Maternal, pregnancy and fetal outcomes in de novo anti-glomerular basement membrane antibody disease in pregnancy: a systematic review
Bibliographic record
Abstract
BACKGROUND: Outside of pregnancy, anti-glomerular basement membrane (GBM) antibody disease is associated with significant morbidity and mortality. However, there is limited knowledge regarding de novo anti-GBM disease in pregnancy. METHODS: A systematic review was performed to identify maternal, pregnancy and fetal outcomes in de novo anti-GBM disease in pregnancy. Studies were selected from PubMed, EMBASE, Cochrane Library databases and conference proceedings, without language restriction. RESULTS: Data from eight patients were derived from seven case reports and one unpublished case. Most (6/8) patients presented after the first trimester. During pregnancy, acute kidney injury (5/8), anemia (5/8), hematuria (8/8) and proteinuria (8/8) were common. When hemodialysis was required antepartum (5/8), renal function recovery to independence of renal replacement was unlikely (2/5). While pulmonary involvement was common (5/8), no permanent damage was reported (0/8). The majority of cases ended in live births (6/8) although prematurity (6/6), intrauterine growth restriction (2/6), small for gestational age (4/6) and complications of prematurity (1/6) were common. When anti-GBM levels were tested in the living newborn, they were detectable (2/5), but no newborn renal or lung disease was reported (0/6). Complications in pregnancy included gestational diabetes (3/8), hyperemesis gravidarum (2/8) and preeclampsia (2/8). CONCLUSIONS: Live births can be achieved in de novo anti-GBM disease in pregnancy, but are commonly associated with adverse maternal, pregnancy and fetal outcomes. Only with awareness of common presentations, and management strategies can outcomes be optimized.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".