Prognostic decision support using symbolic dynamics in CTG monitoring

Stud Health Technol Inform. 2013:186:140-4.

Abstract

Foetal heart rate variability is one of the most important parameters to monitor foetal wellbeing. Linear parameters, widely employed to study foetal heart variability, have shown some limitations in highlight dynamics potentially relevant. During the last decades, therefore, nonlinear analysis methods have gained a growing interest to analyze the chaotic nature of cardiac activity. Parameters derived by techniques investigating nonlinear can be included in computerised systems of cardiotocographic monitoring. In this work, we described an application of symbolic dynamics to analyze foetal heart rate variability in healthy foetuses and a concise index, introduced for its classification in antepartum CTG monitoring. The introduced index demonstrated to be capable to highlight differences in heart rate variability and resulted correlated with the Apgar score at birth, in particular, higher variability indexes values are associated to early greater vitality at birth. These preliminary results confirm that SD can be a helpful tool in CTG monitoring, supporting medical decisions in order to assure the maximum well-being of newborns.

MeSH terms

  • Algorithms*
  • Cardiotocography / methods*
  • Decision Support Systems, Clinical*
  • Diagnosis, Computer-Assisted / methods*
  • Fetal Distress / classification
  • Fetal Distress / diagnosis*
  • Health Status*
  • Humans
  • Prognosis
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Symbolism*