Pregnancy anxiety, placental corticotropin-releasing hormone and length of gestation
Bibliographic record
Abstract
OBJECTIVE: High pregnancy anxiety is a consistent predictor of earlier labor and delivery. Placental corticotropin-releasing hormone (pCRH) predicts earlier delivery consistently and it has been identified as a biological mediator of the association between pregnancy anxiety and gestational length. However, studies have not examined whether changes in pregnancy anxiety are associated with earlier birth as mediated by changes in pCRH during pregnancy. Accordingly, this study tests whether linear changes in pregnancy anxiety are associated with length of gestation indirectly through nonlinear increases in pCRH over pregnancy. METHODS: A sample of pregnant women (n=233) completed prenatal assessments in early pregnancy, second trimester, and third trimester that included a 4-item assessment of pregnancy anxiety and collection of blood samples assayed for pCRH using radioimmunoassay. Length of gestation was abstracted from medical records after birth. RESULTS: Increases in pregnancy anxiety from early pregnancy to third trimester predicted shorted length of gestation, as did nonlinear increases in pCRH over pregnancy. However, there was no evidence of an indirect effect of changes in pregnancy anxiety on length of gestation via changes in pCRH. CONCLUSIONS: These results indicate that linear changes in pregnancy anxiety and nonlinear changes in pCRH during pregnancy are independent risk factors for shortened gestational length. This study adds to a small but growing body of work on biopsychological processes in pregnancy and length of gestation. Modeling changes in psychological and biological processes during pregnancy could provide more insight into understanding risk for adverse pregnancy outcomes.
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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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".