Abstract:
Cardiotocography (CTG) is essential for monitoring high-risk pregnancies, yet perinatal asphyxia prediction accuracy remains limited to 50–55%. Regions of artifacts (missing valid signals)-including signal processing aberrations-possibly contribute to this limitation, highlighted by 40% of FDA reports on intrapartum stillbirths. This cohort study applied causal inference to two digitized CTG databases, analyzing 36,792 labor episodes (>36 weeks) at a tertiary Australian hospital (2010–2021) and externally validating on a Czech dataset (n = 552).High rates of missing valid signals (>30% fetal heart rate signal dropout or >1% maternal-fetal heart rate coincidence) was independently associated with asphyxia (aOR 1.47, 95% CI 1.19–1.81); dropout >30% showing stronger link (aOR 1.58, 95% CI 1.13–2.20 Australian dataset; aOR 2.30, 95% CI 1.08–4.91 Czech dataset). Risk of asphyxia increased with higher dropout (>37.45%, aOR 2.21 Australian dataset; >34.01%, aOR 4.08 Czech dataset). Integrating measures of missing valid signals into fetal monitoring algorithms may improve decision-making and neonatal outcomes.
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