Experience and Impact of OFF Periods in Parkinson’s Disease: A Survey of Physicians, Patients, and Carepartners
Bibliographic record
Abstract
BACKGROUND: OFF periods impair quality of life in Parkinson's disease but the nature and degree of this impact is largely unquantified. Optimal treatment relies on assessing the experience and impact of these periods on patients and their carepartners. OBJECTIVES: To understand the experience and impact of OFF periods on their lives. METHODS: Informed by qualitative interviews we designed questionnaires and surveyed neurologists, people with Parkinson's disease and carepartners. RESULTS: 50 general neurologists, 50 movement disorder neurologists, 442 patients (median disease duration 5 years) and 97 carepartners were included. The most common OFF symptoms reported by patients and carepartners were stiffness, slowness of movement and changes in gait. Non-motor symptoms were less common. A higher proportion of carepartners reported each symptom. A minority of neurologists recognized pain, sweating and anxiety as possible symptoms of OFF periods. The three OFF symptoms most frequently designated as having great impact by people with Parkinson's disease were changes in gait, slowness and stiffness. In contrast, cognitive impairment was most frequently rated as having great impact on carepartners. OFF periods were reported to impact many aspects of the lives of both patients and carepartners. CONCLUSIONS: In people with Parkinson's disease of under 10 years duration, motor symptoms of OFF periods predominate in impact, however cognitive impairment has great impact on carepartners. Education is needed for neurologists regarding the non-motor aspects of OFF. The importance of involving carepartners in the assessment regarding OFF periods is supported by the higher frequency of symptom reporting by carepartners, and the significant impact on their lives.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".