Key result
A multivariate model combining fetal heart rate variability markers and sleep state information identified early-onset intrauterine growth restriction with an AUC of 76%.
Why the study?
Do Doppler-based fetal heart rate analysis markers improve the detection of early intrauterine growth restriction?
Case-Control (n=2,326)
Do Doppler-based fetal heart rate analysis markers improve the detection of early intrauterine growth restriction?
Effect estimate: AUC 76%
Doppler-derived fetal heart rate variability and sleep state markers can contribute to the antenatal detection of early-onset intrauterine growth restriction.
May aid antenatal IUGR risk stratification; leaves open prospective validation before clinical adoption.
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.
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Stroux et al. (2017) conducted a case-control in Intrauterine growth restriction (IUGR) (n=2,326). Doppler-derived fetal heart rate variability markers vs. Healthy controls was evaluated on Detection of early intrauterine growth restriction (AUC 76%). A multivariate model combining fetal heart rate variability markers and sleep state information identified early-onset intrauterine growth restriction with an AUC of 76%.
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