Diagnostic accuracy of placental growth factor and ultrasound parameters to predict the small‐for‐gestational‐age infant in women presenting with reduced symphysis–fundus height
Bibliographic record
Abstract
OBJECTIVES: To assess the diagnostic accuracy of placental growth factor (PlGF) and ultrasound parameters to predict delivery of a small-for-gestational-age (SGA) infant in women presenting with reduced symphysis-fundus height (SFH). METHODS: This was a multicenter prospective observational study recruiting 601 women with a singleton pregnancy and reduced SFH between 24 and 37 weeks' gestation across 11 sites in the UK and Canada. Plasma PlGF concentration < 5(th) centile, estimated fetal weight (EFW) < 10(th) centile, umbilical artery Doppler pulsatility index > 95(th) centile and oligohydramnios (amniotic fluid index < 5 cm) were compared as predictors for a SGA infant < 3(rd) customized birth-weight centile and adverse perinatal outcome. Test performance statistics were calculated for all parameters in isolation and in combination. RESULTS: Of the 601 women recruited, 592 were analyzed. For predicting delivery of SGA < 3(rd) centile (n = 78), EFW < 10(th) centile had 58% sensitivity (95% CI, 46-69%) and 93% negative predictive value (NPV) (95% CI, 90-95%), PlGF had 37% sensitivity (95% CI, 27-49%) and 90% NPV (95% CI, 87-93%); in combination, PlGF and EFW < 10(th) centile had 69% sensitivity (95% CI, 55-81%) and 93% NPV (95% CI, 89-96%). The equivalent receiver-operating characteristics (ROC) curve areas were 0.79 (95% CI, 0.74-0.84) for EFW < 10(th) centile, 0.70 (95% CI, 0.63-0.77) for low PlGF and 0.82 (95% CI, 0.77-0.86) in combination. CONCLUSIONS: For women presenting with reduced SFH, ultrasound parameters had modest test performance for predicting delivery of SGA < 3(rd) centile. PlGF performed no better than EFW < 10(th) centile in determining delivery of a SGA infant.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".