Hemiconvulsion‐Hemiplegia‐Epilepsy in a girl with cobalamin C deficiency
Bibliographic record
Abstract
Hemiconvulsion-Hemiplegia-Epilepsy initially involves an infantile presentation of febrile focal motor status epilepticus, with subsequent hemiplegia of the initially affected side. Months to years later, affected children go on to develop a chronic epilepsy with recurrent focal seizures which are often refractory to treatment. This uncommon paediatric epilepsy syndrome is poorly understood, with only a very small minority of cases associated with an underlying genetic or metabolic abnormality. We present a four-year-old girl with genetic cobalamin C deficiency who had a dramatic presentation with Hemiconvulsion-Hemiplegia-Epilepsy. She had febrile focal status epilepticus, with right hemiconvulsive seizures for nearly 10 hours, ultimately requiring a midazolam infusion. Over subsequent days, she developed progressively worsening cerebral oedema, leading to herniation and requiring a craniectomy to relieve pressure. This girl's presentation is the first association of cobalamin deficiency with hemiconvulsion-hemiplegia-epilepsy; and illustrates the importance of considering this entity when patients with this metabolic disorder present with acute deterioration. More importantly, the case also raises the possibility that derangements of cobalamin metabolism could be a contributing factor in cases of hemiconvulsion-hemiplegia-epilepsy, as well as febrile seizures in general.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".