Effect of simplified Tai Chi exercise on relieving symptoms of patients with mild to moderate Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: Tai Chi, a kind of physical exercise, may act as a non-pharmacologic approach to reducing the symptoms of Parkinson's disease. This study was conducted to investigate the effect of simplified Tai Chi training plus routine exercise on motor and non-motor symptoms in patients with mild to moderate Parkinson's disease in comparison with routine exercise regimen alone. METHODS: Forty-one outpatients and inpatients with Parkinson's disease (PD) were randomized into Tai Chi group (N.=19) and routine exercise group as control group (N.=22) for 12 weeks. The Tai Chi group included both Tai Chi traning and routine exercise. Motor and non-motor functions were assessed. Motor function was evaluated by Unified Parkinson's Disease Rating Scale part III (UPDRS-III) and Berg Balance Scale (BBS). The non-motor symptoms like quality of life, sleep quality, depression and anxiety state, cognitive function were assessed by Parkinson's Disease Questionnaire-39 (PDQ-39), Parkinson's Disease Sleep Scale (PDSS), Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), Montreal Cognitive Assessment (MOCA) respectively. RESULTS: After 12 weeks of intervention, participants in both Tai Chi and routine exercise groups gained effects in UPDRS-III, BBS, PDQ-39, PDSS and HAMD compared to the baseline. However, significant improvements between Tai Chi group and routine exercise group were only found in PDSS (P=0.029) and MoCA (P=0.024). CONCLUSIONS: Tai Chi training plus routine exercise might therefore be an ideal alternative non-pharmacological approach for the motor and non-motor symptoms of PD patients, and especially be more useful for the improvement of sleep quality and cognitive function in Parkinson's disease compared with routine exercise regimen alone.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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".