Treatment guidelines for rare, early-onset conditions associated with epileptic seizures: a literature review on Rett syndrome and tuberous sclerosis complex
Bibliographic record
Abstract
BACKGROUND: Rett syndrome (RTT) and tuberous sclerosis complex (TSC) are two rare disorders presenting with a range of different epileptic seizures. Seizure management requires careful therapy selection, thereby necessitating development of high-quality treatment guidelines. This targeted literature review (TLR) aimed to characterise country-specific and international treatment guidelines available for pharmacological management of seizures in RTT and TSC. METHODS: A TLR was performed between 25-Jan and 11-Mar 2021. Manual searches of online rare disease and guideline databases, and websites of national heath technology assessment bodies were conducted for the following countries: Australia, Canada, France, Germany, Israel, Italy, Japan, Spain, Switzerland, UK, and US as defined by pre-specified eligibility criteria. Search terms were developed for each condition and translated into local languages where appropriate. Eligible publications were defined as guidelines/guidance reporting pharmacological management of seizures in patients with RTT and TSC. Guideline development methodology, geographical focus, author information and treatment recommendations were extracted from guidelines. An author map was generated using R version 3.5.1 to visualise extent of collaboration between authors. RESULTS: 24 total guidelines were included, of which three and six contained only recommendations for RTT and TSC, respectively (some provided recommendations for ≥ 1 condition). Guideline development processes were poorly described (50% [12 guidelines] had unclear/absent literature review methodologies); reported methodologies were variable, including systematic literature reviews (SLRs)/TLRs and varying levels of expert consultation. Most (83% [20/24]) were country-specific, with guideline authors predominantly publishing in contained national groups; four guidelines were classified as 'International,' linking author groups in the US, UK, Italy and France. High levels of heterogeneity were observed in the availability of treatment recommendations across indications, with 13 and 67 recommendations found for RTT and TSC, respectively. For RTT, all treatment recommendations were positive and sodium valproate had the highest number of positive recommendations (Khwaja, Sahin (2011) Curr Opin Pediatr 23(6):633-9). All TSC treatments (21 medications) received either exclusively negative (National Organization for Rare Disorders (2019)) or positive (Chu-Shore et al. (2010) Epilepsia 51(7):1236-41) recommendations; vigabatrin received the highest number of positive recommendations (Kaur, Christodoulou (2019)). CONCLUSIONS: This review highlights the need for the development of international high-quality and comprehensive consensus-based guidance for the management of seizures with pharmacological therapy in RTT and TSC. TRIAL REGISTRATION: Not applicable.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".