Gelastic seizures associated with hypothalamic hamartomas. An update in the clinical presentation, diagnosis and treatment
Bibliographic record
Abstract
Gelastic seizures are epileptic events characterized by bouts of laughter. Laughter-like vocalization is usually combined with facial contraction in the form of a smile. Autonomic features such as flushing, tachycardia, and altered respiration are widely recognized. Conscious state may not be impaired, although this is often difficult to asses particularly in young children. Gelastic seizures have been associated classically to hypothalamic hamartomas, although different extrahypothalamic localizations have been described. Hypothalamic hamartomas are rare congenital lesions presenting with the classic triad of gelastic epilepsy, precocious puberty and developmental delay. The clinical course of patients with gelastic seizures associated with hypothalamic hamartomas is progressive, commencing with gelastic seizures in infancy, deteriorating into more complex seizure disorder resulting in intractable epilepsy. Electrophysiological, radiological, and pathophysiological studies have confirmed the intrinsic epileptogenicity of the hypothalamic hamartoma. Currently the most effective surgical approach is the trancallosal anterior interforniceal approach, however newer approaches including the endoscopic and other treatment such as radiosurgery and gamma knife have been used with success. This review focuses on the syndrome of gelastic seizures associated with hypothalamic hamartomas, but it also reviews other concepts such as status gelasticus and some aspects of gelastic seizures in other locations.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".