The Trajectory of Motor Deterioration to Death in Parkinson's Disease
Bibliographic record
Abstract
Background: Motor progression varies even among those with a single diagnosis such as Parkinson's disease (PD) and little is known about the trajectory of motor signs prior to death. Understanding deterioration patterns may help clinicians counsel patients and proactively plan interdisciplinary care, including palliative care. The objective of this study was to examine and describe Unified Parkinson's Disease Rating Scale motor score (UPDRS-III) trajectories at the end of life in PD. Methods: A retrospective chart review was performed for deceased PD patients who attended the Parkinson and Movement Disorders Program at the University of Alberta for at least 5 years between 1999 and 2018. UPDRS-III scores were recorded for all visits. Trajectory patterns were visualized with Loess curves stratified by sex and age at diagnosis. Piecewise linear models were used to individually model the UPDRS-III scores, and the trajectories obtained were clustered based on their features. Results: Among the 202 charts reviewed, 84 meeting inclusion criteria were analyzed. The UPDRS-III increased over time regardless of sex and age. Distinct trajectory variations present in PD (e.g., Consistent Deterioration, Stability-Deterioration, Improvement-Deterioration, Deterioration-Improvement-Deterioration) were identified. Twenty-five percent of the patients were classified as Undetermined/Irregular trajectories. In addition, regardless of trajectory type, many patients experienced a steep increase in UPDRS-III approaching death. Those with disease diagnosis after age 65 years had a shorter survival time, compared to PD patients with a younger age of onset. Conclusion: Our study identified dominant types of motor trajectory in PD that can help clinicians understand their patients' course of illness. This information can help counsel patients regarding the variability in motor deterioration and should alert physicians to recognize a terminal decline. Age of disease onset was correlated with survival time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".