Land Plus Aquatic Therapy Versus Land-Based Rehabilitation Alone for the Treatment of Freezing of Gait in Parkinson Disease: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Freezing of gait (FOG) is one of the most disabling symptoms of Parkinson disease (PD). Different land-based rehabilitation approaches based on motor and cognitive strategies can be effective in treating FOG. Although there are data about the efficacy of aquatic therapy in ameliorating this phenomenon, no study has explored the combined effect of land-based therapies plus aquatic therapy in patients with PD who have FOG. OBJECTIVE: The objective was to investigate the effectiveness of a multidisciplinary, intensive, motor-cognitive rehabilitation treatment (MIRT) in improving FOG and whether implementation with aquatic therapy (MIRT-AT) adds further benefits. DESIGN: The design consisted of a single-blind, parallel-group, 1:1 allocation ratio, randomized trial. SETTING: The Department of Parkinson Disease, Movement Disorders and Brain Injury Rehabilitation at "Moriggia-Pelascini" Hospital (Gravedona ed Uniti, Como, Italy) was used as the setting. PARTICIPANTS: Sixty hospitalized patients with PD who had FOG in Hoehn and Yahr stage 2 or 5-3 were included. INTERVENTION: Sixty patients with PD + FOG were randomly assigned to 2 groups: 30 underwent a 4-week MIRT and 30 underwent a 4-week MIRT-AT. MEASUREMENTS: The primary outcome measure was the Freezing of Gait Questionnaire; secondary outcome measures were total Unified Parkinson Disease Rating Scale (UPDRS), UPDRS II, UPDRS III, Berg Balance Scale, Timed Up and Go Test, and 6-Minute Walk Test. These measures were assessed both at admission and discharge. RESULTS: Participants in the 2 groups had similar age, sex distribution, Hoehn and Yahr stage, and most-affected side. At baseline, no difference in outcome measures was observed between the 2 groups. After treatment, a significant time effect was observed for all variables in both groups. No significant time × group interaction was observed. A between-group analysis showed nonsignificant differences between values at T1 and values at T0 for all variables. LIMITATIONS: The limitations were the lack of a control group and follow-up. CONCLUSIONS: We showed that a multidisciplinary, intensive, and goal-based rehabilitation treatment, such as MIRT, improves FOG in patients with PD. Although aquatic therapy could be considered a useful approach for treating FOG, it does not add further benefits to this kind of motor-cognitive rehabilitation.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".