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Record W4410715763 · doi:10.3899/jrheum.2025-0390.o064

SUBOPTIMAL MEDICATION USE AND WORSE PERIPARTUM OUTCOMES IN WOMEN WITH LUPUS COMPARED TO THE GENERAL POPULATION

2025· article· en· W4410715763 on OpenAlexaffvenueabout
Stephanie Keeling, Anamaria Savu, Luan Chu, Padma Kaul

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusPopulationLupus erythematosusObstetricsPhysical therapyInternal medicineDiseaseImmunologyEnvironmental health

Abstract

fetched live from OpenAlex

O064 / #405 Topic:AS21 - Pregnancy and Reproductive Health ABSTRACT CONCURRENT SESSION 11: PREGNANCY IN SLE 24-05-2025 10:40 AM - 11:40 AM Background/Purpose Observational and population levels studies confirm that systemic lupus erythematous (SLE) is associated with worse maternal and neonatal outcomes by way of disease activity and peripartum treatment choices compared to the general population without immune-mediated inflammatory diseases (IMID).[1] Increasingly, international societies have modifed their recommendations for peripartum medication use and have recognized the general safety of medications such as hydroxychloroquine and azathioprine throughout pregnancy.[2] We hypothesize that despite increased availability of safe peripartum disease treatments for SLE, outcomes are still worse and treatments underutilized compared to those without IMID in a contemporary Albertan pregnancy cohort. Methods A contemporary pregnancy cohort of 446,017 women and corresponding birth events was assembled for the province of Alberta, Canada from the random selection of 1 live birth event per woman between Jan 1st, 2009 and December 31, 2023. We identified one group with no IMID (n=728,102) and one group with SLE (n=393) using ICD 9 and 10 codes and excluding mothers in the “no IMID” group with any dispensation of corticosteroids for 4 weeks or more during pregnancy. We compared maternal and neonatal outcomes, comorbid conditions and medication use at any point in the pregnancies among the 2 groups. Anatomical Therapeutic Chemical Classification System (ATC codes) were used to identify medication use during the 270 days prior to delivery. Results More SLE mothers (22.1%) were > 35 years old compared to 15.2% of no IMID mothers. Emergent and elective cesarean section deliveries were higher in women with SLE compared to those no IMID. Women with SLE were more likely to have preterm delivery (13.7%), “small for gestational age” babies (19.3%), and NICU admissions (18.6%), compared to those without IMID (Table 1). Medication use among SLE mothers at any point in the pregnancy included 12.5% on glucocorticoids, 3.6% on nonsteroidal antiinflammatories, 25.4% on antimalarials, 3.6% on nonbiologic disease modifying antirheumatic drugs and 1.3% on biologic DMARDs. No women had exposure to anifrolumab or belimumab. Table 1. Maternal Characteristics and Peripartum Outcomes Conclusions Women with SLE have worse peripartum outcomes compared to those without IMIDs. Medications such as antimalarials which are safe in pregnancy are underutilized which may influence these outcomes. Further peripartum studies in this population are needed to evaluate drug uptake and safety over time and whether guidelines are impacting how clinicians manage these complex patients.References:[1.] Tan Y. J Autoimmun 2022;132:102864. [2.] Russell M. Rheumatol (Oxford) 2023;62(4):1370-87.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.812

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.023
GPT teacher head0.314
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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