Antenatal Development Evaluated Prospectively

NCT ID: NCT02478554

Last Updated: 2018-07-02

Basic Information

• Recruitment Status: WITHDRAWN
• Clinical Phase: NA
• Study Classification: INTERVENTIONAL
• Study Start Date: 2015-08-31
• Study Completion Date: 2016-08-31

Brief Summary

Fetal growth abnormalities is one of the most common problems faced in modern obstetrics. The association between low birth weight and perinatal death as well as severe morbidity is well known. Since fetal weight cannot be measured directly, obstetricians use estimates of fetal weight obtained by utilizing various ultrasonographic measurements to diagnose growth abnormalities. Currently in clinical practice, the majority of fetal ultrasound centers employ population-based fetal growth curves that have been previously published and updated to estimate fetal weight percentiles. Up to 70% of neonates found to be below the 10% percentile for estimated fetal weight in population-based growth curves are actually constitutionally small; that is a neonate deemed "small" based on standardized growth curves but in reality have reached its appropriate growth potential in relation to its genetic predisposition.

An equally difficult clinical scenario is fetal macrosomia. A recent meta-analysis revealed that the sensitivity and specificity of ultrasound detection of fetal macrosomia ranges from 15-79%. When compared with neonates with normal birth weight, the odds ratio of emergency cesarean delivery and shoulder dystocia are increased significantly.

Various ultrasound parameters have been tested in an effort to detect both fetal compromise prior to the development of permanent damage and allow differentiation between true fetal growth abnormalities and normal growth potential. Recent reports have introduced the concept of customized fetal growth curve which uses physiological variables to report an adjusted fetal growth assessment. To date, the use of customized fetal growth curves has not been evaluated prospectively. Furthermore, this strategy has not been compared to standard population-based fetal growth curves currently used in clinical practice to determine which would be the most ideal for use in clinical practice.

The primary research question is: are customized fetal growth curves more accurate than population-based fetal growth curves at predicting abnormalities in fetal growth, defined as small-for-gestational age or large-for-gestational age at birth in newborns of high-risk pregnancies? Randomly, participants will be assigned to either having fetal growth reported by customized or population bases growth curves.

Conditions

Retardation, Fetal Growth; Macrosomia, Fetal

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: SINGLE

Study Groups

Population-based

Participants will be randomly assigned to population-based fetal growth curves

Group Type: NO_INTERVENTION

No interventions assigned to this group

Customized-based

Participants will be randomly assigned to customized-based fetal growth curves (intervention)

Group Type: ACTIVE_COMPARATOR

Customized fetal growth curves

Intervention Type: OTHER

Fetal weight will be plotted against growth curves specific for height, weight, parity and ethnicity

Interventions

Customized fetal growth curves

Fetal weight will be plotted against growth curves specific for height, weight, parity and ethnicity

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

1. Gestational age greater than or equal to 24 weeks gestation.

2. Maternal age over 18 years,

3. Prior normal fetal anatomy ultrasound done at main ultrasound unit

Exclusion Criteria

1. Pregnancies carrying higher order multiples (triplets, quadruplets, etc).

• Minimum Eligible Age: 18 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

The University of Texas Health Science Center, Houston

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Other Identifiers

HSC-MS-15-0536

Identifier Type: -

Identifier Source: org_study_id