Monitoring of Systemic Lupus Erythematosus Pregnancies: A Systematic Literature Review
Bibliographic record
Abstract
OBJECTIVE: Few data exist to guide the frequency and type of monitoring in systemic lupus erythematosus (SLE) pregnancies. A systematic literature review was performed to address this gap in the literature. METHODS: A systematic review of original articles (1975-2015) was performed using Medline, Embase, and Cochrane Library. We included search terms for SLE, pregnancy, and monitoring. We also hand-searched reference lists, review articles, and grey literature for additional relevant articles. RESULTS: The search yielded a total of 1106 articles. After removing 117 duplicates, 929 articles that were evidently unrelated to our topic based on title and/or abstract, and 7 that were in a language other than English or French, 53 articles were included for full-text review. Following a more in-depth review, 15 were excluded: 6 did not use any measure of SLE activity and 6 did not specifically address SLE monitoring in pregnancy; 1 case series, 1 review, and 1 metaanalysis were removed. Among the 38 included studies, presence of active disease, antiphospholipid (aPL) antibodies positivity, and abnormal uterine and umbilical artery Doppler studies predicted poor pregnancy outcomes. No studies evaluated an evidence-based approach to the frequency of monitoring. CONCLUSION: Few existing studies address monitoring for optimal care during SLE pregnancies. The available data imply roles for aPL antibodies measurement (prior to pregnancy and/or during the first trimester), uterine and umbilical artery Doppler studies in the second trimester, and following disease activity. Optimal frequency of monitoring is not addressed in the existing literature.
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 | 0.013 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.018 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".