The quality of intrapartum cardiotocography in preterm labour

Objectives The aim of this study is to determine the quality of the foetal heart rate (FHR) recording, defined as signal loss, during preterm labour below 28 weeks gestational age (GA) and contribute to the discussion if cardiotocography (CTG) is of value for the extreme preterm foetus. Methods From January 2010 to December 2019 a retrospective study was conducted with data of 95 FHR recordings of singletons born between 24 and 28 weeks GA at the Amsterdam University Medical Centre, location VUmc. FHR tracings had a duration of at least 30 min and were obtained via external ultrasound mode. Data of all recordings were divided in two groups according to gestation (24–26 weeks and 26–28 weeks). Signal loss was analysed. Statistical significance was calculated by non-parametric tests and chi-square tests. The median signal loss and the proportion of cases exceeding the International Federation of Gynaecology and Obstetrics Guidelines (FIGO) threshold of 20% signal loss were calculated. Results One-third of the recordings exceeded the 20% FIGO-criterion for adequate signal quality during the first stage of labour. In the second stage, this was nearly 75%. Similarly, the median signal loss was 13% during the first and 30% during the second stage of labour (p<0.01). Conclusions The quality of FHR monitoring in the extreme preterm foetus is inadequate in a large proportion of the foetuses, especially during the second stage. FHR monitoring is therefore controversial and should be used with caution.

Foetal heart rate assessment by empirical mode decomposition and spectral analysis

This paper focuses on studying the time-variant dynamics involved in the foetal heart rate (FHR) response resulting from the autonomic nervous system modulation. It provides a comprehensive analysis of such dynamics by relating the spectral information involved in the FHR signal with foetal physiological characteristics. This approach is based on two signal processing methods: the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and time-varying autoregressive (TV-AR) modelling. First, the CEEMDAN allows to decompose the signal into intrinsic mode functions (IMFs). Then, the TV-AR modelling allows to analyse their spectral dynamics. Results reveal that the IMFs can involve significant spectral information (p -value < 0.05) that can help to assess the foetal condition.