Multiparametric analysis combining Lempel Ziv complexity and multiscale entropy of fetal heart rate variability identified severe intrauterine growth-restricted fetuses with 77.8% sensitivity and 82.4% accuracy.
Observational (n=59)
No
Does complexity analysis of fetal heart rate variability using LZC and MSE improve the early identification of severe intrauterine growth-restricted fetuses?
Multiparametric analysis of fetal heart rate variability using Lempel Ziv complexity and multiscale entropy can accurately identify severe intrauterine growth restriction in the antepartum period.
The main goal of this work is to suggest new indices for a correct identification of the intrauterine growth-restricted (IUGR) fetuses on the basis of fetal heart rate (FHR) variability analysis performed in the antepartum period. To this purpose, we analyzed 59 FHR time series recorded in early periods of gestation through a Hewlett Packard 1351A cardiotocograph. Advanced analysis techniques were adopted including the computation of the Lempel Ziv complexity (LZC) index and the multiscale entropy (MSE), that is, the entropy estimation with a multiscale approach. A multiparametric classifier based on k-mean cluster analysis was also performed to separate pathological and normal fetuses. The results show that the proposed LZC and the MSE could be useful to identify the actual IUGRs and to separate them from the physiological fetuses, providing good values of sensitivity and accuracy (Se = 77.8%, Ac = 82.4%).
Ferrario et al. (Fri,) conducted a observational in Intrauterine growth restriction (IUGR) (n=59). Lempel Ziv complexity (LZC) and multiscale entropy (MSE) analysis vs. Normal fetuses and not severe IUGR fetuses was evaluated on Accuracy of identifying severe IUGR fetuses using k-mean cluster analysis of LZC and MSE. Multiparametric analysis combining Lempel Ziv complexity and multiscale entropy of fetal heart rate variability identified severe intrauterine growth-restricted fetuses with 77.8% sensitivity and 82.4% accuracy.