Repetitive Transcranial Magnetic Stimulation and Motor Control Exercise for Chronic Low Back Pain: The ExTraStim Randomized Placebo-Controlled Trial
Bibliographic record
Abstract
OBJECTIVES: To (1) assess the efficacy of combining repetitive transcranial magnetic stimulation (rTMS) and motor control exercise on pain intensity compared to each intervention alone or a placebo in patients with nonspecific chronic low back pain (CLBP), and (2) evaluate the effects of motor control exercise versus no–motor control exercise, and active rTMS versus sham rTMS. DESIGN: Factorial randomized controlled trial. METHODS: Adults aged 18 to 65 years with nonspecific CLBP were randomly assigned in a 1:1:1:1 ratio to 1 of 4 groups: active rTMS, sham rTMS, active rTMS + motor control exercise, and sham rTMS + motor control exercise. Participants received 10 sessions of their allocated intervention over 8 weeks. Active and sham rTMS were performed over the primary motor cortex (10 Hz, 2000 pulses/session). The primary outcome was the average pain intensity at 8 weeks. RESULTS: One hundred forty participants (80 females; mean age, 38.4 years) were recruited. Pain intensity significantly reduced over time, with no difference between groups. At 8 weeks, active rTMS + motor control exercise was not better than active rTMS (mean difference [MD], 0.1; 95% confidence interval [CI]: −1.0, 1.1; P = .89), sham rTMS (MD, 0.1; 95% CI:−0.9, 1.1; P = .83), or sham rTMS + motor control exercise (MD, 0.8; 95% CI: −0.3, 1.8; P = .15) to reduce pain. No significant differences in pain intensity were found between active and sham rTMS groups, with or without motor control exercise at 8 weeks. CONCLUSIONS: Combining rTMS and motor control exercise did not significantly reduce pain intensity compared to each intervention used alone or placebo in participants with CLBP. J Orthop Sports Phys Ther 2026;56(1):28-37. Epub 30 October 2025. doi:10.2519/jospt.2025.13681
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".