Effects of meridian sinew tuina after identifying the treatment area under ultrasound localization combined with greater and third occipital nerve injections in cervicogenic headache: a randomized controlled trial protocol
Bibliographic record
Abstract
Introduction: Cervicogenic headache (CEH) is a secondary headache characterized by chronic, unilateral headache. Ultrasound-guided injections of the greater occipital nerve (GON) and the third occipital nerve (TON) are effective in the treatment of CEH, as is meridian sinew tuina for the treatment of CEH, but the evidence of clinical efficacy of combining these two therapies is valid. Therefore, we have designed a randomized controlled trial with the aim of investigating the efficacy and safety of ultrasound localization meridian sinew tuina combined with GON and TON injections for the treatment of CEH. Methods and analysis: In this study, we enroll 60 patients experiencing CEH. The control group receives ultrasound-guided injections of GON and TON. The intervention group is treated with ultrasound localization meridian sinew tuina combined with the injection of GON and TON. Meridian sinew tuina is performed once a day for 30 min for 3 days. The primary observational index includes the Short-Form of McGill Pain Questionnaire (SF-MPQ). The Secondary outcomes include Cervical Range of Motion (ROM) and Medical Infrared Thermography (MIT). MIT is used to measure the change in skin temperature in the area of the patient's meridian sinew tuina treatment of GON and TON before and after the intervention. There are 5 time points assessed as baseline, day 3, day 15, day 30, and day 60. Discussion: This study proposes to combine ultrasound-guided injections of GON and TON for the treatment of CEH after identifying the treatment area of meridian sinew tuina under ultrasound localization. Meanwhile, MIT is utilized to provide objective evidence of the efficacy of CEH. Clinical trial registration: ChiCTR2300076128.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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".