Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT03480139 |
| Other study ID # |
999918063 |
| Secondary ID |
18-CH-N063 |
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
February 28, 2018 |
| Est. completion date |
March 21, 2023 |
Study information
| Verified date |
March 2023 |
| Source |
National Institutes of Health Clinical Center (CC) |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Objective: To study the natural history of normal pregnancy and the most frequent pregnancy
complications responsible for the excessive rate of perinatal morbidity and mortality, in
order to develop models to predict the occurrence of these complications of pregnancy at the
earliest possible time. The study focuses on the prediction of preterm labor with intact
membranes, preterm prelabor rupture of membranes (PROM), preeclampsia, small for gestational
age, gestational diabetes, and fetal death. These complications account for a minimum of $30
billion annually in the US alone.
Study population: A cohort of pregnant women seeking care at the prenatal clinic of the
Perinatology Research Branch in Detroit, Michigan.
Design: A prospective observational cohort study of the natural history of women with a
normal pregnancy, a history of adverse outcome, or those with a complication in the index
pregnancy; therefore, this study will include nulliparous and parous women. Data will be
collected at the time of clinic visits and will include interviews, clinical measurements,
and ultrasound studies. We will assemble a biorepository of maternal biological fluids
(blood, urine, saliva, cervicovaginal fluid, gingival crevicular fluid, swabs to characterize
microbiota, amniotic fluid when a clinically indicated amniocentesis is performed). Placentas
will be collected at the time of delivery as well as umbilical blood, and swabs to
characterize the neonatal microbiota. We will use a retrospective case control and
case-cohort design to generate models for the prediction of the most common pregnancy
complications. These models will be developed by classifying obstetrical complications
according to clinical presentation and histologic placental lesions. Models will be developed
and subsequently validated in an independent cohort.
Outcome measures: The goal is to develop sensitive, specific, and parsimonious predictive
models to identify the patients at risk for developing complications of pregnancy using a
combination of clinical and biological markers (biochemical and biophysical).
Description:
Objective: To study the natural history of normal pregnancy and the most frequent pregnancy
complications responsible for the excessive rate of perinatal morbidity and mortality, in
order to develop models to predict the occurrence of these complications of pregnancy at the
earliest possible time. The study focuses on the prediction of preterm labor with intact
membranes, preterm prelabor rupture of membranes (PROM), preeclampsia, small for gestational
age, gestational diabetes, and fetal death. These complications account for a minimum of $30
billion annually in the US alone.
Study population: A cohort of pregnant women seeking care at the prenatal clinic of the
Perinatology Research Branch in Detroit, Michigan.
Design: A prospective observational cohort study of the natural history of women with a
normal pregnancy, a history of adverse outcome, or those with a complication in the index
pregnancy; therefore, this study will include nulliparous and parous women. Data will be
collected at the time of clinic visits and will include interviews, clinical measurements,
and ultrasound studies. We will assemble a biorepository of maternal biological fluids
(blood, urine, saliva, cervicovaginal fluid, gingival crevicular fluid, swabs to characterize
microbiota, amniotic fluid when a clinically indicated amniocentesis is performed). Placentas
will be collected at the time of delivery as well as umbilical blood, and swabs to
characterize the neonatal microbiota. We will use a retrospective case control and
case-cohort design to generate models for the prediction of the most common pregnancy
complications. These models will be developed by classifying obstetrical complications
according to clinical presentation and histologic placental lesions. Models will be developed
and subsequently validated in an independent cohort.
Outcome measures: The goal is to develop sensitive, specific, and parsimonious predictive
models to identify the patients at risk for developing complications of pregnancy using a
combination of clinical and biological markers (biochemical and biophysical).
