Updated clinical recommendations for the management of tuberous sclerosis complex associated epilepsy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Children with tuberous sclerosis complex (TSC), may experience a variety of seizure types in the first year of life, most often focal seizure sand epileptic spasms. Drug resistance is seen early in many patients, and the management of TSC associated epilepsy remain a major challenge for clinicians. In 2018 clinical recommendations for the management of TSC associated epilepsy were published by a panel of European experts. In the last five years considerable progress has been made in understanding the neurobiology of epileptogenesis and three interventional randomized controlled trials have changed the therapeutic approach for the management of TSC associated epilepsy. Pre-symptomatic treatment with vigabatrin may delay seizure onset, may reduce seizure severity and reduce the risk of epileptic encephalopathy. The efficacy of mTOR inhibition with adjunctive everolimus was documented in patients with TSC associated refractory seizures and cannabidiol could be another therapeutic option. Epilepsy surgery has significantly improved seizure outcome in selected patients and should be considered early in all patients with drug resistant epilepsy. There is a need to identify patients who may have a higher risk of developing epilepsy and autism spectrum disorder (ASD). In the recent years significant progress has been made owing to the early identification of risk factors for the development of drug-resistant epilepsy. Better understanding of the mechanism underlying epileptogenesis may improve the management for TSC-related epilepsy. Developmental neurobiology and neuropathology give opportunities for the implementation of concepts related to clinical findings, and an early genetic diagnosis and use of EEG and MRI biomarkers may improve the development of pre-symptomatic and disease-modifying strategies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it