Pulsed Radiofrequency of Suprascapular Nerve for Chronic Shoulder Pain: A Randomized Double‐Blind Active Placebo‐Controlled Study
Bibliographic record
Abstract
BACKGROUND: The suprascapular nerve block is frequently implemented to treat chronic shoulder pain. Although effective the nerve blockade provides only a short-term relief, and more compelling apaproaches have been investigated. Pulsed radiofrequency (pRF) has been anecdotally reported as safe and reliable method. However, formal efficacy study has not been published. Ostensibly evidence-based validation of a new method is necessary for both scholastic and practical purposes. METHODS: This study was designed as a randomized active placebo-control double-blind trial. Because of encountered difficulties in recruitment and high rate of dropout, the study was redesigned as to allow a smaller sample size and statistical analyses were performed utilizing the last observation carry forward method. Lidocaine injections alone or with combination of the pRF were performed. Participants were followed up during 6 months, and multiple subjective and objective outcome variables were recorded. RESULTS: Thirteen of 22 participants completed 6 months follow-up. Dropout rate was higher in the lidocaine group. A significant linear trend (P < 0.05) for improvement on the numeric rating scale, Shoulder Pain and Disability Index and Constant-Murley score was observed in the pRF group, but not in the lidocaine group. Patients in the pRF group were on average more satisfied than the lidocaine group at 1 month (P = 0.041) and at 3 months (P = 0.035). DISCUSSION: Considering limitations of the study design and statistics, it seems plausible to attribute better results in the pRF group to unique properties of this physical modality.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".