Electroacupuncture to treat painful diabetic neuropathy: study protocol for a three-armed, randomized, controlled pilot trial
Bibliographic record
Abstract
BACKGROUND: The purpose of this study is to conduct a basic analysis of the effectiveness and safety of electroacupuncture in the treatment of painful diabetic neuropathy (PDN) as compared to placebo and usual care and to evaluate the feasibility of large-scale clinical research. METHODS/DESIGN: This study is a protocol for a three-armed, randomized, patient-assessor-blinded (to the type of treatment), controlled pilot trial. Forty-five participants with a ≥ six month history of PDN and a mean weekly pain score of ≥ 4 on the 11-point Pain Intensity Numerical Rating Scale (PI-NRS) will be assigned to the electroacupuncture group (n = 15), sham group (n = 15) or usual care group (n = 15). The participants assigned to the electroacupuncture group will receive electroacupuncture (remaining for 30 minutes with a mixed current of 2 Hz/120 Hz and 80% of the bearable intensity) at 12 standard acupuncture points (bilateral ST36, GB39, SP9, SP6, LR3 and GB41) twice per week for eight weeks (a total of 16 sessions) as well as the usual care. The participants in the sham group will receive sham electroacupuncture (no electrical current will be passed to the needle, but the light will be seen, and the sound of the pulse generator will be heard by the participants) at non-acupuncture points as well as the usual care. The participants in the usual care group will not receive electroacupuncture treatment during the study period and will receive only the usual care. The follow-up will be in the 5th, 9th and 17th weeks after random allocation. The PI-NRS score assessed at the ninth week will be the primary outcome measurement used in this study. The Short-Form McGill Pain Questionnaire (SF-MPQ), a sleep disturbance score (11-point Likert scale), the Short-Form 36v2 Health Survey (SF-36), the Beck Depression Inventory (BDI) and the Patient Global Impression of Change (PGIC) will be used as outcome variables to evaluate the effectiveness of the acupuncture. Safety will be assessed at every visit. DISCUSSION: The result of this trial will provide a basis for the effectiveness and safety of electroacupuncture for PDN. TRIAL REGISTRATION: Clinical Research information Service. Unique identifier: KCT0000466.
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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 | 0.033 | 0.024 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.051 | 0.010 |
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".