Peripheral magnetic stimulation for the treatment of fibromyalgia: a systematic review and meta-analysis
Bibliographic record
Abstract
Objectives To systematically review and conduct a meta-analysis of studies on peripheral magnetic stimulation (PMS) for fibromyalgia (FM) treatment.Methods MEDLINE, EMBASE, CENTRAL, CINHAL, Web of Science, and ProQuest databases were searched from inception to July 2023 for studies in adult patients with FM treated with PMS. Studies using transcranial magnetic stimulation were excluded.Results Six randomized controlled trials (RCTs) (n = 279 patients) were identified and included in the review. PMS regimens varied, ranging from 8 to 40 min per session over 3–84 days. All studies compared PMS to a visually and physically identical sham device without magnetic fields. Most of the included studies demonstrated positive findings for PMS on pain and functional outcomes. In our meta-analysis, PMS significantly reduced pain scores within 1–3 months (mean difference −1.86 on NRS, 95% confidence interval −2.85 to −0.87, p = 0.0002, I2 = 68%, 4 studies [154 participants], low quality of evidence), but not at ≥3 months (low quality of evidence). Minimal adverse effects were reported.Discussion Evidence for PMS use in FM is encouraging for short-term benefit. However, heterogeneous patient populations, varied PMS regimens, and limited number of studies are important limitations. Large, high-quality RCTs are needed to confirm PMS benefits and to make definitive recommendations.Protocol registration PROSPERO Identifier is CRD42021235164.
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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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".