Clinical associations of fetal heart rate accelerations as derived from transabdominal fetal electrocardiograms.

OBJECTIVE: To determine the value of quantifying accelerations of the fetal heart rate (FHR), as collected non-invasively during pregnancy, as a proxy for fetal movements. STUDY DESIGN: The study consists of a prospective collection of research material with retrospective analyses of the collected fetal electrocardiograms (ECGs), done in a homogeneous population in a low socioeconomic residential area of Cape Town, South Africa, as part of the Safe Passage Study. Recruitment and follow-up were done from August 2007 to August 2016. Maternal and fetal ECGs were collected non-invasively at various gestational ages, for approximately 30-60 min at a time in 4418 pregnant women. After processing of the signal, the number and duration of accelerations and the area under the acceleration curve of the FHR were calculated and compared with the pulsatility index (PI) of the uterine, umbilical, and middle cerebral arteries, common medical conditions, tobacco, alcohol, marijuana, and methamphetamine use and z-scores of the birthweight (BWZS). RESULTS: Of the total, 2777, 691, and 3879 women were at gestational ages of 20-24, 28-32 and 34-38 weeks respectively. At 20-24 weeks duration of accelerations was significantly longer in women who used marijuana (p = 0.014) or methamphetamine (p < 0.001) when compared to nonusers. At 28-32 weeks the duration of accelerations was significantly shorter in hypertensive women (p = 0.003) and significantly longer in women who used methamphetamine (p = 0.015). At 34-38 weeks the number of accelerations were significantly less in women who had hypertension ((p = 0.01) or stillbirths (p = 0.028) and the duration significantly shorter in hypertensive women (p = 0.007) and significantly longer in women who used marjuana (p = 0.003) or methamphetamine (p = 0.028). The acceleration area was significantly smaller (p = 0.02) in women who has stillbirths. Duration of accelerations was significantly longer in users of nicotine and alcohol when compared with that of abstainers. Birthweight z-score correlated significantly with number of accelerations (p < 0.01) and the acceleration area (<0.01). There was a significant negative correlation between the number of accelerations (p < 0.01) and acceleration area (p < 0.01) and the PI of the uterine artery at 34-38 weeks. CONCLUSIONS: Calculation of the acceleration parameters of the FHR during pregnancy may provide useful information for evaluating fetal development.

Accelerations of the Fetal Heart Rate in the Screening for Fetal Growth Restriction at 34-38 Week's Gestation.

OBJECTIVES: To use machine learning to determine what information on Doppler velocimetry and maternal and fetal heart rates, collected at 20-24 weeks gestation, correlates best with fetal growth restriction according to the estimated fetal weight at 34-38 weeks. STUDY DESIGN: Data of 4496 pregnant women, collected prospectively for the Safe Passage Study, from August 2007 to August 2016, were used for the present analysis. Doppler flow velocity of the uterine, umbilical, and middle cerebral arteries and transabdominally recorded maternal and fetal ECGs were collected at 20-24 weeks gestation and fetal biometry collected at 34-38 weeks from which the estimated fetal weight was calculated. Fetal growth restriction was defined as an estimated fetal weight below the 10th centile. Accelerations and decelerations of the fetal and maternal heart rates were quantified as gained or lost beats per hour of recording respectively. Machine learning with receiver operative characteristic curves were then used to determine which model gives the best performance. RESULTS: The final model performed exceptionally well across all evaluation metrics, particularly so for the Stochastic Gradient Descent method: achieving a 93% average for Classification Accuracy, Recall, Precision and F1-Score to identify the fetus with an estimated weight below the 10th percentile at 34-38 weeks. Ranking determined that the most important standard feature was the umbilical artery pulsatility index. However, the excellent overall accuracy is likely due to the value added by the pre-processed features regarding fetal gained beats and accelerations. CONCLUSION: Fetal movements, as characterized by gained beats as early as 20-24 weeks gestation, contribute to the value of the flow velocimetry of the umbilical artery at 34-38 weeks in identifying the growth restricted fetus.

Classification of intrauterine growth restriction at 34-38 weeks gestation with machine learning models.

OBJECTIVE: Intrauterine growth restriction (IUGR) is one of the most common causes of stillbirths. The objective of this study is to develop a machine learning model that will be able to accurately and consistently predict whether the estimated fetal weight (EFW) will be below the 10th percentile at 34+0-37 + 6 week's gestation stage, by using data collected at 20 + 0 to 23 + 6 weeks gestation. METHODS: Recruitment for the prospective Safe Passage Study (SPS) was done over 7.5 years (2007-2015). An essential part of the fetal assessment was the non-invasive transabdominal recording of the maternal and fetal electrocardiograms as well as the performance of an ultrasound examination for Doppler flow velocity waveforms and fetal biometry at 20 + 0 to 23 + 6 and 34 + 0 to 37 + 6 week's gestation. Several predictive models were constructed, using supervised learning techniques, and evaluated using the Stochastic Gradient Descent, k-Nearest Neighbours, Logistic Regression and Random Forest methods. RESULTS: The final model performed exceptionally well across all evaluation metrics, particularly so for the Stochastic Gradient Descent method: achieving a 93% average for Classification Accuracy, Recall, Precision and F1-Score when random sampling is used and 91% for cross-validation (both methods using a 95% confidence interval). Furthermore, the model identifies the Umbilical Artery Pulsality Index to be the strongest identifier for the prediction of IUGR - matching the literature. Three of the four evaluation methods used achieved above 90% for both True Negative and True Positive results. The ROC Analysis showed a very strong True Positive rate (y-axis) for both target attribute outcomes - AUC value of 0.771. CONCLUSIONS: The model performs exceptionally well in all evaluation metrics, showing robustness and flexibility as a predictive model for the binary target attribute of IUGR. This accuracy is likely due to the value added by the pre-processed features regarding the fetal gained beats and accelerations, something otherwise absent from previous multi-disciplinary studies. The success of the proposed predictive model allows the pursuit of further birth-related anomalies, providing a foundation for more complex models and lesser-researched subject matter. The data available for this model was a vital part of its success but might also become a limiting factor for further analyses. Further development of similar models could result in better classification performance even with little data available.