Placental size and the prediction of severe early‐onset intrauterine growth restriction in women with low pregnancy‐associated plasma protein‐A
Bibliographic record
Abstract
OBJECTIVES: Screening studies for trisomy 21 demonstrate that low maternal serum pregnancy-associated plasma protein-A (PAPP-A) at 11-13 weeks' gestation is associated with stillbirth, intrauterine growth restriction (IUGR) and pre-eclampsia in chromosomally normal fetuses. However, the strength of these associations is too weak to justify screening for these placental insufficiency syndromes. Our objective was to evaluate placental size and uterine artery (UtA) Doppler imaging as second-stage screening tests for women with low PAPP-A. METHODS: We prospectively studied 90 normal singleton pregnancies with first-trimester PAPP-A </= 0.30 multiples of the median. Maternal serum alpha-fetoprotein (AFP) at 15-18 weeks' gestation, and second-trimester placental size and UtA Doppler indices were assessed as predictors of pregnancy outcome. RESULTS: The risks of IUGR, preterm delivery before 32 weeks' gestation and stillbirth were significantly associated with small placental size (relative risk (RR), 3.96; 95% CI, 2.21-5.98; RR, 3.96; 95% CI, 2.21-5.98; and RR, 6.44, 95% CI, 2.74-14.54, respectively) and elevated AFP (RR, 3.67; 95% CI, 1.78-7.71; RR, 2.48; 95% CI, 1.23-4.94; and RR, 5.14; 95% CI, 1.66-16.85, respectively), but not with abnormal UtA Doppler indices. The combination of elevated AFP and small placental size further increased the risk of IUGR (RR, 4.88; 95% CI, 2.88-5.31), delivery before 32 weeks' gestation (RR, 4.25; 95% CI, 2.38-4.98) and stillbirth (RR, 7.44; 95% CI, 3.04-3.75). CONCLUSIONS: Small placental size and elevated AFP, but not UtA Doppler indices, identify women with low PAPP-A at high risk of IUGR, extreme preterm delivery and stillbirth. These additional screening tests may directly improve perinatal outcomes in women with low PAPP-A.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".