A novel system to collect dual pulse oximetry data for critical congenital heart disease screening research

A novel system to collect dual pulse oximetry data for critical congenital heart disease screening research

Access to patient medical data is critical to building a real-time data analytic pipeline for improving care providers' ability to detect, diagnose, and prognosticate diseases. Critical congenital heart disease (CCHD) is a common group of neonatal life-threatening defects that must be promptly...

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Bibliographic Details
Published in:Journal of clinical and translational science Vol. 5; no. 1; p. e56
Main Authors: Doshi, Kavish, Rehm, Gregory B, Vadlaputi, Pranjali, Lai, Zhengfeng, Lakshminrusimha, Satyan, Chuah, Chen-Nee, Siefkes, Heather M
Format: Journal Article
Language:English
Published: England Cambridge University Press 01-01-2021
Subjects:
Automation
Babies
Cardiovascular disease
Congenital diseases
Congenital heart disease screening
Coronary artery disease
Data collection
Enrollments
Heart diseases
Heart rate
Infants
Medical screening
Morbidity
Neonates
Oxygen
Oxygen saturation
Perfusion
Pulse oximetry
Software
Translational Research, Design and Analysis
United States > US
California
pulse oximetry
Congenital heart disease screening
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Summary:Access to patient medical data is critical to building a real-time data analytic pipeline for improving care providers' ability to detect, diagnose, and prognosticate diseases. Critical congenital heart disease (CCHD) is a common group of neonatal life-threatening defects that must be promptly diagnosed to minimize morbidity and mortality. CCHD can be diagnosed both prenatally and postnatally. However, despite current screening practices involving oxygen saturation analysis, timely diagnosis is missed in approximately 900 infants with CCHD annually in the USA and can benefit from increased data processing capabilities. Adding non-invasive perfusion measurements to oxygen saturation data can improve the timeliness and fidelity of CCHD diagnostics. However, real-time monitoring and interpretation of non-invasive perfusion data are currently limited. To address this challenge, we created a hardware and software architecture utilizing a Pi-top™ for collecting, visualizing, and storing dual oxygen saturation, perfusion indices, and photoplethysmography data. Data aggregation in our system is automated and all data files are coded with unique study identifiers to facilitate research purposes. Using this system, we have collected data from 190 neonates, 130 presumably without and 60 with congenital heart disease, in total comprising 1665 min of information. From these data, we are able to extract non-invasive perfusion features such as perfusion index, radiofemoral delay, and slope of systolic rise or diastolic fall. This data collection and waveform analysis is relatively inexpensive and can be used to enhance future CCHD screening algorithms.
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ISSN:2059-8661
2059-8661
DOI:10.1017/cts.2020.550