UNLABELLED: The diagnosis of labor and effective prevention of preterm delivery are still among the most significant problems faced by obstetricians. Currently, there is no technique or method for objectively monitoring the uterus and assessing whether the organ has entered a state of increased activity that may indicate labor. Several studies have investigated a new, noninvasive technique to monitor uterine contractions: the electrohysterogram (EHG). Analysis of frequency-related parameters of the EHG may allow physiological uterine activity to be distinguished from uterine contractions that will lead to preterm delivery. However, although a variety of parameters and methodologies have been employed, they have not been objectively compared. The objective of this review, which was based on a systematic literature search using the Cochrane, PubMed, and EMBASE databases up to February 2008, was to determine whether frequency-related parameters of the EHG signal can reliably differentiate preterm contractions that will lead to preterm delivery from those that will not (in patients who will ultimately deliver at term) and to identify the most accurate parameter. Of all the different EHG parameters, both human and animal studies indicate that the power spectral density peak frequency may be the most predictive of true labor. The best parameter for predicting delivery is, therefore, related to the EHG spectral content shift, as calculated by Fourier transform, time-frequency, or Wavelet analysis. The incidence and extent to which shifts in uterine electrical spectral components occur, as the measurement-to-delivery interval decreases, imply that these changes might be used to predict preterm delivery. There is also promising data suggesting that a combination of the measured parameters, used as inputs to artificial neural network algorithms, may be more useful than individual ones for critically assessing uterine activity. TARGET AUDIENCE: Obstetricians & Gynecologists, Family Physicians. LEARNING OBJECTIVES: After completion of this article, the reader will be able to recall the physiology of uterine contractions leading to labor, summarize the limitations of tocodynamometry, and outline four different electrohysterogram parameters.
UNLABELLED: The diagnosis of labor and effective prevention of preterm delivery are still among the most significant problems faced by obstetricians. Currently, there is no technique or method for objectively monitoring the uterus and assessing whether the organ has entered a state of increased activity that may indicate labor. Several studies have investigated a new, noninvasive technique to monitor uterine contractions: the electrohysterogram (EHG). Analysis of frequency-related parameters of the EHG may allow physiological uterine activity to be distinguished from uterine contractions that will lead to preterm delivery. However, although a variety of parameters and methodologies have been employed, they have not been objectively compared. The objective of this review, which was based on a systematic literature search using the Cochrane, PubMed, and EMBASE databases up to February 2008, was to determine whether frequency-related parameters of the EHG signal can reliably differentiate preterm contractions that will lead to preterm delivery from those that will not (in patients who will ultimately deliver at term) and to identify the most accurate parameter. Of all the different EHG parameters, both human and animal studies indicate that the power spectral density peak frequency may be the most predictive of true labor. The best parameter for predicting delivery is, therefore, related to the EHG spectral content shift, as calculated by Fourier transform, time-frequency, or Wavelet analysis. The incidence and extent to which shifts in uterine electrical spectral components occur, as the measurement-to-delivery interval decreases, imply that these changes might be used to predict preterm delivery. There is also promising data suggesting that a combination of the measured parameters, used as inputs to artificial neural network algorithms, may be more useful than individual ones for critically assessing uterine activity. TARGET AUDIENCE: Obstetricians & Gynecologists, Family Physicians. LEARNING OBJECTIVES: After completion of this article, the reader will be able to recall the physiology of uterine contractions leading to labor, summarize the limitations of tocodynamometry, and outline four different electrohysterogram parameters.
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