Practice Parameter: Treatment of nonmotor symptoms of Parkinson disease [RETIRED]
Bibliographic record
Abstract
OBJECTIVE: Nonmotor symptoms (sleep dysfunction, sensory symptoms, autonomic dysfunction, mood disorders, and cognitive abnormalities) in Parkinson disease (PD) are a major cause of morbidity, yet are often underrecognized. This evidence-based practice parameter evaluates treatment options for the nonmotor symptoms of PD. Articles pertaining to cognitive and mood dysfunction in PD, as well as treatment of sialorrhea with botulinum toxin, were previously reviewed as part of American Academy of Neurology practice parameters and were not included here. METHODS: A literature search of MEDLINE, EMBASE, and Science Citation Index was performed to identify clinical trials in patients with nonmotor symptoms of PD published between 1966 and August 2008. Articles were classified according to a 4-tiered level of evidence scheme and recommendations were based on the level of evidence. RESULTS AND RECOMMENDATIONS: Sildenafil citrate (50 mg) may be considered to treat erectile dysfunction in patients with Parkinson disease (PD) (Level C). Macrogol (polyethylene glycol) may be considered to treat constipation in patients with PD (Level C). The use of levodopa/carbidopa probably decreases the frequency of spontaneous nighttime leg movements, and should be considered to treat periodic limb movements of sleep in patients with PD (Level B). There is insufficient evidence to support or refute specific treatments for urinary incontinence, orthostatic hypotension, and anxiety (Level U). Future research should include concerted and interdisciplinary efforts toward finding treatments for nonmotor symptoms of PD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.012 |
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".