Electroacupuncture May Improve Burning and Electric Shock-Like Neuropathic Pain: A Prospective Exploratory Pilot Study
Bibliographic record
Abstract
Objective: To test the effectiveness of electroacupuncture (EA) for managing intractable neuropathic pain (NeP) and assess the protocol for a larger confirmatory trial. Design: A prospective, multicenter, single-armed, add-on, pilot study. Settings/location: At two tertiary university-based hospitals in Seoul, Republic of Korea. Subjects: Patients with chronic peripheral NeP, who have received conventional oral medications but complained of moderate to severe pain. Interventions: Two Korean medicine doctors conducted 12 sessions of EA (2 sessions per week for 4 weeks, followed by 1 session per week for the second month) in addition to conventional treatment. Outcome measures: During the 8-week treatment period, pain intensity, pain natures such as burning, electric shock-like, temperature or mechanical hyperalgesia, and numbness, Short Form of the McGill Pain Questionnaire (SF-MPQ) and the Brief Pain Inventory (BPI-SF), the EuroQol five dimensions questionnaire, patients' satisfaction, and adverse events were evaluated. The primary endpoint was a change in pain intensity (%) at 4 weeks from the baseline. Results: Among 22 patients, 19 finished the protocol. The eight EA sessions over a month reduced pain intensity from 6.0 ± 1.6 at baseline to 3.2 ± 0.9 at 4 weeks, which was a 46.7% reduction (p < 0.001). The incidences of severe burning, electric shock-like pain, and mechanical hyperalgesia reduced at 8 weeks [36%–16% (p = 0.04), 53%–21% (p = 0.009), and 53%–26% (p = 0.03), respectively]. The affective dimensions in the SF-MPQ (p = 0.007) and the pain interference parameters, including mood (p = 0.02), relations with other people (p = 0.03), and enjoyment of life (p = 0.002) in the BPI-SF, were improved at 4 and 8 weeks. The majority of patients (68%) responded that their pain was “much or somewhat improved.” Overall, 84.2% expressed “satisfaction” with their multidisciplinary management. Conclusions: EA might decrease the intensity of NeP, in particular, such as burning, electric shock-like pain, and mechanical hyperalgesia, which was accompanied by psychosocial and functional improvement. A larger study is warranted to prove the effectiveness of EA for managing refractory NeP. Trial registration:ClinicalTrials.gov: NCT03315598. Retrospectively registered on October 20, 2017.
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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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".