Five successful pregnancies with antenatal anakinra exposure
Bibliographic record
Abstract
OBJECTIVES: Our aim is to add to the limited existing prospective data on IL-1 inhibitor use in pregnancy. METHODS: Data were obtained from the Organization of Teratology Information Specialists Autoimmune Disease in Pregnancy Project, a prospective cohort study of pregnancy outcomes in the USA and Canada. Eligible women were enrolled prior to 19 weeks' gestation between 2004 and 2017. Outcomes were obtained by maternal interview and medical record abstraction. RESULTS: Five pregnancies with anakinra exposure were identified, all resulting in full-term singleton live births with no major or long-term complications. Three maternal subjects used anakinra for adult-onset Still's disease and two for systemic JIA. For all individuals who discontinued anakinra, some amount of steroid medication was necessary for treatment of disease flare. Two maternal subjects developed oligohydramnios, one also with pregnancy-induced hypertension. Two women had Caesarian sections, one medically indicated and one scheduled. One infant had low birth weight, but follow-up records indicated normal adjusted weight at 1 year. Three women successfully breastfed their infants, at least two of whom continued anakinra while breastfeeding. CONCLUSION: Anakinra was used successfully in five full-term pregnancies; however, two subjects developed oligohydramnios, a process that can be linked to fetal renal anomalies. Given previously reported cases of congenital renal anomalies associated with both antenatal anakinra use and maternal hyperthermia, the relationship between maternal IL-1 inhibitor use, uncontrolled maternal febrile disease and fetal outcomes should be further explored.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".