A149: Does Prenatal Exposure to Antimalarial Decrease the Risk of Neonatal Lupus: a Bayesian Perspective
Bibliographic record
Abstract
Background/Purpose: It had been suggested that prenatal exposure to hydroxychloroquine reduced the risk of cardiac NLE. The primary aim was to assess if prenatal exposure to antimalarials (AM) decreased the risk of cardiac NLE. The secondary aim was to analyze the effect of AM exposure on the risk of non‐cardiac NLE. Methods: A retrospective cohort study was performed on a large single‐center cohort of children exposed to anti‐Ro and/or anti‐La antibodies on whom prospective data has been collected since 1984. Inclusion criteria were: 1) first child born from a woman positive for anti‐Ro and/or anti‐La antibodies with a diagnosis of cutaneous lupus, systemic lupus erythematosus, Sjogren's syndrome, dermatomyositis or rheumatoid arthritis, 2) the mother underwent fetal chocardiography screening during pregnancy and/or the child had a postnatal ECG and 3) the child was ≥6 months old as of October 2013. We used Bayesian analysis for the association between prenatal use of AM and NLE. Results: The study population consisted of 265 children, of whom 72 were exposed to AM throughout gestation. Full laboratory data was available on 216 infants: 101 (46.8%) developed NLE and 115 (53.2%) remained unaffected. Forty nine children were classified as having no cardiac NLE but could not be diagnosed as true unaffected children as one or more blood test components were missing. These children were only included when the outcome studied was cardiac NLE. On univariable analysis and under a non‐informative prior, the probability that prenatal AM exposure would be protective (RR < 1) was 97.1% for cardiac and 66.9% for non‐cardiac NLE. On multivariable analysis, the RRs obtained were numerically higher, but still suggestive of a protective effect (). Using a more stringent RR cutoff (RR < 0.75), the effect on the outcome cardiac NLE remained significant, unlike for non‐cardiac NLE for which probabilities dropped significantly. Bayesian Analyses of the Effect of Prenatal Exposure to Antimalarial on the Risk of NLE Outcome Prior Sample size (N) RR (95% CrI) Probability of RR <1 (%) Probability of RR <0.75 (%) Univariable analyses Cardiac NLE Non‐informative 265 0.17 (0.01, 1.05) 97.1 93.8 Cardiac NLE Informative 265 0.34 (0.17, 0.66) 99.9 98.9 Non‐cardiac NLE Non‐informative 214 0.93 (0.64, 1.29) 66.9 12.7 Multivariable analyses Cardiac NLE Non‐informative 230 0.31 (0.01, 1.91) 87.8 80.0 Cardiac NLE Informative 230 0.36 (0.18, 0.72) 99.8 98.1 Non‐cardiac NLE Non‐informative 190 0.94 (0.65, 1.31) 64.0 11.6 Independent variable: prenatal exposure to AM Independent variables: prenatal exposure to AM, anti‐Ro ≥50 U/mL, anti‐La ≥50 U/mL and maternal diagnosis (Sjogren's syndrome vs all other diagnosis) NLE: neonatal lupus; RR (95% CrI): relative risk (95% credible interval) Conclusion: In this study of the largest single‐center cohort of children born to anti‐Ro and/or anti‐La antibody positive women with a connective tissue disease, we have shown that the probability that AM exposure was associated with a decreased risk of cardiac NLE was >87%. A clinically significant beneficial effect from AM exposure on non‐cardiac NLE features was not present. These findings need to be confirmed in an independent cohort.
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 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 | 0.018 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".