SYSTEMIC LUPUS ERYTHEMATOSUS PREGNANCIES: TRENDS IN DISEASE MANAGEMENT AND MATERNAL – FETAL OUTCOMES COMPARING 2 TIME PERIODS (1988-2012 VS 2013-2022)
Bibliographic record
Abstract
PV186 / #574 Poster Topic: AS21 - Pregnancy and Reproductive Health Background/Purpose In the last decades, Systemic Lupus Erythematosus (SLE) pregnancies outcome has greatly improved thanks to pregnancy planning, preconception counseling, multidisciplinary follow-up and availability of compatible drugs. However, patients are burdened by an increased risk of disease flares and adverse maternal-fetal outcomes. The aim of this study was to assess how SLE pregnancies management has changed over time and how this has affected the maternal-fetal outcome. Methods Retrospective data of SLE pregnancies prospectively followed in a pregnancy clinic were collected from preconception counseling throughout the 3 trimesters. Twin pregnancies were excluded. Pregnancies from 2 different time intervals were compared: Group 1 (1988 – 2012) and Group 2 (2013-2022). Statistical analysis was performed using Mann-Whitney, Fisher or chi-square test when appropriate. p<0.05 was considered significant. Results 204 pregnancies in 141 SLE patients were included. Compared to Group 1 (n=103), Group 2 (n=101) showed higher age at conception (30 vs 33 years; p = 0.013), lower frequency of Caucasian patients and lower rate of performed preconception counseling (90% vs 63%, p < 0.0001) (Table 1). Moreover, pregnancies in Group 2 showed: lower median disease activity (SLEPDAI) and higher median C4 levels in each trimester (Table 1); higher rate of hydroxychloroquine usage (66% vs 92%; p < 0.0001); lower rate of glucocorticoids usage (84% vs 67%; p = 0.011) with lower median weekly dose (50 mg vs 25 mg; p<0.00001). No statistically significant differences were observed in disease history, pattern of organ involvement, immunosuppressive treatment and maternal - fetal outcome between the 2 groups (Table 1). Table 1 Conclusions Our data show how the approach to SLE pregnancies management has changed over time thanks to increasing knowledge and awareness in this field, as highlighted by recent recommendations. Despite the decreased use of corticosteroids, the increased use of hydroxychloroquine, and the lower disease activity observed in more recent pregnancies, pregnancy outcome was not improved. This can be related to a lower rate of preconception counseling (probably due to the increasing number of patients referred to our pregnancy clinic when already pregnant) in this group but also to the higher age at conception, the higher disease duration, and the high number of non-Caucasian patients, that are known to have a more difficult-to-treat disease because of their ethnicity and social status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".