D.6 Neurological care and outcomes of pregnant patients with epilepsy in a Canadian tertiary care center (2014-2020)
Bibliographic record
Abstract
Background: Limited data exists on neurological care and outcomes of Canadian pregnant patients with epilepsy (PPWE). This study provides Canadian data to inform practice patterns and observed outcomes for PPWE at a tertiary care center. Methods: PPWE receiving care at the University Health Network (Toronto, Canada) epilepsy clinic from January 1, 2014 to November 20 2020 were retrospectively identified with demographics and neurological data and outcomes collected. Results: A total of 195 cases were identified, with a median maternal age of 32 years (SD 4.58), a median age at first seizure of 17 years (range 1 month – 36 years old), 52% were diagnosed with genetic generalized epilepsy and 50% endorsed 6 months of seizure freedom prior to conception. In pregnancy, 93% took ASM(s) with 77% receiving therapeutic drug monitoring (TDM) and drug dose adjustments reported in 69%. Most cases (73%) maintained a stable seizure frequency. Conclusions: This study provides new Canadian data on PPWE at a tertiary care center. PPWE are overall well controlled, more likely to have young adult onset, genetic generalized epilepsy with nearly all taking ASM(s) during pregnancy. While high rates of TDM and drug dose adjustments were observed, most experienced seizure stability in pregnancy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".