New research models and novel signal analysis in studies on preterm labor: a key to progress?

Abstract

Preterm labor affects up to 20% of pregnancies, is considered a main cause of associated neonatal morbidity and mortality and is responsible for neonatal care costs of multimillion euros. In spite of that, the commercial market for this clinical indication is rather limited, which may be also related to high liability. Consequently, with only a few exceptions, preterm labor is not in the orbit of great interest of the pharmaceutical industry. Coordinated effort of research community may bring the change and help required to reduce the influence of this multifactorial syndrome on society. Between the novel techniques that are being explored in a SAFE (The Special Non-Invasive Advances in Fetal and Neonatal Evaluation Network) group, there are new research models of preterm labor as well as novel methodology of analysis of biological signals. In this article, we briefly describe new clinical and nonclinical human models of preterm labor as well as summarize some novel methods of data processing and analysis that may be used in the context of preterm labor.

Figure 1

Graphical presentation of synchronization of contractions of normal (panel A) and fibromyomatous (panel B) uterus. Panel A shows the synchronization of the recording for the normal uterine activity. (a) Uterine contractions (standardized signals); (b) Running cross-correlation functions (values of the cross-correlation coefficients correspond to the gray levels); (c) Instantaneous time shift shows the maximal values of the cross-correlation coefficients for fixed time. Panel B illustrates the synchronization for the uterine activity in patients with fibromyomas; (a) Uterine contractions; (b) Running cross-correlation functions; (c) Instantaneous time shift. In panel A, the maximal values of the cross-correlation coefficients are mainly located in the area of the positive time lags. In this area there are 99.70 per cent points of the instantaneous time shift curve. So, the propagation% parameter equals 99.70. In this case, the fundal time series mostly runs ahead of the cervical one. In panel B, the maximal values of the cross-correlation coefficients are located in the areas of the positive and negative time lags. In the area of the positive time lags are located 61.08 per cent points of the instantaneous time shift curve. In this case we have disturbed synchronization.