Complexity of Cardiotocographic Signals as A Predictor of Labor

Abstract

Prediction of labor is of extreme importance in obstetric care to allow for preventive measures, assuring that both baby and mother have the best possible care. In this work, the authors studied how important nonlinear parameters (entropy and compression) can be as labor predictors. Linear features retrieved from the SisPorto system for cardiotocogram analysis and nonlinear measures were used to predict labor in a dataset of 1072 antepartum tracings, at between 30 and 35 weeks of gestation. Two groups were defined: Group A—fetuses whose traces date was less than one or two weeks before labor, and Group B—fetuses whose traces date was at least one or two weeks before labor. Results suggest that, compared with linear features such as decelerations and variability indices, compression improves labor prediction both within one (C-Statistics of 0.728) and two weeks (C-Statistics of 0.704). Moreover, the correlation between compression and long-term variability was significantly different in groups A and B, denoting that compression and heart rate variability look at different information associated with whether the fetus is closer to or further from labor onset. Nonlinear measures, compression in particular, may be useful in improving labor prediction as a complement to other fetal heart rate features.

Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review

“…The number of articles probing the use of non-linear measures to assess the fHR signals analysis has been growing in the past decade. Non-linear analysis has been successfully applied in the study of fetal heart rate with several research objectives, such as fetal maturation or gestational age (197)(198)(199), fetal gender (182,200), labor stages (201,202), cesarean section (51,203), preterm birth (80,204), impact of nuchal cord on antenatal (205), fHR baseline (206), behavioral state (207,208), IUGR (209)(210)(211)(212)(213), hypoxia (128,137,214,215), fetal distress (216)(217)(218), maternal pathologies (219,220), and signal processing (198,(221)(222)(223)(224). Therefore, it is important that the scientific community is aware of the non-linear methods used depending on the research objective.…”

“…The indices presented in this review are closely related to fetal heart variability. For instance, in ( 199 ) the authors showed that the complexity indices correlate highly with abnormal STV. In ( 143 ) the authors also report correlations between the complexity indices ranging from 0.53 to 0.78.…”

Phase Entropy Analysis of Electrohysterographic Data at the Third Trimester of Human Pregnancy and Active Parturition

“…We consider that future studies may involve the utilization of PhEn as a potential biomarker for evaluating the physiological onset of human labor or even analyzing preterm labor in clinical practice. Recent relevant studies suggest that nonlinear measures, compressibility in particular, may be useful in improving labor prediction as a complement to other parameters [ 37 ]. Additionally, PhEn could be incorporated into the current research of pattern recognition [ 38 ] of EHG data or even be included in some fetal and maternal analysis software [ 39 , 40 ].…”

Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

“…Their exploratory analysis indicates that five main factors, possibly associated with vagal and cardiac sympathetic outflows, autonomic balance, homeostatic stability, and humoral effects, drive the complex heart rate dynamics. Heart-rate entropy analyses are also considered in the paper of Monteiro-Santos et al [ 8 ], who derived fetal heart rate series from cardiotocographic signals recorded on the mothers’ abdomen between 30 and 35 gestational weeks. Their results indicate that the complexity measures of fetal heart rate contribute to the prediction of labor, a finding that opens the possibility to improve the assessment and care of the fetus and the mother.…”