Placental growth factor as an indicator of fetal growth restriction in late‐onset small‐for‐gestational age pregnancies
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: At-risk small-for-gestational age (SGA) pregnancies in New Zealand are identified using Doppler ultrasound; fetuses with Doppler abnormalities are considered growth restricted (FGR). Low maternal placental growth factor (PlGF) has also been associated with late-onset FGR. AIMS: To investigate whether low PlGF at diagnosis of late-onset SGA identifies the same fetuses classified FGR by detailed Doppler studies, and the association between low PlGF and adverse pregnancy outcomes. METHODS: Among an historical database of normotensive suspected SGA pregnancies (fetal abdominal circumference <10th percentile) ≥32 weeks gestation, the ability of low PlGF (<5th percentile) to identify FGR infants was investigated. 'Initial FGR' was an abnormal umbilical artery resistance index (RI) or estimated fetal weight <3rd customised centile. 'Secondary FGR' was abnormal internal carotid RI, cerebro-placental ratio and/or mean uterine artery RI. Development of hypertensive disease and adverse perinatal outcomes were compared by PlGF status. RESULTS: Of 136 SGA pregnancies, 56 (41.1%) had initial FGR. Of the remaining, 20 (25.0%) had secondary FGR, 17 (21.3%) low PlGF. The sensitivity of low PlGF identifying secondary FGR was 0.30 (95% CI 0.14-0.50), specificity 0.83 (0.70-0.92), positive predictive value 0.47 (0.23-0.72) and negative predictive value 0.70 (0.57-0.81). Overall, low PlGF occurred in 44/136 (32.4%) pregnancies and was associated with gestational hypertensive disease (63.6% vs 15.2%, P < 0.01), adverse perinatal outcome (34.1% vs 15.2%, P = 0.01) and very low birthweight (customised centile 2.2 vs 6.8, P < 0.01). CONCLUSIONS: At diagnosis of late-onset SGA, low PlGF was poor at identifying Doppler-defined FGR. Low PlGF identified pregnancies at risk of hypertensive disease, adverse perinatal outcome and very low birthweight.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 it