Surveying Global Availability of Parkinson’s Disease Treatment
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is a debilitating neurodegenerative disease with both motor and non-motor manifestations. Available treatment reduces symptoms and is critical for improving quality of life. Treatment options include drugs, device-aided therapies, and non-pharmacological therapies. Complementary and alternative therapies (CATs) are also used in some countries. OBJECTIVE: To examine the availability of PD treatment by country, and differences by national income as defined by the World Bank (high income countries (HICs), upper middle income countries (UMICs), lower middle income countries (LMICs) and low income countries (LICs)). METHODS: This study was conducted by surveying International Parkinson and Movement Disorders Society members about availability of PD treatment. LMICs and LICs (LMICs/LICs) were analysed together. RESULTS: There were 352 valid responses from 76 countries (41.5% from HICs, 30.4% from UMICs, and 28.1% from LMICs/LICs). Levodopa was widely available across all income groups (99%). Availability of other PD drugs decreased with national income. Availability of device-aided therapies decreased with national income (100% availability in HICs, 92.5% among UMICs, and 57.6% among LMICs/LICs). A similar trend was observed for CATs (37.0% availability in HICs, 31.8% in UMICs, and 19.2% in LMIC/LICs). Physiotherapy was the most available non-pharmacological therapy (> 90% respondents). Occupational therapy and SALT were less available in LMIC/LICs (49.5% and 55.6% respectively) compared to HICs (80.1% and 84.9% respectively). CONCLUSION: Our survey highlights significant discrepancies in availability of PD treatments between countries and income groups. This is concerning given the symptomatic benefit patients gain from treatment. Improving equitable access to PD treatment should be prioritised.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".