Prenatal screening for preeclampsia: the roles of placental growth factor and pregnancy–associated plasma protein A in the first trimester and placental growth factor and soluble fms-like tyrosine kinase 1–placental growth factor ratio in the early second trimester
Bibliographic record
Abstract
Professional societies have recommended universal first trimester screening for preeclampsia and a second or third trimester soluble fms-like tyrosine kinase-1–placental growth factor ratio test to assess for preeclampsia and its severity. However, it may not be feasible to implement the most optimal screening protocol for preeclampsia in the first trimester which uses a combination of maternal characteristics, maternal biophysical and biochemical markers due to limitations in the access to uterine artery doppler ultrasound. There are inconsistent findings on how early in the second trimester the fms-like tyrosine kinase-1–placental growth factor ratio begins to provide useful information in preeclampsia prediction. This study aimed to assess the accuracy of (1) a combination of maternal characteristics, maternal serum pregnancy-associated plasma protein A, and placental growth factor in the screening for preeclampsia in the first trimester; and (2) placental growth factor or soluble fms-like tyrosine kinase-1–placental growth factor ratio in the prediction of preeclampsia in the early second trimester. This retrospective case–control study used frozen residual blood samples from women who had aneuploidy screening and delivered at a tertiary center. The case group included pregnancies with gestational hypertension or preeclampsia (further classified as early-onset [birth at <34 weeks’ gestation] and preterm preeclampsia [birth at <37 weeks’ gestation]). Each case was matched with 3 control pregnancies by date of blood sample draw, gestational age at first blood sample draw, maternal age, maternal ethnicity, type of multiple-marker screening, and amount of residual sample. Mann–Whitney U tests were used to assess the associations between serum markers and the risk of preeclampsia. Logistic regressions were used to assess if the risk of preeclampsia can be predicted using a combination of maternal characteristics and serum markers. The case group included 146 preeclampsia and 295 gestational hypertension cases. Compared with the controls, preeclampsia cases had significantly lower first-trimester pregnancy-associated plasma protein A and placental growth factor. At a 20% false-positive rate, 71% of early-onset and 58% of preterm preeclampsia cases can be predicted using maternal characteristics, pregnancy-associated plasma protein A, and placental growth factor. Preeclampsia cases had lower second-trimester placental growth factor and a higher soluble fms-like tyrosine kinase-1–placental growth factor ratio. At a 10% false-positive rate, 80% and 53% of early-onset preeclampsia can be predicted using maternal characteristics and placental growth factor or soluble fms-like tyrosine kinase-1–placental growth factor ratio, respectively. The current first-trimester aneuploidy screening programs may be expanded to identify women at increased risk of developing preeclampsia. Early in the second trimester, placental growth factor alone provided better prediction for preeclampsia compared with the soluble fms-like tyrosine kinase-1–placental growth factor ratio.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".