Computerized Antepartum Monitoring Using Non-invasive Fetal Ecg for High Risk Pregnancy

• Conditions: Cardiotocography
• Interventions: Device: Non-Invasive fetal ECG; Device: Fetal heart rate monitor

• Registration Number: NCT04186975
• Lead Sponsor: Rambam Health Care Campus

Brief Summary

The long term aim of this research is to evaluate a portable NI-FECG (Non-invasive fetal ECG) monitor (Holter NI-FECG) which can be used for regular remote assessment of fetal health in pregnancies at risk or to follow-up on treatments. The elaboration of a NI-FECG Holter device will offer new opportunities for fetal diagnosis and remote monitoring of problematic pregnancies because of its low-cost, non-invasiveness, portability and minimal set-up requirements.

Detailed Description

Pregnant patients that are of gestational age in which fetal heart rate monitoring is recommended and feasible will be enrolled to this cohort study. Each patient will be monitored via conventional fetal heart rate monitoring in addition to the NI-FECG method and both methods will be directly compared. Each patient will be her own control. NI-FECG is a non-invasive method of fetal monitoring' thus no ethical issues are relevant. Nevertheless, each patient will sign informed consent before participating in the study.

Study Timeline

• Status Verified: 2019-12
• Study Start: 2019-12-01
• Study First Submitted: 2019-12-02
• Study First Submitted QC: 2019-12-04
• Last Update Submitted: 2019-12-04
• Study First Posted: 2019-12-05
• Last Update Posted: 2019-12-05
• Primary Completion: 2023-12-01
• Study Completion: 2023-12-01

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: Female
• Target Recruitment: 500

Inclusion Criteria

• Singleton pregnancies.
• low-risk pregnancy: women from the post-date clinic (after 40 weeks' gestation) in which we perform routinely Non stress test and ultrasound.
• High-risk pregnancy: women who are hospitalized for different indications: IUGR, diabetes, hypertension, non-reassuring fetal heart rate, Decreased fetal movements

Exclusion Criteria

• Non singleton pregnancies.
• Do not want to participate in the study

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Low-risk pregnant women	Fetal heart rate monitor	Normal cohort: this cohort consists of pregnancies which are not at risk. Data are recorded during the normal checkup happening as part of the usual care pathway
High-risk pregnant women	Non-Invasive fetal ECG	Risk cohort: this cohort consists of pregnancies at risk and which are regularly recorded for the purpose of fetal surveillance. Specifically, the investigators recruit pregnancies with intra uterine growth restricted fetuses for this study.
Low-risk pregnant women	Non-Invasive fetal ECG	Normal cohort: this cohort consists of pregnancies which are not at risk. Data are recorded during the normal checkup happening as part of the usual care pathway
High-risk pregnant women	Fetal heart rate monitor	Risk cohort: this cohort consists of pregnancies at risk and which are regularly recorded for the purpose of fetal surveillance. Specifically, the investigators recruit pregnancies with intra uterine growth restricted fetuses for this study.

Primary Outcome Measures

Name	Time	Method
Comparison between computerized CTG and NI-FECG	4 years	To compare the predictive power of computerized CTG versus computerized NI-FECG for the assessment of abnormal traces. For that purpose, a machine learning model will be trained (1) on features extracted from the FHR trace obtained using CTG and (2) on features extracted from the FHR obtained using the NI-FECG trace
Identification of abnormal fetal heart rate from NI-FECG	2 years	To compare the clinical interpretation of the NI-FECG obtained fetal heart rate trace to the fetal heart rate interpretation from the fetal heart rate obtained from conventional CTG. This will involve blinded reading and scoring of FHR obtained from the NI-FECG and CTG from a panel of expert clinician.
Computerized NI-FECG for the prediction of abnormal FHR traces	2 years	To compare the computerized analysis of the FHR trace obtained using NI-FECG to the clinician visual interpretation of the FHR trace obtained using CTG (usual care). This will involve the implementation of algorithms that can detect standard14 and new features assessing the Fetal HRV (FHRV) and the elaboration of a machine learning model which can predict abnormal traces from these features
Develop a portable NI-FECG monitor for remote fetal monitoring.	4 years	To develop a portable NI-FECG monitor which can be used to record the fetal ECG at the patient's home. The monitor will transfer the data to a remote server where source separation will be performed to extract the fetal ECG. Algorithms implemented for extracting characteristic features and the machine learning model will be run to predict whether the traces are normal or abnormal. The elaboration of such algorithm is particularly relevant for resource constrained region where medical experts is scarce.