Intraneural ganglion cyst of the peroneal nerve occurring after coronavirus disease-19 vaccination: A case report
Bibliographic record
Abstract
Ganglion cysts are relatively common, but intraneural ganglion cysts (INGCs) within peripheral nerves are rare and poorly understood. We present the case of a 58-year-old woman who presented with acute right-foot drop. She experienced acute knee pain radiating from the lateral leg to the dorsal foot two days after the first coronavirus disease-19 (COVID-19) vaccination (BNT162b2, Pfizer-BioNTech). She had no history of trauma or medication use. Two weeks after the onset of symptoms, she developed a dorsiflexor weakness of the right foot (Medical Research Council grade, poor). The weakness worsened to a "trace" grade despite providing conservative management for one month. Ultrasonography revealed a fusiform echolucent structure within the course of the right common peroneal nerve around the fibular head. Magnetic resonance imaging revealed multiple intraneural cysts within the right common peroneal nerve. Nerve conduction and electromyographic studies revealed multiphasic motor unit action potentials accompanied by abnormal spontaneous activities in the innervated muscles, along with axonal degeneration of the deep peroneal nerves. Surgical removal of the cyst was performed, and the patient's symptoms gradually improved. Pathological examination revealed a cystic structure containing mucinous or gelatinous fluid and lined with flattened or cuboidal cells. The clinical course and sequential electromyographic findings relevant to this symptomatic cyst were temporally related to the vaccination date. The present case suggests that INGC-induced peroneal palsy is a possible complication after COVID-19 vaccination.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| 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".