive factors of sexes, ages and the state of disease. The main oto-points used were bilateral Jingzhui Area (AH 13) in combination with Jian-Jianguanjie-Suogu (Shoulder-Shoulder-joint-Collarbone) Area, etc. The simplified McGill Pain Scaling was used to give the score of patient's pain before the treatment, 5 min and 30 min after the treatment. RESULTS: Results of sequential trial indicated that the analgesic effect of otopoint-penetrative needling was significantly superior to that of otopoint-straight needling 30 min after the treatment (P < 0.05). Findings of matched-pair t test showed that no marked differences were found between two groups in the pain scores before the treatment, while after the treatment, the pain scores of otopoint-penetrative needling group were significantly lower than those of otopoint-straight needling group (P < 0.001, 0.01), meaning that the analgesic effect of otopoint-penetrative needling was significantly better than that of otopoint-straight needling 5 min and 30 min after the treatment in both men and women, in both cervical type and nerve-root type patients, and in both young and older patients. CONCLUSION: The analgesic effect of otopoint-penetrative needling is obviously superior to that of otopoint-straight needling.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".