TY - JOUR
T1 - A Novel Approach to Predicting Early Pregnancy Outcomes Dynamically in a Prospective Cohort Using Repeated Ultrasound and Serum Biomarkers
AU - Petersen, Jesper Friis
AU - Friis-Hansen, Lennart Jan
AU - Bryndorf, Thue
AU - Jensen, Andreas Kryger
AU - Andersen, Anders Nyboe
AU - Løkkegaard, Ellen
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023
Y1 - 2023
N2 - This study aimed to develop a dynamic model for predicting outcome during the first trimester of pregnancy using baseline demographic data and serially collected blood samples and transvaginal sonographies. A prospective cohort of 203 unselected women with an assumed healthy pregnancy of < 8 weeks’ gestation was followed fortnightly from 4–14 weeks’ gestation until either miscarriage or confirmed first trimester viability. The main outcome was development of a model to predict outcome from gestational age-dependent hazard ratios using both baseline and updated serial data from each visit. Secondary outcomes were descriptions of risk factors for miscarriage. The results showed that 18% of the women experienced miscarriages. A fetal heart rate detected before 8 weeks’ gestation indicated a 90% (95% CI 85–95%) chance of subsequent delivery. Maternal age (≥ 35 years), insufficient crown-rump-length (CRL) and mean gestational sac diameter (MSD) development, and presence of bleeding increased the risk of miscarriage. Serum biomarkers, including hCG, progesterone, and estradiol, were found to impact the risk of miscarriage with estradiol as the most important. The best model to predict miscarriage was a combination of maternal age, vaginal bleeding, CRL, and hCG. The second-best model was the sonography-absent model of maternal age, bleeding, hCG, and estradiol. This study suggests that combining maternal age, and evolving data from hCG, estradiol, CRL, and bleeding could be used to predict fetal outcome during the first trimester of pregnancy. Trial registration ClinicalTrials.gov identifier: NCT02761772.
AB - This study aimed to develop a dynamic model for predicting outcome during the first trimester of pregnancy using baseline demographic data and serially collected blood samples and transvaginal sonographies. A prospective cohort of 203 unselected women with an assumed healthy pregnancy of < 8 weeks’ gestation was followed fortnightly from 4–14 weeks’ gestation until either miscarriage or confirmed first trimester viability. The main outcome was development of a model to predict outcome from gestational age-dependent hazard ratios using both baseline and updated serial data from each visit. Secondary outcomes were descriptions of risk factors for miscarriage. The results showed that 18% of the women experienced miscarriages. A fetal heart rate detected before 8 weeks’ gestation indicated a 90% (95% CI 85–95%) chance of subsequent delivery. Maternal age (≥ 35 years), insufficient crown-rump-length (CRL) and mean gestational sac diameter (MSD) development, and presence of bleeding increased the risk of miscarriage. Serum biomarkers, including hCG, progesterone, and estradiol, were found to impact the risk of miscarriage with estradiol as the most important. The best model to predict miscarriage was a combination of maternal age, vaginal bleeding, CRL, and hCG. The second-best model was the sonography-absent model of maternal age, bleeding, hCG, and estradiol. This study suggests that combining maternal age, and evolving data from hCG, estradiol, CRL, and bleeding could be used to predict fetal outcome during the first trimester of pregnancy. Trial registration ClinicalTrials.gov identifier: NCT02761772.
KW - Early pregnancy
KW - Estradiol
KW - Miscarriage
KW - Prediction model
KW - Vaginal microbiota
KW - Viability
U2 - 10.1007/s43032-023-01323-8
DO - 10.1007/s43032-023-01323-8
M3 - Journal article
C2 - 37640889
AN - SCOPUS:85168867529
VL - 30
SP - 3597
EP - 3609
JO - Reproductive Sciences
JF - Reproductive Sciences
SN - 1933-7191
ER -