Doppler‐based fetal heart rate analysis markers for the detection of early intrauterine growth restriction. (27th September 2017)

• Record Type: Journal Article
• Authors: Stroux, Lisa; Redman, Christopher W.; Georgieva, Antoniya; Payne, Stephen J.; Clifford, Gari D.
• Is Part Of: Acta obstetricia et gynecologica Scandinavica. Volume 96:Number 11(2017)
• Page Start: 1322
• Page End: 1329
• Publication Date: 2017-09-27
• Subjects: Cardiotocography -- Doppler -- heart rate variability -- intrauterine growth restriction -- low‐cost automated fetal monitoring; Gynecology -- Periodicals; Pregnancy -- Periodicals; Obstetrics -- Periodicals; 618.05
• DOI: 10.1111/aogs.13228
• Languages: English
• ISSNs: 0001-6349

Abstract

Abstract: Introduction: One indicator for fetal risk of mortality is intrauterine growth restriction (IUGR). Whether markers reflecting the impact of growth restriction on the cardiovascular system, computed from a Doppler‐derived heart rate signal, would be suitable for its detection antenatally was studied. Material and methods: We used a cardiotocography archive of 1163 IUGR cases and 1163 healthy controls, matched for gestation and gender. We assessed the discriminative power of short‐term variability and long‐term variability of the fetal heart rate, computed over episodes of high and low variation aiming to separate growth‐restricted fetuses from controls. Metrics characterizing the sleep state distribution within a trace were also considered for inclusion into an IUGR detection model. Results: Significant differences in the risk markers comparing growth‐restricted with healthy fetuses were found. When used in a logistic regression classifier, their performance for identifying IUGR was considerably superior before 34 weeks of gestation. Long‐term variability in active sleep was superior to short‐term variability [area under the receiver operator curve (AUC) of 72% compared with 71%]. Most predictive was the number of minutes in high variation per hour (AUC of 75%). A multivariate IUGR prediction model improved the AUC to 76%. Conclusion: We suggest that heart rate variability markers together with surrogate information on sleep states can contribute to the detection of early‐onset IUGR.