Miller-Fisher Syndrome in Pregnancy: Case Report and Review of the Literature
Bibliographic record
Abstract
Miller-Fisher Syndrome (MFS) is a variant of Guillain-Barré syndrome (GBS) that can present with ophthalmoplegia, areflexia, and ataxia with positive GQ1b antibodies. While GBS has been reported in pregnancy, the prevalence of MFS is less well known and rarely reported. Here we describe a case of MFS during pregnancy presenting with ophthalmoplegia, ptosis, and anisocoria. GQ1b antibodies were highly positive and cerebrospinal fluid analysis did not show albuminocytologic dissociation. Her symptoms resolved after treatment with steroids and intravenous immunoglobulins. Our literature search identified 7 other patients that were added to our case series (n = 8). All patients had diplopia from ophthalmoplegia. Other common signs include areflexia and ataxia. GQ1b antibodies were positive in 6/7 patients (1 patient had negative GQ1b antibodies but positive asialo-GM1 antibodies). Investigations showed normal neuroimaging in 7/7 patients, albuminocytologic dissociation in 2/8 patients, and demyelination on nerve conduction studies in 3/6 patients. Patient outcomes tend to be favorable despite varying treatments (median symptom resolution = 2 months). MFS is a rare neurological disorder that needs to be considered in pregnant patients with archetypical symptoms and serology should be sent for GQ1b antibodies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".