Comparative efficacy of moxibustion as an add-on treatment with different durations for diabetic peripheral neuropathy: study protocol for a randomized controlled trial
Bibliographic record
Abstract
Background: Diabetic Peripheral Neuropathy (DPN) can markedly diminish patients' quality of life. Current treatments provide limited relief, driving interest in non-invasive options such as moxibustion. Moxibustion, a technique rooted in acupuncture, shows promise for managing pain. However, it lacks standardized protocols for treating DPN, especially concerning moxibustion duration, and its effectiveness for DPN is not well-supported by evidence. Thus, this study seeks to identify the optimal moxibustion duration to relieve DPN symptoms and enhance nerve function, filling an important gap in clinical practice. Methods: Participants will be randomly allocated to three clinical centers, with 30 individuals at each center, and evenly divided among the conventional treatment group, the 15-min moxibustion group, and the 30-min moxibustion group. The conventional treatment group will be administered mecobalamin and epalrestat for a duration of 4 weeks, while the moxibustion groups will receive moxubustion as an add-on therapy treatment twice a week over the same period. The duration of moxibustion differs from the 15-min group, while the procedure remains consistent across the moxibustion groups. The primary outcome is total clinical effectiveness. The second outcomes include electrophysiological examination, the Toronto Clinical Scoring System (TCSS), the Visual Analogue Scale (VAS), the Traditional Chinese Medicine Syndrome Score Scale (TCMS), and infrared thermography testing. The outcomes will be assessed during the baseline period, after the 8th treatment, and at the one-month follow-up. Conclusion: This trial aims to identify the optimal moxibustion duration for DPN symptom relief and nerve function improvement, offering evidence for standardized clinical protocols. The findings could enhance treatment efficacy, reduce adverse effects, and alleviate DPN's socio-economic burden. Clinical trial registration: https://clinicaltrials.gov/, NCT06330233.
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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 | 0.021 | 0.021 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.052 | 0.007 |
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".