Vaccine-Induced Functional Neurological Disorders in the Covid-19 Era
Bibliographic record
Abstract
The large amount of information available to the public regarding vaccines against Covid-19 coupled with pandemic stress and increased somatic attention could potentially precipitate development of functional neurological disorders (FNDs) following vaccination. A growing number of reports indicate that functional symptoms may follow Covid-19 vaccination, similar to those observed with other vaccines previously. We review previously reported cases of FND following vaccination against Covid-19 and present three additional cases. While two patients presented to the Emergency Department with functional movement disorders, one patient presented with protracted limb weakness and sensory dysfunction. The superficial resemblance to Guillain-Barré syndrome, a known but uncommon complication of vaccination prompted an extensive workup. Clinicians need to convey the diagnosis of FND in clear and unequivocal terms to facilitate institution of appropriate therapy and rehabilitation, but importantly also to dispel any doubts in the minds of the public regarding the safety of the available vaccines. Given the presence of significant vaccine hesitancy in many countries, this is critical to the success of the global immunisation effort.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".