The Efficacy of Pulsed Electromagnetic Fields on Pain, Stiffness, and Physical Function in Osteoarthritis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background. Although there are many pharmacological interventions for adults with osteoarthritis (OA) who do not meet the indications for surgery, side effects and adverse effects cannot be ignored. Physical interventions are known for their effectiveness and safety, and pulsed electromagnetic fields (PEMFs) have already been applied to skeletal diseases such as osteoporosis. Objective. In this systematic review and meta-analysis, we aimed to assess the efficacy of PEMF on the major symptoms of patients with OA compared with efficacy of other interventions. Methods. Randomized controlled trials (RCTs) investigating OA patients treated with PEMF and with pain, stiffness, and physical function impairment since 2009 were included. The Visual Analog Scale (VAS) and Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) scores were used for assessment. All extracted data were analyzed using RevMan V.5.3. Results. Eleven RCTs consisting of 614 patients were enrolled in this meta-analysis, of which 10 trials comprised knee OA and one comprised hand OA. Compared with the control groups, the PEMF treatment yielded a more favorable output. PEMF alleviated pain (standardized mean differences [SMD] = 0.71, 95% confidence interval [CI]: 0.08–1.34, p = 0.03), improved stiffness (SMD = 1.34, 95% CI: 0.45–2.23, p = 0.003 ), and restored physical function (SMD = 1.52, 95% CI: 0.49–2.55, p = 0.004 ). Conclusions. PEMF therapy ameliorates OA symptoms such as pain, stiffness, and physical function in patients compared to other conservative treatments. There is an urgent need to search for different types of OA in multiple locations.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".