Clinical trial NCT05433519: Diagnostic Accuracy of a Novel Machine Learning Algorithm to Estimate Gestational Age
Official title: Z 32104 - Diagnostic Accuracy of a Novel Machine Learning Algorithm to Estimate Gestational Age
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Gestational Age
Machine Learning
Pregnancy Related
Lead sponsor: University of North Carolina, Chapel Hill
Sponsor class: OTHER
Collaborators: name: Bill and Melinda Gates Foundation
First posted: 2022-06-27
Enrollment: 400
Sex: FEMALE
Minimum age (years): 18
Maximum age (years): 59
Standard ages: ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Pregnant women at 14 weeks or earlier gestation

Brief summary: This is a prospective cohort study of women enrolled early in pregnancy, with randomization to determine the timing of three follow-up visits in the second and third trimester. At each of these follow-up visits, investigators will assess gestational age with the FAMLI technology and compare that estimate to the known gestational age established early in pregnancy.

Detailed description: The primary purpose of this research is to assess the diagnostic accuracy of the FAMLI Technology, a novel machine learning-based tool for gestational age assessment that can run on a smart phone or tablet. Study staff will enroll 400 pregnant volunteers prior to 14 completed gestational weeks and obtain accurate "ground truth" gestational age dating with standard ultrasound biometry, using the crown-rump length. These participants will then be asked to return for three follow-up visits, which will include a routine sonogram performed by a trained sonographer and the collection of a set of blind sweep cineloop videos using a low-cost, battery-operated device. The research will be conducted in Chapel Hill, North Carolina (at the University of North Carolina Hospital and/or sites associated with UNC OBGYN) and in Lusaka, Zambia (at the University Teaching Hospital or Kamwala District Health Centre). Approximately equal numbers of participants will be enrolled from each country.

Eligibility criteria: Inclusion Criteria:

* 18 years of age or older
* viable intrauterine pregnancy at less than 14 0/7 weeks of gestation
* ability and willingness to provide written informed consent
* intent to remain in current geographical area of residence for the duration of study
* willingness to adhere to study procedures

Exclusion criteria:

* maternal body mass index = 40 kg/m\^2
* multiple gestation (i.e., twins or higher order)
* major fetal malformation or anomaly
* any other condition (social or medical) that, in the opinion of the study staff, would make study participation unsafe or complicate data interpretation.

Primary outcomes:
measure: Diagnostic accuracy of FAMLI Technology
timeFrame: From 14 through 27 completed weeks of gestation
Secondary outcomes:
measure: Mean absolute error in the secondary evaluation window
timeFrame: From 28 through 36 completed weeks of gestation
Other outcomes:
Locations:
city: Chapel Hill
country: United States
facility: University of North Carolina
state: North Carolina
city: Lusaka
country: Zambia
facility: University Teaching Hospital
Study officials:
affiliation: University of North Carolina
name: Jeff Stringer, MD
role: PRINCIPAL_INVESTIGATOR
References: