The scientific and clinical basis for the treatment of Parkinson disease (2009)
Bibliographic record
Abstract
Parkinson disease (PD) is an age-related neurodegenerative disorder that affects as many as 1-2% of persons aged 60 years and older. With the aging of the population, the frequency of PD is expected to increase dramatically in the coming decades. Current therapy is largely based on a dopamine replacement strategy, primarily using the dopamine precursor levodopa. However, chronic treatment is associated with the development of motor complications, and the disease is inexorably progressive. Further, advancing disease is associated with the emergence of features such as freezing, falling, and dementia which are not adequately controlled with dopaminergic therapies. Indeed, it is now appreciated that these nondopaminergic features are common and the major source of disability for patients with advanced disease. Many different therapeutic agents and treatment strategies have been evaluated over the past several years to try and address these unmet medical needs, and many promising approaches are currently being tested in the laboratory and in the clinic. As a result, there are now many new therapies and strategic approaches available for the treatment of the different stages of PD, with which the treating physician must be familiar in order to provide patients with optimal care. This monograph provides an overview of the management of PD patients, with an emphasis on pathophysiology, and the results of recent clinical trials. It is intended to provide physicians with an understanding of the different treatment options that are available for managing the different stages of the disease and the scientific rationale of the different approaches.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".