Percutaneous Electrical Nerve Stimulation for Chronic Knee Pain: A Randomized, Sham-controlled Trial.
Bibliographic record
Abstract
CONTEXT: Anti-inflammatory drugs are often used to treat chronic knee pain (CKP), but their long-term use is associated with decreased effectiveness and numerous side effects. Complementary and alternative medicine provides additional treatments for the condition, including percutaneous electrical nerve stimulation (PENS). However, the benefits of PENS for treatment of CKP are still controversial. OBJECTIVE: The study intended to assess the effects and safety of PENS for treatment of CKP. METHODS: This study was a 2-arm, randomized, sham-controlled trial. SETTING: The study took place at the Fourth People's Hospital of Shaanxi (Xi'an, China). PARTICIPANTS: Participants were 72 patients at the hospital being treated for CKP. INTERVENTION: Participants were randomly divided into a real PENS group and a sham PENS group at a ratio of 1:1. All patients received etoricoxib and either real or sham PENS therapy, 3 ×/wk for 8 wk, at the same local acupoints around the knee. OUTCOME MEASURES: The primary outcome, pain, was measured on a numeric rating scale (NRS). Secondary outcomes, stiffness and physical function, were evaluated using the Western Ontario and McMaster Universities arthritis index (WOMAC) and the short-form 36-item health survey (SF-36) to obtain a score on the physical component scale (PCS) and the mental component scale (MCS). The NRS and the WOMAC were administered at initiation of treatment to establish a baseline and again after 8 wk of treatment. The SF-36 was administered postintervention. RESULTS: At the end of 8 wk, the group receiving the real PENS exhibited statistically significant improvements in both primary and secondary outcomes compared with the group receiving the sham PENS treatment. CONCLUSIONS: The findings suggest that treatment with the real PENS with etoricoxib is effective for treatment of CKP.
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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 | 0.003 | 0.008 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".