Physical therapy in patients with Parkinson’s disease treated with Deep Brain Stimulation: a Delphi panel study
Bibliographic record
Abstract
Although deep brain stimulation of the subthalamic nucleus (STN-DBS) induces motor benefits in people with Parkinson's disease (PwPD), the size and duration of the effects of STN-DBS on motor axial (e.g., postural instability, trunk posture alterations) and gait impairments (e.g., freezing of gait - FOG) are still ambiguous. Physical therapy (PT) effectively complements pharmacological treatment to improve postural stability, gait performance, and other dopamine-resistant symptoms (e.g. festination, hesitation, axial motor dysfunctions, and FOG) in PwPD who are non-surgically treated. Despite the potential for positive adjuvant effects of PT following STN-DBS surgery, there is a paucity of science available on the topic. In such a scenario, gathering the opinion and expertise of leading investigators worldwide was pursued to study motor rehabilitation in PwPD following STN-DBS. After summarizing the few available findings through a systematic review, we identified clinical and academically experienced DBS clinicians (n=21) to discuss the challenges related to PT following STN-DBS. A 5-point Likert scale questionnaire was used and based on the results of the systematic review along with a Delphi method. Thirty-nine questions were submitted to the panel - half related to general considerations on PT following STN-DBS, half related to PT treatments. Despite the low-to-moderate quality, the few available rehabilitative studies suggested that PT could improve dynamic and static balance, gait performance and posture. Similarly, panellists strongly agreed that PT might help in improving motor symptoms and quality of life, and it may be possibly prescribed to maximize the effects of the stimulation. The experts agreed that physical therapists could be part of the multidisciplinary team taking care of the patients. Also, they agreed on prescribing of conventional PT, but not massage or manual therapy. Our results will inform the rehabilitation and the DBS community to engage, publish and deepen this area of research. Such efforts may spark guidelines for PT following STN-DBS.
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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 | 0.034 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".