Maternal underweight and obesity are associated with placental pathologies in human pregnancy
Bibliographic record
Abstract
Abstract Introduction Maternal underweight and obesity are prevalent conditions, associated with chronic, low-grade inflammation, poor fetal development, and long-term adverse outcomes for the child. The placenta senses and adapts to the pregnancy environment in an effort to support optimal fetal development. However, the mechanisms driving these adaptations, and the resulting placental phenotypes, are poorly understood. We hypothesised that maternal underweight and obesity would be associated with increased prevalence of placental pathologies in term and preterm pregnancies. Methods Data from 12,154 pregnancies were obtained from the Collaborative Perinatal Project, a prospective cohort study conducted from 1959 to 1974. Macro and microscopic placental pathologies were analysed across maternal prepregnancy body mass index (BMI) to assess differences in the presence of pathologies among underweight, overweight, and obese BMI groups compared to normal weight reference BMI at term and preterm. Placental pathologies were also assessed across fetal sex. Results Pregnancies complicated by obesity had placentae with increased fetal inflammation at preterm, and increased inflammation of maternal gestational tissues at term. In term pregnancies, increasing maternal BMI associated with increased maternal vascular malperfusion (MVM), odds of an appropriately mature placenta for gestational age, and placental weight, and decreased placental efficiency. Male placentae, independent of maternal BMI, had increased inflammation, MVM, and placental efficiency than female placentae, particularly at term. Discussion Maternal underweight and obesity are not inert conditions for the placenta, and the histomorphological changes driven by suboptimal maternal BMI may serve as indicators of adversities experienced in utero and potential predictors of future health trajectories.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".