Sharp-Hook Acupuncture (<i>Feng Gou Zhen</i>) for Patients with Periarthritis of Shoulder: A Randomized Controlled Trial
Bibliographic record
Abstract
The Feng Gou Zhen (sharp-hook acupuncture) as a traditional form of ancient acupuncture is said to be particularly effective for managing periarthritis of shoulder. We conducted this randomized controlled trial to evaluate the effectiveness of Feng Gou Zhen as an add-on compared to conventional analgesics for patients with PAS. 132 patients were randomly assigned in a 1 : 1 ratio to either a acupuncture group receiving sharp-hook acupuncture plus acupoint injection with conventional analgesics or a control group. Patients from both groups were evaluated at week 0 (baseline), week 1, and week 4. The primary outcome measure was the change from baseline shoulder pain, measured by Visual Analogue Scale at 7 days after treatment. Secondary outcome measures include the (i) function of shoulder joint and (ii) McGill pain questionnaire. The results showed that patients in acupuncture group had better pain relief and function recovery compared with control group (P < 0.05) at 1 week after treatment. Moreover, there were statistical differences between two groups in VAS and shoulder joint function and McGill pain questionnaire at 4 weeks after treatment (P < 0.05). Therefore, the sharp-hook acupuncture helps to relieve the pain and restore the shoulder function for patients with periarthritis of shoulder.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".