Pregnancy Outcome in Idiopathic Inflammatory Myopathy Patients in a Multicenter Study
Bibliographic record
Abstract
To the Editor: Pregnancy in autoimmune diseases may be complicated for both the fetus and the mother. Polymyositis (PM) and dermatomyositis (DM) are autoimmune diseases that affect women more often than men, and can occur before childbearing years1,2. Complications during pregnancy were frequently reported in patients with PM/DM with active disease, whereas there seems to be a low risk for the fetus and mother in women with a well-controlled disease at time of conception2,3,4,5,6,7,8,9,10. Our aims were to assess the pregnancy outcome in myositis. Based on international collaboration, records for women with PM/DM who had been pregnant after the diagnosis of myositis were searched in 4 countries using the clinical databases of contributing hospitals. There were 23 women identified: Czech Republic (n = 8), Hungary (n = 9), Sweden (n = 5), and Poland (n = 1). All 23 women were white. Medical records were retrospectively reviewed using a standardized protocol. Normal delivery was defined when a healthy newborn weighing > 2500 g was delivered after 37 weeks of pregnancy. Premature delivery was defined when the pregnancy … Address correspondence to Dr. M. Nagy-Vincze, Division of Clinical Immunology, Department of Internal Medicine, University of Debrecen, Moricz Zs. u. 22, H-4032 Debrecen, Hungary. E-mail: melinda.nagyvincze{at}gmail.com
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".