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Clinical Trial Summary

The overall aims of this proposal are to improve, facilitate, optimize and equalize the existing screening system for adverse pregnancy outcomes in early pregnancy in order to limit adverse consequences for both the mother and infant, by: 1. Creating a Swedish prediction model with population-specific risk factors, optimized for the Swedish health care system, identifying high-risk women for preterm preeclampsia and validate the model within the cohort. This would give us the possibility to start aspirin prophylaxis in time, which has been proven to reduce the risk of developing preterm preeclampsia by 50%. 2. Validating the Fetal Medicine Foundation prediction model for detection of preterm (< 37 gestational weeks) preeclampsia in a Swedish population. 3. Creating a prediction model identifying high-risk women for overall preeclampsia during pregnancy and birth of a small for gestational age infant in order to plan individualized surveillance for early detection, which has been proven beneficial for both the mother and infant. 4. Creating a national pregnancy biobank with blood samples and individual clinical registry data, including pregnancy outcomes, enabling future research on prevention and early detection for various adverse pregnancy outcomes which could be such as preterm birth and intrauterine growth restriction.


Clinical Trial Description

Preeclampsia is a pregnancy-specific syndrome that affects 3-5% of all pregnancies and traditionally defined as new onset hypertension (blood pressure ≥ 140/90) and proteinuria after gestational week 20. The syndrome is one of the leading causes of maternal and perinatal acute morbidity and long-term disability and accounts for about 50 000 maternal deaths annually worldwide. Morbidity risks for the mother include seizures, intracranial hemorrhage, kidney failure, heart failure and pulmonary edema. Risks for the fetus include fetal growth restriction, preterm birth and hypoxia. Generally preterm preeclampsia (delivery before 37 weeks) is more severe than term preeclampsia. Risk assessment for preeclampsia enables both prevention and early prediction of the disease. Swedish risk assessment for preeclampsia in early pregnancy is still obtained by maternal history and characteristics, without medical examinations, which only detects about 30% of women that will develop preeclampsia. Risk factors are evaluated individually without being incorporated into a combined model that would allow multivariable analysis. This approach has been proven to be poor due to low specificity and sensitivity. Lately a more complex prediction model has been developed by the Fetal Medicine Foundation, using multivariable analysis and including serum biomarkers and physiological measurements reflecting maternal adaption to pregnancy. Intervention with aspirin given to identified high-risk pregnancies according this model has been shown to decrease the incidence of preterm (< 37 gestational weeks) preeclampsia (OR: 0.38; 95% CI 0.20-0.74), compared to placebo. Detection rates and cut-off values have been shown to vary between populations, depending on differences in population characteristics and incidence of disease, overfitting of the original model and differences in healthcare systems. Therefore, the model needs to be validated in Sweden. Further, the Fetal Medicine Foundation prediction model includes expensive covariates such as several biochemical markers and uterine artery Doppler. There is a need to create, validate and implement a cost-effective prediction model for first trimester screening for preeclampsia in a Swedish population, with the purpose to select who might benefit from aspirin prophylaxis to prevent preterm preeclampsia. We will study preeclampsia both according to the definition used in Sweden prior to 2020 and the definition used hereafter. Early detection of preeclampsia remains one of the major focuses of maternal health care and is emphasized by the WHO, since it has proven to be beneficial for both the mother and unborn child. Small-for-gestational-age fetuses not identified before delivery have an increased risk of adverse perinatal outcomes, compared to those identified during pregnancy. Identification of high-risk pregnancies is therefore important in early pregnancy not only to plan for prophylactic interventions, but also to optimize surveillance and to plan deliveries. Today most Swedish women attend the same maternal health care program with increasing number of visits in the end of pregnancy. By risk identification in early pregnancy we can individualize maternal health care and target women at high risk early in pregnancy. High-risk pregnancies can be referred to specialized health care and normal pregnancies followed at the basic maternal health care. The Swedish registry data is unique and combining it with a biobank containing blood samples from the first trimester could improve maternal healthcare and in the long run reduce adverse outcomes for Swedish women. A national first trimester pregnancy biobank would facilitate future research on prevention and prediction of pregnancy complications. A total of 13000 enrolled individuals will be needed for creating the model and for validation. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03831490
Study type Observational [Patient Registry]
Source Uppsala University
Contact
Status Completed
Phase
Start date November 9, 2018
Completion date December 31, 2022

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