Affiliation:
1. Department of Pediatrics University of California Davis CA
2. Department of Electrical & Computer Engineering University of California Davis CA
3. Department of Pediatrics, Cohen Children’s Medical Center Zucker School of Medicine at Hofstra/Northwell New Hyde Park NY
4. University of Utah, Primary Children’s Hospital Salt Lake City UT
5. Department of Pediatrics University of California Los Angeles CA
6. Department of Pediatrics Sutter Sacramento Medical Center Sacramento CA
7. Department of Pediatrics University of California San Francisco CA
Abstract
Background
Oxygen saturation (Sp
o
2
) screening has not led to earlier detection of critical congenital heart disease (CCHD). Adding pulse oximetry features (ie, perfusion data and radiofemoral pulse delay) may improve CCHD detection, especially coarctation of the aorta (CoA). We developed and tested a machine learning (ML) pulse oximetry algorithm to enhance CCHD detection.
Methods and Results
Six sites prospectively enrolled newborns with and without CCHD and recorded simultaneous pre‐ and postductal pulse oximetry. We focused on models at 1 versus 2 time points and with/without pulse delay for our ML algorithms. The sensitivity, specificity, and area under the receiver operating characteristic curve were compared between the Sp
o
2
‐alone and ML algorithms. A total of 523 newborns were enrolled (no CHD, 317; CHD, 74; CCHD, 132, of whom 21 had isolated CoA). When applying the Sp
o
2
‐alone algorithm to all patients, 26.2% of CCHD would be missed. We narrowed the sample to patients with both 2 time point measurements and pulse‐delay data (no CHD, 65; CCHD, 14) to compare ML performance. Among these patients, sensitivity for CCHD detection increased with both the addition of pulse delay and a second time point. All ML models had 100% specificity. With a 2‐time‐points+pulse‐delay model, CCHD sensitivity increased to 92.86% (
P
=0.25) compared with Sp
o
2
alone (71.43%), and CoA increased to 66.67% (
P
=0.5) from 0. The area under the receiver operating characteristic curve for CCHD and CoA detection significantly improved (0.96 versus 0.83 for CCHD, 0.83 versus 0.48 for CoA; both
P
=0.03) using the 2‐time‐points+pulse‐delay model compared with Sp
o
2
alone.
Conclusions
ML pulse oximetry that combines oxygenation, perfusion data, and pulse delay at 2 time points may improve detection of CCHD and CoA within 48 hours after birth.
Registration
URL:
https://www.clinicaltrials.gov/study/NCT04056104?term=NCT04056104&rank=1
; Unique identifier: NCT04056104.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Cited by
2 articles.
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