Researching COVID-19 in progressive MS requires a globally coordinated, multi-disciplinary and multi-stakeholder approach—perspectives from the International Progressive MS Alliance
Bibliographic record
Abstract
Background: The COVID-19 pandemic has reinforced the importance of research for the health of our society and highlighted the need for stakeholders of the health research and care continuum to form a collaborative and interdependent ecosystem. Objective: With the world still reeling from waves of the COVID-19 pandemic and adapting to the vaccine rollout at widely different rates, the International Progressive MS Alliance (hereafter Alliance) organized a meeting (April 2021) to consider how the Covid-19 pandemic impacts the health and well-being of people with progressive Multiple Sclerosis (MS). Methods: We invited the Alliance stakeholders and experts to present what they have learned about SARS-CoV-2 infection and progressive MS and to define future scientific priorities. Results: The meeting highlighted three priorities for additional focus: (1) the impact of Disease Modifying Therapies (DMTs) on the risk of COVID-19 and on the efficacy of COVID-19 vaccines in people with progressive MS; (2) the long-term impact of COVID-19 and COVID-19 vaccines on the biology of progressive MS; and (3) the impact on well-being of people with progressive MS. Conclusion: This paper's calls to action could represent a path toward a shared research agenda. Multi-stakeholder and long-term investigations will be required to drive and evolve such an agenda.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".