196 Pregnancy and infant outcomes in women with MS receiving ocrelizumab: analysis of ~4,000 pregnancies
Bibliographic record
Abstract
a:2:{s:4:"lang";s:2:"en";s:7:"content";s:1255:" The aim of this study is to report pregnancy and infant outcomes in women with MS exposed to ocrelizumab before or during pregnancy and/or breastfeeding. Pregnancies from the Roche safety database were analysed. Maternal ocrelizumab exposure was defined as ≥1 infusion; in utero exposure was defined as an infusion ≤3 months prior to the last menstrual period (LMP) or during pregnancy. Major congenital anomalies (MCA) were classified via EUROCAT 1.5. As of 28 March 2024, 3,989 cumulative MS pregnancies were reported; A total of 1,000 prospective pregnancies were considered in utero exposed. In utero exposed and non-exposed groups with known outcomes had similar proportions of live births (LB) (85.8% vs 89.2%), including preterm (8.5% vs 8.1%) LB, and spontaneous abortion (6.9% vs 8.4%). The proportion of LB with MCA was similar between the exposed and non-exposed group (1.8% vs 1.5%) and remained within epidemiological background. In utero exposure to ocrelizumab, primarily occurring ≤3M before the LMP and first trimester, did not increase the risk of adverse pregnancy or infant outcomes. Counselling remains important to ensure optimal outcomes for mothers and infants. ruth.dobson{at}qmul.ac.uk ";}
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".