Canadian Pregnancy Outcomes in Rheumatoid Arthritis and Systemic Lupus Erythematosus
Bibliographic record
Abstract
Objective. To describe obstetrical and neonatal outcomes in Canadian women with rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE). Methods. An administrative database of hospitalizations for neonatal delivery (1998-2009) from Calgary, Alberta was searched to identify women with RA (38 pregnancies) or SLE (95 pregnancies), and women from the general population matched on maternal age and year of delivery (150 and 375 pregnancies, resp.). Conditional logistic regression was used to calculate odds ratios (OR) for maternal and neonatal outcomes, adjusting for parity. Results. Women with SLE had increased odds for preeclampsia or eclampsia (SLE OR 2.16 (95% CI 1.10-4.21; P = 0.024); RA OR 2.33 (95% CI 0.76-7.14; P = 0.138)). Women with SLE had increased odds for cesarean section after adjustment for dysfunctional labour, instrumentation and previous cesarean section (OR 3.47 (95% CI 1.67-7.22; P < 0.001)). Neonates born to women with SLE had increased odds of prematurity (SLE OR 6.17 (95% CI 3.28-11.58; P < 0.001); RA OR 2.66 (95% CI 0.90-7.84; P = 0.076)) and of SGA (SLE OR 2.54 (95% CI 1.42-4.55; P = 0.002); RA OR 2.18 (95% CI 0.84-5.66; P = 0.108)) after adjusting for maternal hypertension. There was no excess risk of congenital defects in neonates. Conclusions. There is increased obstetrical and neonatal morbidity in Canadian women with RA or SLE.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".