This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Fetal well-being in high-risk pregnancies is assessed with serial antenatal testing after 23 weeks gestation. Frequently employed is the non-stress test (NST), which evaluates the fetal heart rate (FHR) response to fetal movements. The resulting FHR tracing is evaluated visually by a clinician for the presence of accelerations and beat-to-beat variability. A non-reassuring NST may be followed by a contraction stress test (CST), during which FHR response to contractions is monitored, or a biophysical profile (an ultrasound assessment of fetal activity). While the specificity of NSTs and CSTs is relatively high (>90%), the sensitivity is fairly low (45-55%). Recent studies suggest computerized analysis of the heart rate variability may improve the predictive value. 1 The accuracy of this assessment is enhanced when measured directly from the fetal ECG (FECG), rather than by ultrasonic determination of FHR. Furthermore the FECG waveform contributes information that more accurately predicts fetal well-being intrapartum.2 Unfortunately, acquisition of the FECG is invasive (a wire electrode placed on the fetal scalp via the maternal cervix) and not available during antepartum testing. We propose a prospective observational pilot study that will enroll approximately 200 pregnant women between 24 and 43 weeks who present for antenatal testing. Following written, informed consent, abdominal electrodes will be placed and electrical data collected to a personal computer for subsequent analysis. Demographic and relevant maternal, delivery and neonatal medical information will be abstracted from medical records. Advanced digital signal processing techniques will be applied to the abdominal electrical signal to extract the FECG, features of which will be recorded. This database of patients presenting serially for antenatal testing, and their obstetric outcome, will be analyzed to determine the additive value of FECG in predicting neonatal outcome.
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