Birth hospitalization in mothers with multiple sclerosis and their newborns
Bibliographic record
Abstract
OBJECTIVE: To compare the duration of birth hospitalization in mothers with multiple sclerosis (MS) and their newborns relative to the general population and to investigate the impact of MS-related clinical factors on the length of birth hospitalization stays. METHODS: Data from the British Columbia Perinatal Database Registry and the British Columbia MS database were linked in this retrospective cohort study. The duration of birth hospitalization in mothers with MS and their newborns (n = 432) were compared with a frequency-matched sample of the general population (n = 2,975) from 1998 to 2009. Clinical factors investigated included disease duration and disability, as measured by the Expanded Disability Status Scale. A multivariable model (generalized estimating equations) was used to analyze the association between MS and duration of birth hospitalization, adjusting for factors such as maternal age, diabetes, hypertension, and consecutive births to the same mother. Additional analyses included propensity score matching to further balance cohort characteristics. RESULTS: Compared with the general population, the duration of birth hospitalization was not statistically or clinically different for mothers with MS or their newborns (median differences = +1.5 and +2.1 hours, respectively; adjusted p > 0.4). Lengths of birth hospitalization were not significantly associated with disease duration (adjusted p > 0.7) or level of disability (adjusted p > 0.5). Findings remained virtually unchanged after propensity score matching. CONCLUSIONS: Birth hospitalization has been understudied in women with MS. Contrary to existing studies, we found that MS was not associated with a longer birth hospitalization. This study provides assurance to expectant mothers with MS, their families, and health care 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".