[Resuscitation acupuncture for thalamic pain:a randomized controlled trial].
Bibliographic record
Abstract
OBJECTIVE: To compare the effects between resuscitation acupuncture and pregabalin for thalamic pain and their impacts on plasma P substance (SP) and β-endorphin (β-EP). METHODS: Sixty-four patients were randomly assigned into an acupuncture group and a western medication group, 32 cases in each one. Based on conventional western methods, pregabalin capsule was used orally in the western medication group, 75 mg a time,twice a day; resuscitation acupuncture was applied in the acupuncture group. The main acupoints were Shuigou (GV 26), Neiguan (PC 6), Sanyinjiao (SP 6). Patients with upper limb pain were attached affected Jiquan (HT 1), Chize (LU 5), and Hegu (LI 4); lower limb pain, affected Weizhong (BL 40), Zusanli (ST 36); hea-dache, bilateral Fengchi (GB 20), Wangu (GB 12), and Yifeng (TE 17), twice a day. Treatment was given 6 d a week for 8 weeks in the two groups. The changes of simplified McGill pain questionnaire (SF-MPQ), plasma SP and β-EP were observed before and after 4-week, 8-week treatment, as well as at follow-up, namely, 3 months after treatment. Also, clinical effects were evaluated. RESULTS: <0.05). CONCLUSIONS: Resuscitation acupuncture can effectively relieve the symptoms of thalamic pain with stable and long-term effect, and it is better than pregabalin. Meanwhile, the acupuncture can increase β-EP and reduce SP.
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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) | 0.004 | 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 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".