Association Between Maternal Cytomegalovirus Seropositivity, Preterm Birth, and Preeclampsia in Two Cohorts From Quebec, Canada: A Mediation Analysis
Bibliographic record
Abstract
PROBLEM: Preterm birth and preeclampsia significantly contribute to infant morbidity and mortality, posing critical public health concerns. Viral infections, particularly Cytomegalovirus (CMV), associated with chronic inflammation, may play a role in these adverse pregnancy outcomes. The contribution of CMV to preterm birth and preeclampsia requires further investigation. METHOD OF STUDY: Data from 6048 pregnant women from two prospective Quebec cohorts, recruited between May 2005 and August 2012, were analyzed. First-trimester CMV serology was the exposure variable. Associations were assessed using multivariable logistic regression adjusted by inverse probability treatment weighting (IPTW) of propensity scores. Mediation analyses estimated the direct effect of maternal CMV serostatus on preterm birth, excluding mediation by preeclampsia. RESULTS: Preterm birth and preeclampsia proportions were 5.1% (95% CI: 4.6-5.7) and 1.9% (95% CI: 1.6-2.3), respectively. Multivariable logistic regression adjusted by IPTW showed associations between CMV seropositivity and preterm birth (OR 1.20, 95% CI: 1.02-1.41) and CMV seropositivity and preeclampsia (OR 1.41, 95% CI: 1.08-1.84). Mediation analysis indicated that 97% of the total effect of CMV seropositivity on preterm birth is direct, with the remaining 3% mediated by preeclampsia. CONCLUSIONS: CMV seropositivity appears to be a risk factor for both preterm birth and preeclampsia. The effect of maternal CMV seropositivity on preterm birth is primarily direct, not mediated by preeclampsia. Future studies should explore the impact of preventive measures against CMV infection on the incidence of preterm delivery and preeclampsia.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".