A Wearable Proprioceptive Stabilizer (Equistasi®) for Rehabilitation of Postural Instability in Parkinson’s Disease: A Phase II Randomized Double-Blind, Double-Dummy, Controlled Study
Bibliographic record
Abstract
BACKGROUND: Muscle spindles endings are extremely sensitive to externally applied vibrations, and under such circumstances they convey proprioceptive inflows to the central nervous system that modulate the spinal reflexes excitability or the muscle responses elicited by postural perturbations. The aim of this pilot study is to test the feasibility and effectiveness of a balance training program in association with a wearable proprioceptive stabilizer (Equistasi) that emits focal mechanical vibrations in patients with PD. METHODS: Forty patients with PD were randomly divided in two groups wearing an active or inactive device. All the patients received a 2-month intensive program of balance training. Assessments were performed at baseline, after the rehabilitation period (T1), and two more months after (T2). Posturographic measures were used as primary endpoint; secondary measures of outcome included the number of falls and several clinical scales for balance and quality of life. RESULTS: Both groups improved at the end of the rehabilitation period and we did not find significant between-group differences in any of the principal posturographic measures with the exception of higher sway area and limit of stability on the instrumental functional reach test during visual deprivation at T1 in the Equistasi group. As for the secondary outcome, we found an overall better outcome in patients enrolled in the Equistasi group: 1) significant improvement at T1 on Berg Balance Scale (+45.0%, p = .026), Activities-specific Balance Confidence (+83.7, p = .004), Falls Efficacy Scale (-33.3%, p = .026) and PDQ-39 (-48.8%, p = .004); 2) sustained improvement at T2 in terms of UPDRS-III, Berg Balance Scales, Time Up and Go and PDQ-39; 3) significant and sustained reduction of the falls rate. CONCLUSIONS: This pilot trial shows that a physiotherapy program for training balance in association with focal mechanical vibration exerted by a wearable proprioceptive stabilizer might be superior than rehabilitation alone in improving patients' balance. TRIAL REGISTRATION: EudraCT 2013-003020-36 and ClinicalTrials.gov (number not assigned).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".