Maternal and neonatal outcomes in women with disorders of lipid metabolism
Bibliographic record
Abstract
OBJECTIVES: The effects of lipid metabolism disorders (LMD) on pregnancy outcomes is not well known. The purpose of this study is to evaluate the impact of LMD on maternal and fetal outcomes. METHODS: Using the Healthcare Cost and Utilization Project - National Inpatient Sample from the United States, we carried out a retrospective cohort study of all births between 1999 and 2015 to determine the risks of complications in pregnant women known to have LMDs. All pregnant patients diagnosed with LMDs between 1999 and 2015 were identified using the International Classification of Disease-9 coding, which included all patients with pure hypercholesterolemia, pure hyperglyceridemia, mixed hyperlipidemia, hyperchylomicronemia, and other lipid metabolism disorders. Adjusted effects of LMDs on maternal and newborn outcomes were estimated using unconditional logistic regression analysis. RESULTS: A total of 13,792,544 births were included, 9,666 of which had an underlying diagnosis of LMDs for an overall prevalence of 7.0 per 10,000 births. Women with LMDs were more likely to have pregnancies complicated by diabetes, hypertension, and premature births, and to experience myocardial infarctions, venous thromboembolisms, postpartum hemorrhage, and maternal death. Their infants were at increased risk of congenital anomalies, fetal growth restriction, and fetal demise. CONCLUSIONS: Women with LMDs are at significantly higher risk of adverse maternal and newborn outcomes. Prenatal counselling should take into consideration these risks and antenatal care in specialized centres should be considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".