P.099 Generator replacement with cardiac based VNS device in children with drug-resistant epilepsy
Bibliographic record
Abstract
Background: We aimed to study the proportion of patients with DRE and pre-existing VNS device, who show improvement of at least one class in McHugh seizure outcome classification at last follow up after generator replacement with cardiac based VNS device. Methods: We retrospectively reviewed children with DRE with the older VNS model (102) who underwent battery replacement with the AspireSR®, model 106 since September 2016 at our institution. We assessed the seizure outcomes since the first VNS device insertion till the last follow up after AspireSR® (with cardiac-based seizure detection) using McHugh seizure outcome classification. Results: The study population was comprised of 15 patients. The mean age at seizure onset was 2.7 years old, with mean age of initial VNS1 placement being 10.1 years and mean age of replacement with VNS2 being 14.9 years of age. Three of the fifteen patients had reported status epilepticus prior to initial VNS insertion, and none reported episodes following insertion. Two patients showed at least one class improvement in McHugh seizure outcomes at last follow up after VNS2. Conclusions: Through our preliminary data at the present time, we note that the majority of our patients maintains their seizure control following replacement with VNS2 with a few showing improvement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".