A Systematic Review and Meta-analysis Investigating the Pain-Relieving Effect of Interferential Current on Musculoskeletal Pain
Bibliographic record
Abstract
BACKGROUND: Interferential current is one of the most common electrotherapeutic modalities used in the treatment of painful conditions. Patients seeking medical help to reduce their musculoskeletal pain can be treated using interferential current. OBJECTIVE: The current review aimed to analyze the recently available information regarding the efficacy of interferential current in alleviating the pain of musculoskeletal origin. METHODS: This study used Scopus, CINAHL, Cochrane Library, Web of Science, MEDLINE, Embase, and EBSCOas as data sources. The initial selection of the studies, thorough assessment of the full articles, and extraction of the necessary study characteristics were carried out by two independent reviewers. Another two independent reviewers assessed the methodological quality of each included trial against 39 criteria. These criteria were integrated from several popular scales. Pain intensity-measured using the visual analog scale, numeric pain rating scale, or McGill Pain Questionnaire-was the outcome of interest. RESULTS: This review included 35 trials of variable methodological quality from which 19 trials were selected for the meta-analysis. In general, interferential current alone versus placebo demonstrated a significant pain-relieving effect. On the other hand, interferential current showed no significant difference when added to standard treatment compared with placebo plus standard treatment or standard treatment alone. Similarly, interferential current showed no significant difference when compared with other single interventions (laser, transcutaneous electrical nerve stimulation, cryotherapy). CONCLUSIONS: Interferential current alone is better than placebo at discharge. However, the low number of studies raises suspicions about this conclusion. Interferential current alone or added to other interventions is not more effective than comparative treatments in relieving musculoskeletal pain.
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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 | 0.018 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 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) | 0.005 | 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".