P.052 SYNGAP-1 developmental and epileptic encephalopathy: utility of corpus callosotomy and neuromodulation
Bibliographic record
Abstract
Background: Pathogenic variants in SYNGAP1causedevelopmental and epileptic encephalopathy (DEE) and intellectual disability. Seizures are medically refractory and there is limited evidence on the use of corpus callosotomy (CC) and vagal nerve stimulation (VNS). Methods: A retrospective study was completed examining the effectiveness of VNS and CC in children with SYNGAP1-DEE using the SynGAP Research Database and an additional child followed at our centre. Results: Fifteen patients from the SynGAP Database were included. Of those who had VNS (n=11), 7 children had an >50% reduction in seizure frequency (n=7/11, 64%), 2 had worsening (n=2/11, 18%), 1 had no change (n=1/11, 9%), and 1 had an unknown response (n=1/11, 9%). Two children had CC only, 1 had complete seizure freedom, and 1 had a >50% reduction. Two children underwent VNS and CC, 1 had a >50% reduction in seizure frequency and the other had no change. One child followed at our centre experienced a sustained >80% reduction in seizure frequency following CC (i.e., after 1.5 years). Conclusions: We provide the first in-depth description of the response to VNS and CC in children with SYNGAP1-DEE, and provide insight into the use of of palliative surgical procedures in this population.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 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".