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| ID | Type | Description | Link |
|---|---|---|---|
| 22-4067 | Other Grant/Funding Number | Bill and Melinda Gates |
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| Name | Class |
|---|---|
| Bill and Melinda Gates Foundation | OTHER |
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Purpose: The primary objective of this study is to assess the diagnostic accuracy of an AI-enabled ultrasound tool for estimating fetal weight Participants: 1,000 pregnant individuals Procedures (methods): This prospective diagnostic accuracy study will enroll 1,000 pregnant individuals within one week of anticipated delivery. At a single visit, each participant will undergo two ultrasound assessments: (1) standardized sweeps for AI analysis (performed by both specialist and nonspecialist users), (2) specialist-performed fetal biometry.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Pregnant Women within One Week of Delivery | Participants receive a standardized ultrasound sweep protocol and specialist-performed fetal biometry. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI ultrasound diagnostic tool for fetal weight estimation | Diagnostic Test | Participants will undergo study-specific transabdominal ultrasound acquisition using standardized abdominal sweeps of the gravid abdomen, guided by external maternal landmarks and saved as cineloop videos. The cineloop videos will be analyzed by a locked deep-learning AI diagnostic tool to generate an estimated fetal weight. The AI-generated estimate will be compared with specialist-performed fetal biometry and actual birth weight to evaluate diagnostic accuracy. The AI output is for research evaluation only and will not direct clinical management during the study. |
| Measure | Description | Time Frame |
|---|---|---|
| Difference in Mean Absolute Percent Error (MAPE) in fetal weight estimation | Mean of pairwise differences in absolute percent error between the AI diagnostic tool (index test) and specialist biometry (clinical reference standard), compared against actual birthweight (ground truth). | Within 1 week of delivery, 24-42 weeks of gestation |
| Measure | Description | Time Frame |
|---|---|---|
| Proportion of fetal weight estimates within 10% of actual birthweight | Between-method difference in the proportion of estimates within 10% of actual birthweight (ground truth) for the AI diagnostic tool (index test) versus specialist biometry (clinical reference standard). | Within 1 week of delivery, 24-42 weeks of gestation |
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Inclusion Criteria:
Exclusion Criteria:
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1,000 pregnant individuals
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jeffrey R Stringer, MD | Contact | 919-962-4717 | jeff_stringer@unc.edu |
| Name | Affiliation | Role |
|---|---|---|
| Jeffrey Stringer, MD | University of North Carolina, Chapel Hill | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ochsner Health | Not yet recruiting | New Orleans | Louisiana | 70115 | United States |
Deidentified individual data that supports the results will be shared beginning 9 and continuing for 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.
beginning 9 and continuing for 36 months following publication
Investigator has approved IRB, IEC, or REB and an executed data use/sharing agreement with UNC
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| University of North Carolina | Recruiting | Chapel Hill | North Carolina | 27516 | United States |
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| University of Saskatchewan | Not yet recruiting | Saskatoon | Saskatchewan | Canada |
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| University of Rwanda | Not yet recruiting | Kigali | Rwanda |
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| University Teaching Hospital | Not yet recruiting | Lusaka | Zambia |
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| ID | Term |
|---|---|
| D020567 | Fetal Weight |
| ID | Term |
|---|---|
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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