Six Action Steps to Address Global Disparities in Parkinson Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Importance: The Global Burden of Disease study conducted between 1990 and 2016, based on a global study of 195 countries and territories, identified Parkinson disease (PD) as the fastest growing neurological disorder when measured using death and disability. Most people affected by PD live in low- and middle-income countries (LMICs) and experience large inequalities in access to neurological care and essential medicines. This Special Communication describes 6 actions steps that are urgently needed to address global disparities in PD. Observations: The adoption by the 73rd World Health Assembly (WHA) of resolution 73.10 to develop an intersectoral global action plan on epilepsy and other neurological disorders in consultation with member states was the stimulus to coordinate efforts and leverage momentum to advance the agenda of neurological conditions, such as PD. In April 2021, the Brain Health Unit at the World Health Organization convened a multidisciplinary, sex-balanced, international consultation workshop, which identified 6 workable avenues for action within the domains of disease burden; advocacy and awareness; prevention and risk reduction; diagnosis, treatment, and care; caregiver support; and research. Conclusions and Relevance: The dramatic increase of PD cases in many world regions and the potential costs of PD-associated treatment will need to be addressed to prevent possible health service strain. Across the board, governments, multilateral agencies, donors, public health organizations, and health care professionals constitute potential stakeholders who are urged to make this a priority.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it