Acupuncture for Comorbid Mild-Moderate Depression and Chronic Musculoskeletal Pain: Study Protocol for A Randomized Controlled Trial
Bibliographic record
Abstract
Abstract Background: Depression and Chronic musculoskeletal pain (CMSP) are the leading causes of global years lived with disability diseases. Moreover, they often commonly coexist, which made a great difficult to diagnosis and treatment. A safe and effective treatment was urgently need. Previous studies showed that acupuncture was a cost-effective treatment for simple depression or CMSP. But limited evidence showed that acupuncture was effective for depression comorbid CMSP. Methods: This is a randomized, sham acupuncture-controlled trial with three arms: real acupuncture (RA), sham acupuncture (SA) and healthy control (HC). 48 depression combined CMSP participants and 12 healthy people will be recruited from GDTCM hospital and randomized 2:2:1 to RA, SA, HC group. The patients will receive RA or SA intervention for 8 weeks, and HC will not receive any intervention. Upon completion of the intervention, there is a 4 weeks follow-up. The primary outcome measures will be severity of depression and pain which assessed by Hamilton depression rating scale (HAMD-17) and brief pain inventory (BPI), respectively. The secondary outcome measures will be cognitive function, and quality of life which measured by Montreal cognitive assessment (MoCA), P300 and world health organization quality of life (WHOQOL-BREF). In addition, the correlation between brain derived neurotrophic factor (BDNF) and symptoms will also be determined. Discussion : The aim of this study is to evaluate the clinic efficacy and underlying mechanism of acupuncture on depression comorbid CMSP. This study will provide a convenient and cost-effectively means for future prevention and treatment of combined depression and CMSP. Trial registration: This study pre-registered at 2th Feb 2018, at Chinese Clinical Trail Registry (ChiCTR1800014754). The study is on the recruiting status.
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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 | 0.079 | 0.067 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.008 |
| 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; both teacher heads agree on what is shown here.
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".