Effects of transcutaneous electrical nerve stimulation (TENS) and interferential currents (IFC) in patients with nonspecific chronic low back pain: randomized clinical trial
Bibliographic record
Abstract
CONTEXT AND OBJECTIVE: Transcutaneous electrical nerve stimulation (TENS) and interferential current are the most used electrotherapy methods, although there is little scientific evidence to support their use. The aim of this study was to compare the effects of TENS and interferential current among patients with nonspecific chronic low back pain. DESIGN AND SETTING: Single-blind randomized controlled trial in the Department of Physiotherapy, Centro Universitário de Maringá. METHODS: One hundred and fifty patients were randomly divided into three groups: TENS (group 1), interferential current (group 2) and controls (group 3). The patients designated for electrotherapy received ten 30-minute sessions, while the control group remained untreated. All patients and controls were evaluated before and after treatment using a visual analog scale and the McGill Pain and Roland Morris questionnaires, and regarding their use of additional medications. RESULTS: There was a mean reduction on the visual analog scale of 39.18 mm with TENS, 44.86 mm with interferential current and 8.53 mm among the controls. In the Roland Morris questionnaire, group 1 had a mean reduction of 6.59; group 2, 7.20; and group 3, 0.70 points. In group 1, 84% of the patients stopped using medications after the treatment; in group 2, 75%; and in group 3, 34%. There was no statistically significant difference between the TENS and interferential current groups (P > 0.05); a difference was only found between these groups and the controls (P < 0.0001). CONCLUSION: There was no difference between TENS and interferential current for chronic low back pain treatment. CLINICAL TRIAL REGISTRATION: NCT01017913.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".