Peripartum disease activity in moderately and severely disabled women with multiple sclerosis
Bibliographic record
Abstract
Background: The effects of pregnancy on multiple sclerosis (MS) inflammatory activity are not well described in women with moderate to severe disabilities. Objective: To quantify the peripartum annualized relapse rate (ARR) in women with MS with an Expanded Disability Status Scale (EDSS) ≥ 3. Methods: We performed a retrospective cohort study of 85 pregnancies in 74 subjects with preconception EDSS ≥ 3. We quantified peripartum ARR and tested for risk factors predictive of peripartum relapses, postpartum brain magnetic resonance imaging activity (new T2 or gadolinium-enhancing lesions), and disability worsening. Results: There were 74 live births, with a 56% operative delivery rate. In subjects with relapsing-remitting MS, ARR decreased to 0.11 during the third trimester of pregnancy compared to 0.59 in the year preconception and increased to 1.22 in the 3 months postpartum. Women with a higher preconception EDSS had higher odds of postpartum relapses and clinically significant worsening of disability as compared to subjects with a lower EDSS. Conclusions: Moderately to severely disabled women with MS have a lower risk of relapse during pregnancy as compared to preconception, followed by a marked increase postpartum. Further studies are needed to identify ways to reduce peripartum inflammatory activity and disability progression in women with MS with moderate to severe disability.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".