Levodopa-carbidopa related severe mixed dyskinesia in a patient with advanced Parkinson’s disease admitted to the intensive care unit
Bibliographic record
Abstract
Parkinson's disease (PD) is characterised by motor complications that can become difficult to manage with disease progression. Certain medications used to treat PD, such as levodopa-carbidopa, can also cause motor complications. The timing and type of motor complication occurrence can provide important clues in determining the cause and help with treatment optimisation.This case report highlights the management of severe mixed dyskinesia in a critically ill PD patient admitted to the intensive care unit (ICU). The patient experienced debilitating motor complications, requiring intensive monitoring and personalised levodopa-carbidopa dose adjustments. Following the optimisation of her regimen, which included increasing the frequency of lower doses and the addition of another agent, her motor complications improved. This report underscores the need for individualised treatment strategies in advanced PD and the benefit of ICU-level close monitoring to optimise PD therapy in patients with severe dyskinesias.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".