Initial combination versus early sequential standard therapies for Infantile Epileptic Spasms Syndrome—Feedback from stakeholders
Bibliographic record
Abstract
We read with great interest the report by Sourbron et al. 1 entitled "Medical Treatment in Infants and Young Children with Epilepsy: Off-label Use of Antiseizure Medications.Survey Report of ILAE Task Force Medical Therapies in Children".We want to congratulate the authors on this timely article that explores the occurrence of off-label anti-seizure medicine use.It analyzes the prescription behavior of over 500 neurologists worldwide in six different epilepsy syndromes, including Infantile Epileptic Spasms Syndrome (IESS).In this letter, we aim to focus on recommendations concerning the management of infants with IESS.Specifically, we want to address the authors' recommendation that a standard of care should involve combination therapy (hormonal therapy combined with vigabatrin) at the onset of treatment.This recommendation primarily relies on the short-term clinical remission of epileptic spasms (ES) observed between day 14 and day 42 of treatment, as noted in the prospective randomized controlled International Collaborative Infantile Spasms Study (ICISS).This trial compared combination therapy versus hormonal therapy alone for new-onset IESS. 2 We argue that, for IESS, early sequential therapy -initiating treatment with standard monotherapy (prioritizing hormonal therapy) and adding another standard therapy (such as vigabatrin) if no electroclinical remission by 14 days-is a reasonable alternative to combination therapy.This approach is supported by the available evidence and may be preferable in specific contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.057 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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".