Perinatal outcomes after selective third‐trimester ultrasound screening for small‐for‐gestational age: prospective cohort study nested within <scp>DESiGN</scp> randomized controlled trial
Bibliographic record
Abstract
ABSTRACT Objective In screening for small‐for‐gestational age (SGA) using third‐trimester antenatal ultrasound, there are concerns about the low detection rates and potential for harm caused by both false‐negative and false‐positive screening results. Using a selective third‐trimester ultrasound screening program, this study aimed to investigate the incidence of adverse perinatal outcomes among cases with (i) false‐negative compared with true‐positive SGA diagnosis and (ii) false‐positive compared with true‐negative SGA diagnosis. Methods This prospective cohort study was nested within the UK‐based DESiGN trial, a prospective multicenter cohort study of singleton pregnancies without antenatally detected fetal anomalies, born at > 24 + 0 to < 43 + 0 weeks' gestation. We included women recruited to the baseline period, or control arm, of the trial who were not exposed to the Growth Assessment Protocol intervention and whose birth outcomes were known. Stillbirth and major neonatal morbidity were the two primary outcomes. Minor neonatal morbidity was considered a secondary outcome. Suspected SGA was defined as an estimated fetal weight (EFW) < 10th percentile, based on the Hadlock formula and fetal growth charts. Similarly, SGA at birth was defined as birth weight (BW) < 10th percentile, based on UK population references. Maternal and pregnancy characteristics and perinatal outcomes were reported according to whether SGA was suspected antenatally or not. Unadjusted and adjusted logistic regression models were used to quantify the differences in adverse perinatal outcomes between the screening results (false negative vs true positive and false positive vs true negative). Results In total, 165 321 pregnancies were included in the analysis. Fetuses with a false‐negative SGA screening result, compared to those with a true‐positive result, were at a significantly higher risk of stillbirth (adjusted odds ratio (aOR), 1.18 (95% CI, 1.07–1.31)), but at lower risk of major (aOR, 0.87 (95% CI, 0.83–0.91)) and minor (aOR, 0.56, (95% CI, 0.54–0.59)) neonatal morbidity. Compared with a true‐negative screening result, a false‐positive result was associated with a lower BW percentile (median, 18.1 (interquartile range (IQR), 13.3–26.9) vs 49.9 (IQR, 30.3–71.7)). A false‐positive result was also associated with a significantly increased risk of stillbirth (aOR, 2.24 (95% CI, 1.88–2.68)) and minor neonatal morbidity (aOR, 1.60 (95% CI, 1.51–1.71)), but not major neonatal morbidity (aOR, 1.04 (95% CI, 0.98–1.09)). Conclusions In selective third‐trimester ultrasound screening for SGA, both false‐negative and false‐positive results were associated with a significantly higher risk of stillbirth, when compared with true‐positive and true‐negative results, respectively. Improved SGA detection is needed to address false‐negative results. It should be acknowledged that cases with a false‐positive SGA screening result also constitute a high‐risk population of small fetuses that warrant surveillance and timely birth. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".