Focused ultrasound and deep brain stimulation for Parkinsonism – Review of literature to investigate tradeoff between safety and efficacy
Bibliographic record
Abstract
Parkinsonism is a movement disorder, mostly caused by the neurodegenerative Parkinson's disease (PD), the second most common movement disorder. Its symptoms include rigidity, slow movement, tremor, and disruption of balance. First treatment line is dopamine replacement drugs, and surgery is due when medication fails. Surgery options include deep brain stimulation (DBS), which revolves around implanting impulse generator in the target structure, and magnetic resonance-guided focused ultrasound (MRgFUS), where transcranial sonication ablates certain structures to counter the excitotoxic circuitopathy. This review aims to compare results described in peer-reviewed publications describing DBS and MRgFUS in Parkinsonism in terms of improvement in symptoms and side effects. This study was carried out by searching prominent computerized biomedical databases (PubMed, Web of Science, Cochrane, and EMBASE) to assess and compare the safety and efficacy of MRgFUS and DBS procedures done for the treatment of PD. Most of the published results for each of the two operations are comparable, in tremor and Unified Parkinson's Disease Rating Scale scores, though minimal superiority is shown in the DBS results. The neurological adverse effects are similar between the two types, including mild-to-moderate transient instances of dysarthria and gait disturbances, which are the most common two adverse events, among others. However, DBS has a more severe or significant adverse event profile that includes hemorrhage and infection. Long-term improvement is observed more with DBS which can sustain improvement for up to 5 years. DBS, therefore, tends to better improve Parkinsonism prognosis at the cost of safety. Postoperative complications are less severe in MRgFUS, which can be a safe, efficient alternative procedure for medication-refractory Parkinsonism.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".