Risk factors for adverse maternal and fetal outcomes in SLE patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease that increases the risk of adverse maternal and fetal outcomes in SLE pregnancies. Identifying potential risk factors can enhance preconception risk assessment for SLE pregnancies, thereby reducing the burden of pregnancy for SLE patients. Objective: The goal of this meta-analysis is to designate the risk factors for unfavorable maternal and fetal outcomes in SLE pregnancies by means of a systematic review of the literature and meta-analysis. Methods: statistic was used to assess heterogeneity. Sensitivity analysis, Egger's test, the Newcastle-Ottawa Quality Assessment Scale (NOS), and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system were also performed. Results: Eleven papers with 1,790 SLE patients who were pregnant were examined in the meta-analysis out of 2,467 citations that were screened. The meta-analysis's findings indicated that the onset of SLE is associated with an increased risk of preterm birth (OR: 2.85; 95% CI: 2.04, 3.99). Hypertension is associated with an increased risk of composite pregnancy outcomes (OR: 4.56; 95% CI: 2.42, 8.53), preterm birth (OR: 2.20; 95% CI: 1.53, 3.17) and preeclampsia (OR: 10.11; 95% CI: 1.83, 55.89). Renal involvement is associated with an increased risk of composite pregnancy outcomes (OR: 3.09; 95% CI: 1.66, 5.72) and preterm birth (OR: 1.65; 95% CI: 1.22, 2.23). Anti-dsDNA is associated with an increased risk of preterm birth (OR: 1.83; 95% CI: 1.13, 2.92) and pregnancy loss (OR: 2.64; 95% CI: 1.09, 6.40). Drug therapy is associated with a decreased risk of composite pregnancy outcomes (OR: 0.51; 95% CI: 0.31, 0.85), preterm birth (OR: 0.66; 95% CI: 0.48, 0.89) and pregnancy loss (OR: 0.42; 95% CI: 0.21, 0.84). Sensitivity analysis demonstrated how solid our results are. Egger's test revealed no discernible publication bias. Conclusion: The onset of SLE, hypertension, renal involvement, drug therapy, and serological factors have a predictive effect on the occurrence of adverse maternal and fetal outcomes in SLE pregnancies. Strengthening preconception risk assessment for SLE patients plays an important role in reducing pregnancy risks and improving the quality of life during pregnancy. Systematic review registration: https://www.crd.york.ac.uk/prospero/#recordDetails, identifier: CRD42024564190.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.046 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".