The Impact of <scp>COVID</scp>‐19 on Access to Parkinson's Disease Medication
Bibliographic record
Abstract
BACKGROUND: Many countries have implemented drastic measures to fight the COVID-19 pandemic. Restrictions and diversion of resources may have negatively affected patients with Parkinson's disease (PD). Our aim was to examine whether COVID-19 had an impact on access to PD medication by region and income. METHODS: This study was conducted as part of a survey sent to members of the Movement Disorders Society focusing on access to PD medication globally. RESULTS: Of 346 responses, 157 (45.4%) agreed that COVID-19 had affected access to PD medication, while 189 (54.6%) disagreed. 22.8% of high-income and 88.9% of low-income countries' respondents agreed that access to PD medication was affected by COVID-19. 59% of all 'yes' respondents reported increased disability of patients as an impact. CONCLUSIONS: Access to PD medication is likely to have been affected by COVID-19 and result in deterioration of patients' symptomatic control. Resource-poor countries appear to be disproportionately affected compared to more affluent countries. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.013 |
| 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 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".