Feasibility of Labor Induction Success Prediction based on Uterine Myoelectric Activity Spectral Analysis

C. Benalcazar Parra, A. I. Tendero, Y. Ye-Lin, J. Alberola-Rubio, A. Perales Marin, J. Garcia-Casado, G. Prats-Boluda

2018

Abstract

Labor induction using prostaglandins (PG) is a common practice to promote uterine contractions and to facilitate cervical ripening. However, not all cases of labor inductions result in vaginal deliveries and it has been associated with an increased risk of cesarean delivery. This last situation is associated to a greater healthcare economic impact and to an increment in the maternal and fetal mortality and morbidity. Obstetricians face different scenarios daily during a labor induction and it would be advantageous to be able to infer the result of the labor induction for a better labor management. Uterine electrohysterogram (EHG) has been proven to play an outstanding role in monitoring uterine dynamics and in characterizing the uterine myoelectrical activity. Therefore, the aim of this study was to characterize and to compare the response of uterine myoelectrical activity to labor induction drugs for different labor induction outcomes by obtaining and analyzing the evolution of spectral parameters from EHG records picked up during the first 4 hours after labor induction onset. Specifically, deciles from the EHG-bursts’ power spectral density (PSD) were worked out. Our results showed that deciles D8 and D9 are able to discriminate between women who achieved active phase of labor and those who did not. For women who achieved active phase of labor, D5 makes it possible to separate women who delivered vaginally and those who underwent a cesarean section; finally D2-D6 enabled us to distinguish vaginal deliveries within 24 hours after induction onset from the other outcomes. Thus, deciles computed from EHG PSD are potentially useful to discriminate the different outcomes of a labor induction, suggesting the feasibility of induction success prediction based on EHG recording.

Paper Citation

in Harvard Style

Benalcazar Parra C., Tendero A., Ye-Lin Y., Alberola-Rubio J., Perales Marin A., Garcia-Casado J. and Prats-Boluda G. (2018). Feasibility of Labor Induction Success Prediction based on Uterine Myoelectric Activity Spectral Analysis . In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS; ISBN 978-989-758-279-0, SciTePress, pages 70-77. DOI: 10.5220/0006649400700077

in Bibtex Style

@conference{biosignals18,
author={C. Benalcazar Parra and A. I. Tendero and Y. Ye-Lin and J. Alberola-Rubio and A. Perales Marin and J. Garcia-Casado and G. Prats-Boluda},
title={Feasibility of Labor Induction Success Prediction based on Uterine Myoelectric Activity Spectral Analysis },
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS},
year={2018},
pages={70-77},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006649400700077},
isbn={978-989-758-279-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS
TI - Feasibility of Labor Induction Success Prediction based on Uterine Myoelectric Activity Spectral Analysis
SN - 978-989-758-279-0
AU - Benalcazar Parra C.
AU - Tendero A.
AU - Ye-Lin Y.
AU - Alberola-Rubio J.
AU - Perales Marin A.
AU - Garcia-Casado J.
AU - Prats-Boluda G.
PY - 2018
SP - 70
EP - 77
DO - 10.5220/0006649400700077
PB - SciTePress