Development of a Predictive Model of Fetal PH At Birth from Novel Variables Derived from Cardiotocographic Tracing

Cardiotocography is the current tool used to assess fetal well-being in labor and to identify cases of fetal distress early. We decided to conduct this study because the current interpretation of the cardiotocographic trace has limitations, related to the subjective interpretation of the trace. There are currently no predictive models that can reduce this margin of error. Creating a predictive model of fetal acidosis, based on variables from the cardiotocographic tracing, could be useful in order to enable a better and more timely intervention. It can also be useful in reducing the rate of improper obstetric interventions.

The recording of the cardiotocographic trace will take place throughout the duration of labor as per internal clinical management recommendations. Once delivery has taken place (by cesarean section, obstetric suction or spontaneously), the data derived from the cardiotocographic tracing will be extracted using the Sonicaid Fetal Care Software from the cardiotocograph into a .csv file that will report for each second four measurements of heart rate and intensity of maternal contractions.

The .csv file is converted to a .sav file and the new variables are generated, using a specially created SPSS script, in order to calculate the stability and variability of fetal heart rate. Neonatal outcomes will be considered the dependent variable in this set of variables originated from the fetal heart rate patterns.

The clinical variables that will be collected for the predictive model and/or for descriptive purposes are:

• umbilical artery and vein pH
• excess umbilical artery and vein bases
• Apgar score at birth
• presence of dyed amniotic fluid
• onset of active labor of delivery
• onset of the expulsive period
• fetal expulsion
• cord rounds
• mode of delivery
• neonatal weight.

Inclusion criteria

• Maternal age between 18 and 45 years;
• Single pregnancy
• Participants undergoing continuous monitoring of labor labor
• Obtaining informed consent for study participation and processing of personal data

Exclusion criteria

• None