Improved estimates of foetal growth are associated with perinatal outcomes: A latent modelling approach in a population-based birth cohort
Bibliographic record
Abstract
Background: We aimed to estimate latent foetal growth conditions and explore their determinants among maternal characteristics and ultrasound biometric parameters. We additionally investigated the influence of foetal growth conditions on perinatal variables. Methods: We used data from live-born singletons in the Maternal and Child Health and Nutrition in Acre, Brazil (MINA-Brazil Study) population-based birth cohort. Maternal and perinatal characteristics were assessed in medical records from the maternity hospital and interviews with participants from July 2015 to June 2016. A sub-sample went through ultrasound examinations during the antenatal period, with assessment of foetal head and abdominal circumferences, and femur length. We estimated latent foetal growth conditions with a structural equation modelling framework, informed by the child's birth weight z-scores (BWZ) and birth length z-scores (BLZ) according to gestational age. Odds ratios and 95% confidence intervals (CIs) for the occurrence of perinatal events were estimated according to linear predictions of the latent variable. Results: We included 1253 participants. Latent foetal growth conditions explained 88.3% of BWZ and 53.7% of BLZ variation. Maternal elevated blood pressure, primiparity, smoking, malaria, and insufficient gestational weight gain negatively impacted foetal growth conditions. In the subsample (n = 499), ultrasound biometric parameters assessed at 28 weeks were positively associated with the latent variable, with the largest contribution from foetal abdominal circumference. Each standardised unit of predicted foetal growth conditions halved the chance for preterm birth (95% CI = 0.26, 0.74) and longer hospital stay (>3 days) (95% CI = 0.28, 0.88). Conversely, BWZ and BLZ were not independently associated with these perinatal variables in separate logistic regression models. Conclusions: Latent foetal growth conditions jointly encompassing weight gain and linear growth during gestation were negatively influenced by a scenario of dual burden of maternal morbidities, with perinatal implications.
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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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".