Measurement of the cardiac time intervals of the fetal ECG utilising a computerised algorithm: A retrospective observational study. (May 2022)

• Record Type: Journal Article
• Authors: Chivers, SC; Vasavan, T; Nandi, M; Hayes-Gill, BR; Jayawardane, IA; Simpson, JM; Williamson, C; Fifer, WP; Lucchini, M
• Is Part Of: JRSM cardiovascular disease. Volume 11(2022)
• Publication Date: 2022-05
• Subjects: Fetal -- ECG -- pregnancy -- abdominal fetal ECG -- cardiac time intervals -- algorithm -- signal to noise ratio; Cardiovascular system -- Diseases -- Periodicals; 616.1005
• DOI: 10.1177/20480040221096209
• Languages: English
• ISSNs: 2048-0040

Abstract

Objective: Establish whether the reliable measurement of cardiac time intervals of the fetal ECG can be automated and to address whether this approach could be used to investigate large datasets. Design: Retrospective observational study. Setting: Teaching hospitals in London UK, Nottingham UK and New York USA. Participants: Singleton pregnancies with no known fetal abnormality. Methods: Archived fetal ECG's performed using the MonicaAN24 monitor. A single ECG (PQRST) complex was generated from 5000 signal-averaged beats and electrical cardiac time intervals measured in an automated way and manually. Main Outcome measure: Validation of a newly developed algorithm to measure the cardiac time intervals of the fetal ECG. Results: 188/236 (79.7%) subjects with fECGs of suitable signal:noise ratio were included for analysis comparing manual with automated measurement. PR interval was measured in 173/188 (92%), QRS complex in 170/188 (90%) and QT interval in 123/188 (65.4%). PR interval was 107.6 (12.07) ms [mean(SD)] manual vs 109.11 (14.7) ms algorithm. QRS duration was 54.72(6.35) ms manual vs 58.34(5.73) ms algorithm. QT-interval was 268.93 (21.59) ms manual vs 261.63 (36.16) ms algorithm. QTc was 407.5(32.71) ms manual vs 396.4 (54.78) ms algorithm. The QRS-duration increased with gestational age in both manual and algorithm measurements. Conclusion: Accurate measurement of fetal ECG cardiac time intervals can be automated with potential application to interpretation of larger datasets.