Acute Central Nervous System Demyelination Following COVID-19 Vaccination
Bibliographic record
Abstract
Objective To describe features of central nervous system (CNS) demyelinating events following vaccination against coronavirus disease 19 (COVID-19). Background Several reports suggest a potential association between COVID-19 vaccines and acute CNS inflammation. Design/Methods A case series was performed at the BARLO MS Centre in Toronto, Ontario, Canada. Clinicians reported patients who experienced an acute CNS demyelinating event within 60 days after receiving at least one COVID-19 vaccination from March 2021 to January 2022. Clinical characteristics were evaluated. Results Twenty patients were identified (median age 39 years (range 25-82); 13 (65.0%) female). Two had pre-existing multiple sclerosis (MS). Individuals received the Pfizer (n = 14), Moderna (n = 5) or Astrazeneca (n = 1) COVID-19 vaccines. Within 1-53 days (median 12) of the first (n = 8) or second (n = 12) vaccine dose, patients developed transverse myelitis (TM) (n = 15), optic neuritis (n = 4) or brain demyelination (n = 4). Diagnoses at last follow up (median 114 days (range 39-255)) were relapsing remitting MS (n = 8), post-vaccine TM (n = 5), clinically isolated syndrome (n = 3), myelin oligodendrocyte glycoprotein antibody disease (n = 2), MS relapse (n = 1) and neuromyelitis optica spectrum disorder (n = 1). Thirteen patients received pulse corticosteroids, and of these, 4 received plasma exchange. Seven did not receive acute treatment. 20.0% returned to baseline (n = 4), 75.0% partially recovered (n = 15) and 5.0% worsened (n = 1). At last follow up, 11 were on disease modifying therapy and 9 were not. Nine patients received a subsequent COVID-19 vaccine. Of these, one experienced symptom recrudescence without radiologic evidence of a new demyelinating attack. Conclusions To our knowledge, this is the largest series to date describing acute CNS demyelination after vaccination against COVID-19. The rate of vaccination in the eligible general population was high during the time of the cases and we could not determine whether the number of demyelinating events was higher than expected. Repeat vaccination was not associated with recurrent adverse events in this small observational series.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".