Screening for critical congenital heart disease using a machine learning algorithm
Official title: Dynamic Critical Congenital Heart Screening With Addition of Perfusion Measurements
Run by University of California, Davis · NCT05637814 · Data updated 2026-11-12
This study is testing a new computer program to see if it can better screen newborns for serious heart problems using simple measurements like blood oxygen levels.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 0 Minutes to 21 Days |
| Sex | All |
| Enrollment | 320 (estimated) |
| Sponsor | University of California, Davis Academic / other |
| Locations | 3 sites (Davis, California and 2 other locations) |
| Status | Recruiting |
| Started | August 17, 2023 |
| Main results expected | June 30, 2027 |
| Study ends | December 31, 2027 |
| Registry record updated | June 18, 2026 |
| Trial ID | NCT05637814 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study are newborns under 22 days old who are suspected of having congenital heart disease or are asymptomatic and undergoing SpO2 screening for CCHD.
✕Probably not a fit
Patients who have already undergone an echocardiogram or have specific types of congenital heart defects may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This study aims to validate a machine learning algorithm that combines pulse oximetry and perfusion measurements to screen for critical congenital heart disease (CCHD) in newborns. The algorithm was previously developed and tested internally, and this study will assess its effectiveness on an external patient sample. The approach includes repeated measurements to improve detection rates while minimizing false positives. The goal is to enhance the screening process for CCHD, which can be life-threatening if not detected early.
Why it matters
Potential benefit: If successful, this study could lead to improved early detection of critical congenital heart disease in newborns, potentially saving lives.
How similar studies have gone: Previous studies have shown promise in using machine learning algorithms for similar screening approaches, indicating potential for success in this novel application.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age \< 22 days * Fetuses suspected to have congenital heart disease * Newborns with suspected/confirmed critical congenital heart disease * Asymptomatic newborn undergoing SpO2 screening for CCHD Exclusion Criteria: * Echocardiogram completed prior to enrollment as the newborn would then no longer be considered "asymptomatic undergoing SpO2 screening for CCHD" * For Newborns with confirmed/suspected congenital heart disease (CHD): a) Patent ductus arteriosus and/or atrial septal defect/patent foramen ovale without other defects, b) Corrective cardiac surgical or catheter intervention performed before enrollment or c) Current infusions of vasoactive medications other than prostaglandin therapy.
Where it's running
-
UC Davis Medical Center
Davis, California, United States Recruiting -
Cohen Children's Medical Center
Queens, New York, United States Not yet recruiting -
University of Utah Health Care
Salt Lake City, Utah, United States Not yet recruiting
Study contacts
- Study coordinator: Heather Siefkes, MD, MSCI
- Email: hsiefkes@ucdavis.edu
- Phone: 916-713-7697
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.