Disease-modifying drugs for multiple sclerosis in pregnancy
Bibliographic record
Abstract
OBJECTIVE: To systematically review the literature regarding safety of disease-modifying drug (DMD) use during pregnancy on perinatal and developmental outcomes in offspring of patients with multiple sclerosis (MS). METHODS: A PubMed and EMBASE search up to February 2012 was conducted with a manual search of references from relevant articles. Selected studies were evaluated using internationally accepted criteria. RESULTS: Fifteen studies identified 761 interferon β-, 97 glatiramer acetate-, and 35 natalizumab-exposed pregnancies. Study quality ranged from poor to good; no study was rated excellent. Small sample sizes limited most studies. Compared with data for unexposed pregnancies, fair- to good-quality prospective cohort studies reported that interferon β exposure was associated with lower mean birth weight, shorter mean birth length, and preterm birth (<37 weeks), but not low birth weight (<2,500 g), cesarean delivery, congenital anomaly (including malformation), or spontaneous abortion. Fewer studies of fair quality were available for glatiramer acetate and natalizumab. Glatiramer acetate exposure was not associated with lower mean birth weight, congenital anomaly, preterm birth, or spontaneous abortion. Natalizumab exposure did not appear to be associated with shorter mean birth length, lower mean birth weight, or lower mean gestational age. No studies examined mitoxantrone or fingolimod exposure. One study of paternal DMD use during conception found no effect on gestational age or birth weight. Few studies examined longer-term developmental outcomes. CONCLUSION: Further studies are needed to determine the potential risks associated with preconceptional and in utero DMD exposure in patients with MS. Discontinuation of DMDs before conception is still recommended.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".