Cardiotocography Clinical Trial
Official title:
Computerized Antepartum Monitoring Using Non-invasive Fetal Ecg for High Risk Pregnancy
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.
Status | Not yet recruiting |
Enrollment | 500 |
Est. completion date | December 1, 2023 |
Est. primary completion date | December 1, 2023 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | Female |
Age group | 18 Years to 50 Years |
Eligibility |
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 |
Country | Name | City | State |
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n/a |
Lead Sponsor | Collaborator |
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Rambam Health Care Campus | Technion, Israel Institute of Technology |
Type | Measure | Description | Time frame | Safety issue |
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Primary | Identification of abnormal fetal heart rate from NI-FECG | 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. | 2 years | |
Primary | Computerized NI-FECG for the prediction of abnormal FHR traces | 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 | 2 years | |
Primary | Comparison between computerized CTG and NI-FECG | 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 | 4 years | |
Primary | Develop a portable NI-FECG monitor for remote fetal monitoring. | 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. | 4 years |
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