Uterine myoelectrical activity as biomarker of successful induction with Dinoprostone: Influence of parity

Díaz-Martinez, Alba; Monfort-Ortíz, Rogelio; Ye-Lin, Yiyao; Garcia-Casado, Javier; Nieto-Tous, Mar; Nieto-del-Amor, Félix; Diago-Almela, Vicente Jose; Prats-Boluda, Gema

doi:10.1016/j.bbe.2022.12.004

Cited by 4 publications

(2 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, there are only a few studies that have examined the electrophysiological aspects of the preparedness prior to labor both before and during the induction process ( Benalcazar-Parra et al, 2018 , 2019 , 2019 ; Benalcazar-Parra et al, 2019a , Benalcazar-Parra et al, 2019b ; Diaz-Martinez et al, 2023 ). Benalcazar-Parra et al showed that in the case of prostaglandin E1 (Misoprostrol) administration, successful induction was related to increase in electrophysiological activity both terms of amplitude and frequency content of the bursts ( Benalcazar-Parra et al, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Assessing uterine electrophysiology prior to elective term induction of labor

Mehl,

Simmons,

Whittington

et al. 2023

Current Research in Physiology

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

Assessing uterine electrophysiology prior to elective term induction of labor

Mehl,

Simmons,

Whittington

et al. 2023

Current Research in Physiology

View full text Add to dashboard Cite

“…It consists of EHG signals recorded from 300 subjects, of which 262 delivered to term [17]. The efficiency of an EHG signal analysis for the prediction of preterm labor has been widely evidenced in the literature using this database [18][19][20][21][22][23][24][25][26][27][28][29][30][31]. In general, the feature extraction strategies for the EHG signal analysis can be classified into three groups: linear, nonlinear, and propagated EHG signal-related features [32].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Preterm Labor from the Electrohysterogram Signals Based on Different Gestational Weeks

Far

Beiramvand

Shahbakhti

et al. 2023

Sensors

View full text Add to dashboard Cite

Timely preterm labor prediction plays an important role for increasing the chance of neonate survival, the mother’s mental health, and reducing financial burdens imposed on the family. The objective of this study is to propose a method for the reliable prediction of preterm labor from the electrohysterogram (EHG) signals based on different pregnancy weeks. In this paper, EHG signals recorded from 300 subjects were split into 2 groups: (I) those with preterm and term labor EHG data that were recorded prior to the 26th week of pregnancy (referred to as the PE-TE group), and (II) those with preterm and term labor EHG data that were recorded after the 26th week of pregnancy (referred to as the PL-TL group). After decomposing each EHG signal into four intrinsic mode functions (IMFs) by empirical mode decomposition (EMD), several linear and nonlinear features were extracted. Then, a self-adaptive synthetic over-sampling method was used to balance the feature vector for each group. Finally, a feature selection method was performed and the prominent ones were fed to different classifiers for discriminating between term and preterm labor. For both groups, the AdaBoost classifier achieved the best results with a mean accuracy, sensitivity, specificity, and area under the curve (AUC) of 95%, 92%, 97%, and 0.99 for the PE-TE group and a mean accuracy, sensitivity, specificity, and AUC of 93%, 90%, 94%, and 0.98 for the PL-TL group. The similarity between the obtained results indicates the feasibility of the proposed method for the prediction of preterm labor based on different pregnancy weeks.

show abstract

Recurrence quantification analysis of uterine vectormyometriogram reveals differences between normal-weight and overweight parturient women

Reyes-Lagos,

Abarca-Castro,

Ledesma-Ramírez

et al. 2024

Physiol. Meas.

View full text Add to dashboard Cite

Objective. This study aims to use recurrence quantification analysis (RQA) of uterine vectormyometriogram (VMG) created from the slow wave (SW) and high wave (HW) bands of electrohysterogram (EHG) signals and assess the directionality of the EHG activity (horizontal or X, vertical or Y) in normal-weight (NW) and overweight (OW) women during the first stage of labor. Approach. The study involved 41 parturient women (NW = 21 and OW = 20) during the first stage of labor, all of whom were attended at the Gynecology and Obstetrics Hospital of the Maternal and Child Institute of the State of Mexico in Toluca, Mexico. Twenty-minute EHG signals were analyzed in horizontal and vertical directions. Linear and nonlinear indices such as dominant frequency (Dom), Sample Entropy (SampEn), and RQA measures of VMG were computed for SW and HW bands. Main results. Significant differences in SampEn and Dom were observed in the SW band between NW and OW in both X and Y directions, indicating more regular dynamics of electrical uterine activity and a higher Dom in NW parturient women compared to OW women. Additionally, the RQA indices calculated from the VMG of SW were consistent and revealed that NW women exhibit more regular dynamics compared to OW women. Significance. The study demonstrates that RQA of VMG signals and EHG directionality differentiate uterine activity between NW and OW women during the first stage of labor. These findings suggest that the uterine vector may become more periodic, predictable, and stable in NW women compared to OW women. This highlights the importance of tailored clinical strategies for managing labor in OW women to improve maternal and infant outcomes.

show abstract

Uterine myoelectrical activity as biomarker of successful induction with Dinoprostone: Influence of parity

Cited by 4 publications

References 77 publications

Assessing uterine electrophysiology prior to elective term induction of labor

Assessing uterine electrophysiology prior to elective term induction of labor

Prediction of Preterm Labor from the Electrohysterogram Signals Based on Different Gestational Weeks

Recurrence quantification analysis of uterine vectormyometriogram reveals differences between normal-weight and overweight parturient women

Contact Info

Product

Resources

About