Analyzing the effects of PDSAFEx™ on the motor symptoms of Parkinson’s disease: A retrospective study
Bibliographic record
Abstract
BACKGROUND: The cardinal motor symptoms of Parkinson's disease (PD) include postural instability, bradykinesia, tremor and rigidity. The overall Unified Parkinson's Disease Rating Scale (UPDRS-III) indicates, the gold-standard treatment for PD (dopaminergic-therapy) is very effective in improving these symptoms. However, recent research indicated that 2 of the 4 cardinal symptoms of PD (balance and tremor) remain unimproved by dopaminergic-therapy. This prompts the investigation of other alternative and adjunct treatments such as exercise rehabilitation. Unfortunately, like drug studies, exercise studies often focus on overall symptom improvement yet fail to monitor changes to specific symptoms. This may be problematic for individuals with different symptomatic phenotypes. If tremor/balance were the main concern, then adjunct therapies may be critically important when these symptoms may be dopa-resistant. Thus, it is important for all therapies to examine individual symptomatic-improvement. Interestingly, recent studies show PDSAFEx™ (a sensory integration therapy) to have a significantly improve motor symptoms in comparison to traditional exercise (14). Yet, the effects of PDSAFEx™ on individual PD symptoms is unknown. OBJECTIVE: To explore the effects of PDSAFEx™ on PD symptoms in adjunct to medications. METHODS: UPDRS-III scores of 229 cases were retrospectively examined and analysed in SPSS using Wilcoxon pairs singed-rank test to evaluate specific symptom-improvements. RESULTS: PDSAFEx™ was confirmed to improve overall motor symptoms (p = 0.0001), but more importantly a significant improvement to tremor (p < 0.00001) and balance (p < 0.00001) were also identified. CONCLUSIONS: These findings suggest that PDSAFEx™ is an important adjunct to medications, since it is able to address all four cardinal symptoms of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".