COVID-19 Vaccination for Persons with Parkinson’s Disease: Light at the End of the Tunnel?
Bibliographic record
Abstract
Several COVID-19 vaccines have recently been approved for emergency use according to governmental immunization programs. The arrival of these vaccines has created hope for people with Parkinson's disease (PD), as this can help to mitigate their risk of becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which can lead to serious, life-threatening disease, at least among those with more advanced PD. However, both persons with PD and physicians looking after these individuals have expressed concerns about the vaccine's efficacy and safety in the specific context of PD and its symptomatic treatment. Here, we discuss our perspective on these concerns, based on our interpretation of the literature plus the unfolding experience with widespread vaccination in the population at large. Because the benefits and risks of COVID-19 vaccines do not appear to be different than in the general population, we recommend COVID-19 vaccination with approved vaccines to persons with PD, unless there is a specific contraindication. Some caution seems warranted in very frail and terminally ill elderly persons with PD living in long-term care facilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".