MICTURITION-INDUCED REFLEX EPILEPSY: A PEDIATRIC CASE AND REVIEW OF THE LITERATURE
Bibliographic record
Abstract
Objectives: Reflex seizures are epileptic events triggered by specific stimuli. They may occur individually, or as part of a focal or generalized epilepsy syndrome. Flashing lights are common triggers, however thinking, reading, bathing and somatosensory phenomena may also induce seizures. Micturition as a trigger is rare, and the localization for this reflex epilepsy has not been reported. Methods: We present a pediatric case of partial complex seizures provoked by micturition and review the available literature. Results: A 12 year-old left-hand dominant girl with moderate developmental delay of unknown etiology and refractory epilepsy since age two developed partial complex seizures with micturition at age ten. Electroencephalography (EEG) of micturition-induced seizures disclosed initial low-voltage fast activity at Cz with spread to the bifrontal regions. Magnetic resonance imaging was normal. Comparison of ictal and interictal single photon emission computed tomography (SPECT) images showed ictal hyperperfusion in the right anterolateral frontal lobe as well as the cingulate region. Video and EEG recordings confirmed that micturition preceded and precipitated seizures, thus ruling out more common phenomena such as micturition syncope and loss of bladder control due to seizure. Conclusion: Micturition is a complex event coordinated by multiple levels of the central and peripheral nervous systems. Reflex seizures induced by micturition are exceedingly rare, with only three available cases in the literature. We report a patient with probable deep midline onset and rapid spread to the right anterolateral frontal lobe, and suggest involvement of the right frontal lobe as a possible common localization. This finding is in keeping with experimental positron emission photometry (PET) data showing similar active areas during urination in normal subjects.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".