Pregnancy Outcomes in Women With Neuromuscular Dystrophies: A Retrospective Study [34F]
Bibliographic record
Abstract
INTRODUCTION: Neuromuscular dystrophies (NMD) are a group of rare genetic diseases characterized by weakness and muscular wasting. Data on NMD in pregnancy is limited. Our aim is to determine the prevalence of muscular dystrophies at delivery, and related maternal and newborn outcomes. METHODS: Using the United States Healthcare Cost and Utilization Project Nationwide Inpatient Sample (HCUP-NIS) from 1999 to 2013, we conducted a population-based retrospective cohort study to compare women with and without any form of NMD at delivery. We used multivariate logistic regression analyses to estimate the associated risks of maternal and neonatal outcomes. RESULTS: Of the 12,592,178 births in our cohort, 914 deliveries were to women carrying a NMD. Over the 15-year period, there was an increased prevalence rate from 3 to 10 cases per 100 000 deliveries per year (p < 0.001). Births to women with NMD were more likely to be premature (OR 1.60, 95% CI 1.26-2.02), have intrauterine growth restriction (OR 2.08,95% CI 1.50-2.90) and congenital malformation (OR 4.93, 95% CI 3.30-7.38). Compared with controls, women with muscular dystrophies were more likely to deliver by cesarean section (OR 1.87,95% CI 1.62-2.17), have forceps assisted deliveries (OR 1.76, 95% CI 1.01-3.04), were at higher risk of major morbidities including cardiac dysrhythmia (OR 4.97,95% CI 3.02-8.20) and increased requirements for blood transfusion (OR 2.44,95% CI 1.56-3.83). CONCLUSION: Pregnancies in NMD patients are associated with an increased risk of maternal and fetal morbidities and, as such, they should be cared for in a tertiary care center.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".