The prediction of fetal acidosis at birth by computerised analysis of intrapartum cardiotocography

Abstract

Objective To assess the capability of a computer software interpretation program, using intrapartum fetal heart rate and intrauterine pressure as recorded in a cardiotocogram to predict fetal acidosis at birth. Design and subjects A retrospective analysis of digitised fetal heart rate and uterine activity values obtained from 73 high risk women in labour. Setting Two university teaching hospitals. Methods A computer software program was constructed to analyse the digitised data and predict acidosis. The results of the analysis were compared with actual umbilical arterial blood pH and base excess at delivery. Results The software cardiotocogram interpreter was able to predict a pH of less than 7.15 with an accuracy of 77%, a sensitivity of 88% and specificity of 75% in this set of data. It was able to predict a base excess of less than –8 mmol/1 with an accuracy of 81%, a sensitivity of 76% and specificity of 82%. Conclusions A computerised method of analysing fetal heart rate and uterine activity using a simple algorithm has demonstrated a capability to predict fetal acidosis at the time of delivery. Further research in this area is warranted.

Classification of Fetal Heart Rate Using Scale Dependent Features and Support Vector Machines

“…This investigation is helped by the technological advances in computers, along with advanced signal processing and machine learning methods. Therefore, many researches have proposed automated methods and systems capable of analyzing the FHR (Arduini, et al, 1993;Berdinas, et al, 2002;Bernardes, et al, 1991;Magenes, et al, 2000;Cazares, et al, 2001;Chung, et al, 1995;Dawes, et al, 1995;Jezewski, and Wrobel, 1993;Krause, 1990;Maeda, et al, 1990;Mantel, et al, 1990a;Mantel, et al, 1990b;Salamelekis, et al, 2002;Skinner, et al, 1999;Taylor, et al, 2000). Most of the research efforts aimed to propose methodologies, not only to record, store and display the FHR, but also to classify FHR and produce indices alerting when the fetus is on the verge of severe compromise (metabolic acidosis that may lead to cerebral palsy or even death).…”

Novel approach for fetal heart rate classification introducing grammatical evolution

“…Magenes et al [20,21] and Kol et al [22] employed artificial neural networks for the interpretation of FHR recordings. Chung et al [23] developed an algorithm to analyze and predict fetal acidosis. Salamalekis et al [24], Struzik and Wijngaarden [25] and Georgoulas et al [26] employed wavelets for the analysis of the FHR signal.…”

Computerised electronic foetal heart rate monitoring in labour: automated contraction identification

“…Such a task is challenging for two reasons: noise in the tocodynamometer (TOCO) signal and sharp oscillations when the TOCO belt is poorly adjusted. Among previous reports, the first methods of identifying contractions were simple, heuristic threshold approaches [1,4,6,7,[10][11][12][13][14]. Contractions were identified as deviations of the TOCO graph from a baseline (or reference signal) above a threshold.…”