Effects of focal muscle vibration on cervical pain in Parkinson’s disease patients: a pilot study
Bibliographic record
Abstract
Musculoskeletal pain is a common symptom of Parkinson's disease (PD) that is not adequately treated with current dopaminergic drugs. This pilot study sought to investigate the effect of focal muscle vibration (fMV) on a group of Parkinson's disease patients suffering from chronic cervical pain. In addition to conventional physiotherapy, twenty-two patients with idiopathic Parkinson's disease (Hoehn and Yahr stages II-III) received three weeks of bilateral focal musclevibration to the trapezius muscles. The Visual Analogue Scale (VAS), the Short-form McGill, and the Present PainIntensity scales were used to assess pain at baseline (T0), after three weeks of treatment (T1), one week after the last treatment session (T2), and three weeks after T2 (T3). Pain intensity decreased significantly from baseline to T1 across all pain scales (p < 0.0001). Furthermore, the beneficial effect of fMV on cervical pain lasted up to one month after treatment. Our findings show that fMV, in combination with conventional physiotherapy, is effective at reducing pain intensity in PD patients, with results visible even after a month of follow-up.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".