Cesarian sections in women with multiple sclerosis: A Canadian prospective pregnancy study
Bibliographic record
Abstract
Background: An increasing number of women with multiple sclerosis (wMS) are considering pregnancy. Prior studies suggest increased rate of elective cesarian sections (C-sections) in wMS. Methods: The Canadian Multiple Sclerosis Pregnancy Study (CANPREG-MS) is a prospective study on pregnant wMS. This report shows comparisons between (i) CANPREG-MS wMS delivered by C-section and the general population and (ii) C-section and vaginal deliveries in this study cohort. Results: = .0085). The majority (66.7%) of C-sections were not planned, and typically were performed for obstetrical indications. C-sections were performed at an earlier gestational age than vaginal deliveries, although birthweight did not differ by mode of delivery in wMS. MS relapses (3.2%) and pseudo-relapses (3.2%) were rare in the first month after C-section deliveries, regardless of disease modifying therapy decisions during gestation and postpartum. Conclusions: C-sections were more common in wMS than the general population, but few were because of maternal MS. CANPREG-MS provides informative data for pregnancies in wMS with well-managed and relatively mild disease. This information is helpful to obstetrical and MS healthcare providers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".