Resistance Training with Instability for Patients with Parkinson’s Disease
Bibliographic record
Abstract
PURPOSE: This randomized controlled trial compared the effects of resistance training (RT) and RT with instability (RTI) on the timed up and go test (TUG), on-medication Unified Parkinson's Disease Rating Scale part III motor subscale score (UPDRS-III), Montreal Cognitive Assessment (MoCA) score, Parkinson's Disease Questionnaire (PDQ-39) score, and muscle strength in the leg press exercise (one-repetition maximum) of patients with Parkinson's disease (PD). METHODS: Thirty-nine patients with moderate to severe PD were randomly assigned to a nonexercising control group (C), RT group, and RTI group. The RT and RTI groups performed progressive RT twice a week for 12 wk. However, only the RTI group used high motor complexity exercises (i.e., progressive RT with unstable devices), for example, half squat exercise on the BOSU® device. The primary outcome was mobility (TUG). The secondary outcomes were on-medication motor signs (UPDRS-III), cognitive impairment (MoCA), quality of life (PDQ-39), and muscle strength (one-repetition maximum). RESULTS: There were no differences between RTI and RT groups for any of the outcomes at posttraining (P > 0.05). However, there were differences between RTI and C groups in the TUG, MoCA, and muscle strength values at posttraining (P < 0.05). Only the RTI group improved the TUG (-1.9 s), UPDRS-III score (-4.5 score), MoCA score (6.0 score), and PDQ-39 score (-5.2 score) from pre- to posttraining (P < 0.001). Muscle strength improved for both training groups (P < 0.001). No adverse events were reported during the trial. CONCLUSIONS: Both training protocols improved muscle strength, but only RTI improved the mobility, motor signs, cognitive impairment, and quality of life, likely because of the usage of high motor complexity exercises. Thus, RTI may be recommended as an innovative adjunct therapeutic intervention for patients with PD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".