A Multicenter Randomized Controlled Trial on Intervention Methods of TCM for Sub-health Status of Neck and Back Pain
Bibliographic record
Abstract
Objective To compare the effect of different TCM methods on sub-health status of neck and back pain by the study of RCT,and establish an effective intervention method of TCM.Methods 195 patients were randomly assigned to daoyin group,manipulation group and blank control group.The curative effect of each group was observed with short-form McGill Pain Questionnaire,indexes of pain,MCU detection system and the World Health Organization Quality of Life BREF(WHOQOL-BREF).Results The pain scores were decreased in daoyin group and manipulation group,but there was no significant difference between them;the content of plasma β-EP and 5-HT did not change significantly before and after the treatment in three groups;the MCU index improved significantly after the treatment in daoyin group and manipulation group,the improvement of MCU muscle strength index in daoyin group was better than that of manipulation group,and the improvement of MCU activity index in manipulation group was better than that of daoyin group;the WHOQOL-BREF table scores were increased in daoyin group and manipulation group,but there was no significant difference between them.Conclusion Intervention methods of TCM such as daoyin and manipulation,can effectively improve the sub-health status of neck and back pain,decrease the pain scores,increase cervical muscle strength and activity of cervical vertebra,improve life quality,and daoyin has advantages in increasing muscle strength and manipulation has advantages in increasing the activity of cervical vertebra.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".