Optimal management of seizures associated with tuberous sclerosis complex: current and emerging options
Bibliographic record
Abstract
Seizures are clinically significant manifestations associated with 79%-90% of patients with tuberous sclerosis complex. Often occurring within the first year of life in the form of infantile spasms, seizures interfere with neuropsychiatric, social, and cognitive development and carry significant individual and societal consequences. Prompt identification and treatment of seizures is an important focus in the overall management of tuberous sclerosis complex patients. Medical management, either after seizure onset or prophylactically in infants with electroencephalographic abnormalities, is considered first-line therapy. Vigabatrin and adrenocorticotropic hormone have emerged over the past few decades as mainstay pharmacologic modalities. Furthermore, emerging research on mammalian target of rapamycin inhibitors demonstrated promise for the management of seizures and subependymal giant cell astrocytoma. For appropriate surgical candidates with an epileptogenic zone associated with one or more glioneuronal hamartomas, ideally in noneloquent cortex, resective surgery can be considered, which provides a cure in 56% of patients. For medically refractory patients who do not meet criteria for curative surgery, palliative surgical approaches focused on reducing seizure burden, in the form of corpus callosotomy and vagus nerve stimulation, are alternative management options. Lastly, the ketogenic diet, a reemerging therapy based on the anticonvulsant effects of ketone bodies, can be utilized independently or in conjunction with other treatment modalities for the management of difficult-to-treat seizures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".