Dynamic Critical Congenital Heart Screening With Addition of Perfusion Measurements

NCT05637814 | Recruiting DMC

• 1 other identifier: 1933258
• Study Type: interventional
• Target: 320
• Locations: 1 country
• Sites: 3

Brief Summary

The purpose of this study is to implement and externally validate an inpatient ML algorithm that combines pulse oximetry features for critical congenital heart disease (CCHD) screening.

Conditions

Congenital Heart Disease

Keywords

Machine Learning Algorithm; Pulse Oximetry

Outcome Measures

Primary Outcomes (1)

• Area under the curve for receiver operating characteristics for critical congenital heart disease using ML inpatient algorithm.

  Receiver operating characteristics reflect a combination of sensitivity and specificity of a test. The investigators will identify the true positive and true negative rates for CCHD by confirming health status to a minimum of 2 months of age. The investigators will also utilize birth defect and death registries for missing infants.

  Through study completion, an average of 4 years

Secondary Outcomes (6)

• Sensitivity for critical congenital heart disease using ML inpatient algorithm (0-24 hours and 24-48 hours)

  Through study completion, an average of 4 years

• Specificity for critical congenital heart disease using ML inpatient algorithm (0-24 hours and 24-48 hours)

  Through study completion, an average of 4 years

• Area under the curve for receiver operating characteristics for critical congenital heart disease using dynamic ML algorithm

  Through study completion, an average of 4 years

• Sensitivity for critical congenital heart disease using dynamic ML algorithm

  Through study completion, an average of 4 years

• Specificity for critical congenital heart disease using dynamic ML model

  Through study completion, an average of 4 years

Other Outcomes (3)

• Frequency of repeated inpatient ML measurements

  Through study completion, an average of 4 years

• Feasibility: Number of minutes needed to obtain simultaneous artifact free hand and foot measurements such that all pulse oximetry features can be included.

  Through study completion, an average of 4 years

• Feasibility: Number of outpatient pulse oximetry measurements obtained

  Through study completion, an average of 4 years

Study Arms (1)

SpO2 and PIx Measurement

EXPERIMENTAL

Non-invasive measurements of oxygenation (SpO2) and perfusion (PIx) will be measured with pulse oximeters and a ML CCHD screening algorithm will be assigning a prediction every minute.

Diagnostic Test: SpO2/PIx Measurement and ML Algorithm

Interventions

SpO2/PIx Measurement and ML Algorithm DIAGNOSTIC_TEST

Right upper and any lower extremity oxygen saturation (SpO2) and perfusion index (PIx) will be measured and an online ML inference model will be used to classify a newborn as healthy versus CCHD as new pulse oximetry data is collected.

SpO2 and PIx Measurement

Eligibility Criteria

• Age: 0 Minutes - 21 Days
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)

You may qualify if:

• 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

You may not qualify if:

• 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.

Sponsors & Collaborators

• University of California, Davis: lead
• National Institutes of Health (NIH): collaborator

Study Sites (3)

UC Davis Medical Center

Davis, California, 95616, United States

RECRUITING

Cohen Children's Medical Center

Queens, New York, 11040, United States

NOT YET RECRUITING

University of Utah Health Care

Salt Lake City, Utah, 84102, United States

NOT YET RECRUITING

MeSH Terms

Conditions

Heart Defects, Congenital

Condition Hierarchy (Ancestors)

Cardiovascular Abnormalities; Cardiovascular Diseases; Heart Diseases; Congenital Abnormalities; Congenital, Hereditary, and Neonatal Diseases and Abnormalities

Central Study Contacts

Heather Siefkes, MD, MSCI

CONTACT

916-713-7697; hsiefkes@ucdavis.edu

Elva Horath, IMG

CONTACT

916-713-7697; ethorath@ucdavis.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: Non-invasive measurements of oxygenation and perfusion will be measured with pulse oximeters and a machine learning algorithm to improve sensitivity of CCHD screening.

Study Record Dates

• First Submitted: November 22, 2022
• First Posted: December 5, 2022
• Study Start: August 17, 2023
• Primary Completion (Estimated): June 30, 2027
• Study Completion (Estimated): December 31, 2027
• Last Updated: June 18, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will not share

Locations

US (3)