Pregnancy Outcomes Among Women With Bulimia Nervosa [A217]
Bibliographic record
Abstract
INTRODUCTION: Bulimia nervosa may be associated with inadequate pregnancy weight gain, nutritional deficiencies, and maternal stress. However, knowledge of maternal and newborn risks associated with bulimia nervosa during pregnancy remains limited. The objective of this study was to evaluate pregnancy outcomes among women with bulimia nervosa using a population database. METHODS: A retrospective cohort study was conducted using data from the Healthcare Cost and Utilization Project–Nationwide Inpatient Sample from 2004 to 2014. ICD-9 code 307.51 was used to identify deliveries among women with bulimia nervosa. Multivariate logistic regression analyses were performed, adjusting for confounding effects. RESULTS: Of the 9,096,788 pregnancies included in the cohort, 260 were among women with bulimia nervosa (2.86/100,000 pregnancies). Infants born to women with bulimia nervosa were more likely to be small for gestational age (SGA) compared to infants born to women without bulimia nervosa (aOR, 3.35; 95% CI, 1.85–6.09). There were no statistically significant differences in the risk of gestational hypertension, preeclampsia, gestational diabetes, or preterm delivery between groups. CONCLUSION: Contrary to previous smaller studies, we found an increased risk of SGA among pregnant women with bulimia nervosa. Therefore, we recommend increased surveillance for fetal growth restriction among women with eating disorders in pregnancy.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".