Is physical therapy recommended for people with parkinson’s disease treated with subthalamic deep brain stimulation? a delphi consensus study
Bibliographic record
Abstract
BACKGROUND: Although deep brain stimulation of the subthalamic nucleus (STN-DBS) induces motor benefits in people with Parkinson's disease (PwPD), its effect on motor axial symptoms (e.g., postural instability, trunk posture alterations) and gait impairments (e.g., freezing of gait) is still ambiguous. Physical therapy (PT) effectively complements pharmacological treatment to improve postural stability, gait performance, and other dopamine-resistant symptoms (e.g. freezing of gait) in the general population with PD. Despite the positive potential of combined PT and STN-DBS surgery, scientific results are still lacking. We therefore involved worldwide leading experts on DBS and motor rehabilitation in PwPD in a consensus Delphi panel to define the current level of PT recommendation following STN-DBS surgery. METHODS: After summarizing the few available findings through a systematic scoping review, we identified clinically 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, thirty-nine questions were designed and submitted to the panel-half related to general considerations on PT following STN-DBS, and half related to PT treatments. RESULTS: Despite the low-to-moderate quality of data, the few available rehabilitation studies suggested that PT could improve dynamic and static balance, gait performance and posture in the population with PD receiving STN-DBS. Similarly, the panellists strongly agreed that PT might help improve motor symptoms and quality of life, and it may be prescribed to maximize the effects of stimulation. The experts agreed that physical therapists could be part of the multidisciplinary team taking care of the patients. Also, they agreed that conventional PT, but not massage or manual therapy, should be prescribed because of the specificity of STN-DBS implantation. CONCLUSIONS: Although RCT evidence is lacking, upon Delphi panel, PT for PwPD receiving STN-DBS can be potentially useful to maximize clinical improvement. However, more research is needed, with RCTs and well-designed studies. The rehabilitation and DBS community should expand this area of research to create 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 | 0.151 | 0.170 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".