Purpose: To assess the effectiveness of half peak systolic velocity deceleration time (hPSV-DT) in predicting neonatal outcomes in pregnant women with preeclampsia and to compare its usefulness with the conventional umbilical artery (UA) pulsatility index (PI) approach.
Methods: A prospective cohort study was conducted among pregnant women with preeclampsia who were admitted to the Department of Perinatology, Ministry of Health Ankara City Hospital between 01 September 2022 and 01 January 2023 at 28-41 weeks gestational age. 55 patients were divided into two groups: the study group with UA hPSV-DT value < 5th percentile (n = 22) and the control group with UA hPSV-DT value ≥ 5th percentile (n = 33). UA hPSV-DT calculates the time in milliseconds needed to halve the maximal velocity of the UA waveform using Doppler ultrasonography.
Results: Birth weight, gestational age at birth, 1st minute APGAR, 5th minute APGAR, and umbilical cord pH values were significantly lower in the anormal hPSV-DT group (p < 0.05). Additionally, the rates of admission to NICU, respiratory distress syndrome (RDS), delivery time < 34 weeks, and birth weight < 2500 g were significantly more frequent in the anormal hPSV-DT group compared to the normal hPSV-DT group (p < 0.05). UA-PI > 95th percentile was detected in only 2 (8%) of 23 patients whose newborns were admitted to the NICU (p = 0.149), while hPSV-DT < 5th percentile was detected in 16 (69%) of 23 patients (p < 0.001). According to ROC analysis, the area under the curve was 0.82 (95% CI 0.06-0.28) for admission to the NICU. The best balance of sensitivity/specificity in ROC curves was 221.5 (82.6% sensitivity, 69.1% specificity, p < 0.001).
Conclusion: UA hPSV-DT was successful in predicting composite adverse perinatal outcomes in pregnant women with preeclampsia. It is a promising novel method that is accurate, quantitative, reproducible, and easily applicable. With further studies, this method may be a primary diagnostic tool in the management of high-risk pregnancies and in determining the optimal timing of delivery.
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