It Is Time to Modify Treatment to Enable More Women with Rheumatoid Arthritis to Have Successful Pregnancies
Bibliographic record
Abstract
I met Linda, a 39-year-old woman diagnosed with severe rheumatoid arthritis (RA) in her mid-20s, in clinic a few months ago. Her condition had been well controlled with etanercept and methotrexate (MTX) for the past decade. Linda had been told at some point that she could not continue her medications during pregnancy. She was worried that her RA would worsen significantly while not taking her medications, so she had decided not to become a mother. Now that she was about to get married, she thought she should ask just one more time. In this issue of The Journal , the metaanalysis by Jethwa, et al accurately describes the history of RA in pregnancy1. As early as the 1930s, the medical literature included reports of temporary improvements in RA during pregnancy, followed by a postpartum flare. It was this phenomenon that led Philip Hench to look for a “Substance X” that improved RA, ultimately contributing to the discovery of cortisol and the Nobel Prize in 19502 (see box). “At the Mayo Clinic we saw, not infrequently, patients who had become pregnant during the course of their rheumatoid arthritis. It was observed that most of them noted, not long after the onset of pregnancy, an undramatic and slowly progressive development of relief from their arthritic disability.” Philip Hench, MD. Nobel Lecture, December 1950 While studies suggested that surging cortisol in pregnancy might not be the mitigating factor for RA, other immunologic reasons have been discovered. In 1993, Nelson, et al published a study of 46 pregnant women with RA, demonstrating that the 34 who improved had a greater degree of maternal-fetal genetic disparity than the 12 who did not improve3. Similarly, high levels of fetal DNA in the mother’s circulation have been associated with decreased RA … Address correspondence to Dr. M.E. Clowse, Box 3535, Trent Drive, Durham, North Carolina 27710, USA. E-mail: Megan.clowse{at}duke.edu
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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 | 0.005 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".