Update in therapeutic strategies for Parkinson's disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review recent advances in therapeutics for motor and nonmotor symptoms of Parkinson's disease. RECENT FINDINGS: Neuroprotection remains a large area of investigation with preliminary safety data on alpha synuclein immunotherapy and glucagon-like peptide-1 agonists. Novel Monoamine Oxidase B and Caetchol-O-methyltransferase-inhibitors for motor fluctuations have shown benefit and are recently approved for clinical use. Long-acting amantadine has also been approved to reduce dyskinesia. Alternative delivery strategies (sublingual, inhaled) dopaminergics may prove useful for rapid reversal of Parkinson's disease motor symptoms. Advanced therapies (surgery and infusional therapies) continue to be useful in subgroups of patients for motor complications with improved safety and also benefit on some nonmotor symptoms, including neuropsychiatric issues. Specific therapeutics for cognition, swallowing, sleep, and mood disorders had moderate to limited benefits. Exercise-based therapy appears beneficial at all stages of Parkinson's disease. SUMMARY: The motor symptoms of Parkinson's disease can be reasonably treated and managed. However, therapies to slow or prevent disease progression remain a focus of research. Despite increased studies, treating nonmotor symptoms remains a challenge and an ongoing priority.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".