Women's Health in Multiple Sclerosis: A Scoping Review
Bibliographic record
Abstract
Background Women with multiple sclerosis (MS) may face challenges related to managing reproduction, pregnancy, and menopause while simultaneously managing their disease. The purpose of this scoping review was to map the literature broadly related to topics relevant to women's health in MS to inform the clinical and research communities about the existing types and sources of evidence and knowledge gaps. Apart from coverage of topics within the field of women's health, we were interested in potential gaps related to geographic and racial and ethnic diversity. We also aimed to understand the degree of inclusion of women with progressive MS in this research. Methods We searched the EMBASE and Ovid Medline databases from 1980 until November 23, 2020. We included case-control and cohort studies, clinical trials and case series published in any language, conducted in women with MS, clinically isolated syndrome, or radiologically isolated syndrome, that addressed women's health. Two reviewers independently screened abstracts and full-text reports for study inclusion, and completed data extraction. Results Of 112,106 citations screened, 1,041 underwent full-text review and 353 met the inclusion criteria. The number of studies regarding women's health has increased exponentially over time. Almost half of the studies were conducted (at least in part) in Europe, while 21.7% were conducted in North America; only one study was conducted in Africa. Most studies did not report the race or ethnicity of their participants (n = 308, 87.2%). Among the 353 studies, 509 topics were reported as some studies addressed more than one topic. Over one-third of these focused on pregnancy (n = 201, 37.2%), followed by fetal/neonatal outcomes (14.4%) and sexual dysfunction (10%). Among the 201 studies that focused on pregnancy, only 51 (25.4%) included participants with progressive MS. Conclusions This review identifies important knowledge gaps related to women's health in MS and particularly the need for future studies to include participants with a broader range of races and ethnicities, with progressive MS, and living in Asia-Pacific and African regions.
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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 | 0.017 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.023 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".