Acupuncture for chronic neck pain with sensitive points: study protocol for a multicentre randomised controlled trial
Bibliographic record
Abstract
Introduction Chronic neck pain is a challenging condition to treat in clinical practice and has a considerable impact on quality of life and disability. According to the theory of traditional Chinese medicine, acupoints and tender points may become sensitised when the body is in a diseased state. Stimulation of such sensitive points may lead to disease improvement and improved clinical efficacy. This study aims to evaluate the efficacy and safety of needling at sensitive acupoints in providing pain relief, improvement of cervical vertebral function and quality of life in patients with chronic neck pain. Methods and analysis This multicentre, randomised controlled, explanatory and parallel clinical trial will include 716 patients with chronic neck pain. Study participants will be randomly assigned in a 1:1:1:1 ratio to four treatment groups: the highly sensitive acupoints group, low/non-sensitive acupoints group, sham acupuncture group and waiting-list control group. The primary outcome will be the change in the visual analogue scale score for neck pain from baseline to 4 weeks. Secondary outcomes will be the Northwick Park Neck Pain Questionnaire and McGill pain questionnaire, 12-item Short-Form health survey, Neck Disability Index, changes in the pressure pain threshold, range of cervical motion, Self-Rating Anxiety Scale, Self-Rating Depression Scale and adverse events before treatment, post-treatment, and at 4, 8, 12, 16 and 20 weeks post-treatment. The intention-to-treat approach will be used in the statistical analysis. Group comparisons will be undertaken using χ 2 tests for categorical characteristics, and analysis of variance for continuous variables to analyse whether acupuncture in the highly sensitive acupoints group achieves better treatment outcomes than in each of the other three groups. Ethics and dissemination Ethical approval of this study has been granted by the local Institutional Review Board (ID: 2017 KL-038). The outcomes of the trial will be disseminated through peer-reviewed publications. Trial registration number ChiCTR1800016371; Pre-results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 teacher head, 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".