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| Name | Class |
|---|---|
| Bill and Melinda Gates Foundation | OTHER |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Pregnant Women | Pregnant women with gestational age established at less than 14 weeks of gestation |
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| Measure | Description | Time Frame |
|---|---|---|
| Diagnostic accuracy of FAMLI Technology | Difference in mean absolute error (MAE) of the index test and clinical reference standard in the primary evaluation window | From 14 through 27 completed weeks of gestation |
| Measure | Description | Time Frame |
|---|---|---|
| Mean absolute error in the secondary evaluation window | Difference in mean absolute error (MAE) of the index test and clinical reference standard in the secondary evaluation window | From 28 through 36 completed weeks of gestation |
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Inclusion Criteria:
Exclusion criteria:
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Pregnant women at 14 weeks or earlier gestation
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| Name | Affiliation | Role |
|---|---|---|
| Jeff Stringer, MD | University of North Carolina | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of North Carolina | Chapel Hill | North Carolina | 27599 | United States | ||
| University Teaching Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39088200 | Derived | Stringer JSA, Pokaprakarn T, Prieto JC, Vwalika B, Chari SV, Sindano N, Freeman BL, Sikapande B, Davis NM, Sebastiao YV, Mandona NM, Stringer EM, Benabdelkader C, Mungole M, Kapilya FM, Almnini N, Diaz AN, Fecteau BA, Kosorok MR, Cole SR, Kasaro MP. Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps. JAMA. 2024 Aug 27;332(8):649-657. doi: 10.1001/jama.2024.10770. |
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Deidentified individual data that supports the results will be shared beginning 9 to 36 months following publication provided the investigator who proposes to use the data has approval from an Institutional Review Board (IRB), Independent Ethics Committee (IEC), or Research Ethics Board (REB), as applicable, and executes a data use/sharing agreement with UNC.
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9-36 months following publication
noted above
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot | Yes | No | No | Study Protocol | May 25, 2023 | May 1, 2024 | Prot_002.pdf |
| SAP | No | Yes | No | Statistical Analysis Plan | Jun 8, 2022 | Jul 5, 2022 | SAP_001.pdf |
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Whole blood, plasma, serum, and urine
| Lusaka |
| Zambia |