The role and structure of the multidisciplinary team in the management of advanced Parkinson’s disease with a focus on the use of levodopa–carbidopa intestinal gel
Bibliographic record
Abstract
Stephen W Pedersen,1 Martin Suedmeyer,2 Louis W C Liu,3 Dirk Domagk,4 Alison Forbes,5 Lars Bergmann,6 Koray Onuk,6 Ashley Yegin,6 Teus van Laar7 1Department of Neurology, Glostrup Hospital, University of Copenhagen, Glostrup, Copenhagen, Denmark; 2Department of Neurology, University of Düesseldorf, Düesseldorf, Germany; 3Division of Gastroenterology, Department of Medicine, University of Toronto, University Health Network, Toronto, ON, Canada; 4Department of Medicine I, Josephs-Hospital Warendorf, Academic Teaching Hospital, University of Muenster, Warendorf, Germany; 5PDNS consultant, AbbVie Inc., Roswell, GA, USA; 6Global Medical Affairs, AbbVie Inc., North Chicago, IL, USA; 7Department of Neurology, University Medical Center Groningen, Groningen, The Netherlands Abstract: A multidisciplinary team (MDT) approach is increasingly recommended in Parkinson’s disease (PD) treatment guidelines, but no standard of care exists for such an approach, and the guidelines do not provide clarification on how it should be implemented. This paper reviews evidence of MDT interventions in people with PD and provides expert clinical perspectives for an MDT approach, with a focus on advanced PD and levodopa–carbidopa intestinal gel (carbidopa–levodopa enteral suspension in the USA). The key recommendations are to enable the best possible treatment of people with PD locally by facilitating a close structured collaboration of different health care professionals working in a fixed network structure; to refer people with PD to established MDT centers in a timely manner; to establish regular meetings for the MDT enabling interdisciplinary exchange and learning; to optimize individual treatment and carefully evaluate available treatment options; to ensure treatment decisions are agreed jointly between people with PD, their caregivers, family, and health care professional; and to include specialists outside of neurology from adjuvant medical departments as necessary when implementing advanced therapies. Keywords: Parkinson’s disease, multidisciplinary team, advanced therapy, levodopa–carbidopa intestinal gel, carbidopa–levodopa enteral suspension
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".