P.059 Management of motor symptoms for patients with advanced Parkinson’s disease without safe oral access: a scoping review
Bibliographic record
Abstract
Background: Parkinson’s disease (PD) is the second most common neurodegenerative disorder worldwide. Oral medications for control of motor symptoms are the mainstay of treatment however, as the disease progresses, patients with PD may develop dysphagia or other medical illnesses that prohibit them from safely taking oral medications. Currently there are no clinical guidelines for managing distressing motor symptoms in patients with PD and severe dysphagia, which can therefore be quite challenging. Methods: A scoping review using MEDLINE, EMBASE, CENTRAL, CINAHL, AgeLine and Psyc INFO databases (1946-2021) was conducted. Articles examining PD with dysphagia in palliative care or at end-of-life were included. Studies that included patients who were also on oral PD medications or received device-aided therapy were excluded. Results: Of 3836 articles screened for title and abstract, 274 were selected for full text review, and 20 articles were finally selected for data extraction. These included five case reports, one retrospective cohort study, one book chapter and 13 narrative reviews. Conclusions: There are very few articles addressing the issue of treatment of patients with advanced PD who are unable to take oral medications. Although rotigotine patch and apormorphine injections are most frequently recommended, there are no clinical trials in this patient population to support those recommendations.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".