The Canadian Multiple Sclerosis Pregnancy Study: First-trimester miscarriages in women with multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: There is increasing need for evidence-based data on reproduction for women with multiple sclerosis (MS). First-trimester (first 13 weeks) miscarriages are relatively common in the general population. It is therefore important to have information on the frequency with which this occurs in women with MS. METHODS: The Canadian Multiple Sclerosis Pregnancy Study (CANPREG-MS) is a prospective study on women with MS who are pregnant or actively trying to conceive. As far as we are aware, this is the first study on miscarriages for this population that takes into account each woman's entire pregnancy history (i.e. before and after the MS diagnosis as well as during enrollment in CANPREG-MS). RESULTS: There were 208 pregnancies during the study and 36 resulted in first-trimester miscarriage for a rate of 17.31%, within the expected range of 15%-20% for the general population. CONCLUSIONS: CANPREG-MS provides real world data that there does not appear to be an increase in first-trimester miscarriages for women with MS. This information will be helpful to women with MS and their healthcare providers.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".