Acta obstetricia et gynecologica Scandinavica · 2017
Doppler-based fetal heart rate analysis markers for the detection of early intrauterine growth restriction.
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Stroux Lisa, Redman Christopher W, Georgieva Antoniya, Payne Stephen J, Clifford Gari D
Аннотация
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.
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.