Practice Parameter update: Management issues for women with epilepsy—Focus on pregnancy (an evidence-based review): Obstetrical complications and change in seizure frequency [RETIRED]
Bibliographic record
Abstract
OBJECTIVE: To reassess the evidence for management issues related to the care of women with epilepsy (WWE) during pregnancy, including the risk of pregnancy complications or other medical problems during pregnancy in WWE compared to other women, change in seizure frequency, the risk of status epilepticus, and the rate of remaining seizure-free during pregnancy. METHODS: A 20-member committee including general neurologists, epileptologists, and doctors in pharmacy evaluated the available evidence based on a structured literature review and classification of relevant articles published between 1985 and February 2008. RESULTS: For WWE taking antiepileptic drugs, there is probably no substantially increased risk (greater than two times expected) of cesarean delivery or late pregnancy bleeding, and probably no moderately increased risk (greater than 1.5 times expected) of premature contractions or premature labor and delivery. There is possibly a substantially increased risk of premature contractions and premature labor and delivery during pregnancy for WWE who smoke. Seizure freedom for at least 9 months prior to pregnancy is probably associated with a high likelihood (84%-92%) of remaining seizure-free during pregnancy. RECOMMENDATIONS: Women with epilepsy (WWE) should be counseled that seizure freedom for at least 9 months prior to pregnancy is probably associated with a high rate (84%-92%) of remaining seizure-free during pregnancy (Level B). However, WWE who smoke should be counseled that they possibly have a substantially increased risk of premature contractions and premature labor and delivery during pregnancy (Level C).
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".