Maternal dyslipidemia during pregnancy may increase the risk of preterm birth: A meta-analysis
Bibliographic record
Abstract
Epidemiological studies have reported an inconsistent relationship between maternal lipid levels and preterm birth (PTB). We performed this meta-analysis to evaluate the association between maternal dyslipidemia and PTB. Overall, three nested case-control studies and eight cohort studies were eligible. Effect estimates [odds ratio(OR)/relative risk] were pooled using a fixed-effects or a random-effects model. Subgroup and metaregression analyses were conducted to evaluate the sources of heterogeneity. Eleven studies involving 13,025 pregnant women were included. Compared with pregnant women with normal lipid levels, the women with elevated levels of lipids had an increased risk of PTB, and the pooled OR was 1.68 [95% confidence interval (CI): 1.25-2.26)]; meanwhile, women with lower levels of lipids also had a trend of an increased risk of PTB (OR=1.52, 95% CI=0.60-3.82). The pooled ORs for elevated levels of total cholesterol, triglycerides, low density lipoprotein-cholesterol, and lower levels of high density lipoprotein-cholesterol were 1.71 (95% CI: 1.05-2.79), 1.55 (95% CI: 1.13-2.12), 1.19 (95% CI: 0.95-1.48), and 1.33 (95% CI: 1.14-1.56), respectively. The present meta-analysis found that maternal dyslipidemia during pregnancy, either the elevated total cholesterol or triglycerides, was associated with an increased risk of PTB. These findings indicate that a normal level of maternal lipid during pregnancy may reduce the risk of PTB.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".