Publications by authors named "Urszula Nowacka"

2 Publications

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Competing risks model for prediction of small-for-gestational-age neonates from biophysical markers at 19 to 24 weeks' gestation.

Am J Obstet Gynecol 2021 Apr 24. Epub 2021 Apr 24.

Fetal Medicine Research Institute, King's College Hospital, London, United Kingdom. Electronic address:

Background: Antenatal identification of women at high risk to deliver small-for-gestational-age neonates may improve the management of the condition. The traditional but ineffective methods for small-for-gestational-age screening are the use of risk scoring systems based on maternal demographic characteristics and medical history and the measurement of the symphysial-fundal height. Another approach is to use logistic regression models that have higher performance and provide patient-specific risks for different prespecified cutoffs of birthweight percentile and gestational age at delivery. However, such models have led to an arbitrary dichotomization of the condition; different models for different small-for-gestational-age definitions are required and adding new biomarkers or examining other cutoffs requires refitting of the whole model. An alternative approach for the prediction of small-for-gestational-age neonates is to consider small for gestational age as a spectrum disorder whose severity is continuously reflected in both the gestational age at delivery and z score in birthweight for gestational age.

Objective: This study aimed to develop a new competing risks model for the prediction of small-for-gestational-age neonates based on a combination of maternal demographic characteristics and medical history with sonographic estimated fetal weight, uterine artery pulsatility index, and mean arterial pressure at 19 to 24 weeks' gestation.

Study Design: This was a prospective observational study of 96,678 women with singleton pregnancies undergoing routine ultrasound examination at 19 to 24 weeks' gestation, which included recording of estimated fetal weight, uterine artery pulsatility index, and mean arterial pressure. The competing risks model for small for gestational age is based on a previous joint distribution of gestational age at delivery and birthweight z score, according to maternal demographic characteristics and medical history. The likelihoods of the estimated fetal weight, uterine artery pulsatility index, and mean arterial pressure were fitted conditionally to both gestational age at delivery and birthweight z score and modified the previous distribution, according to the Bayes theorem, to obtain an individualized posterior distribution for gestational age at delivery and birthweight z score and therefore patient-specific risks for any desired cutoffs for birthweight z score and gestational age at delivery. The model was internally validated by randomly dividing the data into a training data set, to obtain the parameters of the model, and a test data set, to evaluate the model. The discrimination and calibration of the model were also examined.

Results: The estimated fetal weight was described using a regression model with an interaction term between gestational age at delivery and birthweight z score. Folded plane regression models were fitted for uterine artery pulsatility index and mean arterial pressure. The prediction of small for gestational age by maternal factors was improved by adding biomarkers for increasing degree of prematurity, higher severity of smallness, and coexistence of preeclampsia. Screening by maternal factors with estimated fetal weight, uterine artery pulsatility index, and mean arterial pressure, predicted 41%, 56%, and 70% of small-for-gestational-age neonates with birthweights of <10th percentile delivered at ≥37, <37, and <32 weeks' gestation, at a 10% false-positive rate. The respective rates for a birthweight of <3rd percentile were 47%, 65%, and 77%. The rates in the presence of preeclampsia were 41%, 72%, and 91% for small-for-gestational-age neonates with birthweights of <10th percentile and 50%, 75%, and 92% for small-for-gestational-age neonates with birthweights of <3rd percentile. Overall, the model was well calibrated. The detection rates and calibration indices were similar in the training and test data sets, demonstrating the internal validity of the model.

Conclusion: The performance of screening for small-for-gestational-age neonates by a competing risks model that combines maternal factors with estimated fetal weight, uterine artery pulsatility index, and mean arterial pressure was superior to that of screening by maternal characteristics and medical history alone.
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http://dx.doi.org/10.1016/j.ajog.2021.04.247DOI Listing
April 2021

Predictive Accuracy of Singleton Versus Customized Twin Growth Chart for Adverse Perinatal Outcome: A Cohort Study.

Int J Environ Res Public Health 2021 02 19;18(4). Epub 2021 Feb 19.

Department of Obstetrics and Gynecology, Medical University of Warsaw, Starynkiewicza Square 1/3, 02-015 Warsaw, Poland.

Background: Fetal growth of twins differs from singletons. The objective was to assess the fetal growth in twin gestations in relation to singleton charts and customized twin charts, respectively, followed by a comparison of the frequency of neonatal complications in small-for-gestational-age (SGA) twins.

Methods: We performed an analysis of twin pregnancies with established chorionicity with particular emphasis on postnatal adverse outcomes in newborns classified as SGA. Neonatal birth weight was comparatively assessed using both singleton and twin growth charts with following percentile estimation. Using a statistical model, we established the prediction strength of neonatal complications in SGA twins for both methods.

Results: The dataset included 322 twin pairs (247 cases of dichorionic and 75 cases of monochorionic diamniotic gestations). Utilization of twin-specific normograms was less likely to label twins as SGA-nevertheless, this diagnosis strongly correlated with risk of observing adverse outcomes. Using a chart dedicated for twin pregnancies predicted newborn complications in the SGA group with higher sensitivity and had better positive predictive value regarding postnatal morbidity.

Conclusions: Estimating twin growth with customized charts provides better prognosis of undesirable neonatal events in the SGA group comparing to singleton nomograms and consequently might determine neonatal intensive care prenatal approach.
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http://dx.doi.org/10.3390/ijerph18042016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921915PMC
February 2021