New Study Validates Non-Invasive Prediction of Carbon Dioxide Retention in Neonates Using Etiometry’s Clinical Intelligence Platform
News and Press Releases
September 9, 2025 – BOSTON – A newly published study in the Journal of Perinatology has validated a breakthrough predictive tool, IVCO2, that accurately estimates the risk of carbon dioxide (CO2) retention in neonates using Etiometry’s Clinical Intelligence Platform. Unlike traditional monitoring methods that rely on skin sensors and can compromise the skin integrity of fragile neonatal patients, this novel approach provides continuous, non-invasive calculated estimates alongside existing monitoring, without requiring additional skin-based sensors
The study, titled Validation of a Novel Bayesian Predictive Algorithm for Detection of Carbon Dioxide Retention Using Retrospective Neonatal ICU Data, evaluated more than 1,000 arterial blood gas measurements from two Level IV NICUs. The IVCO2 index, developed using retrospective data, showed strong correlation with hypercapnia risk, achieving AUC values of 0.87 and 0.90 for PaCO2 thresholds of 50 mmHg and 60 mmHg, respectively.
By leveraging a broad set of existing physiologic measurements, such as SpO2, respiratory rate, tidal volume, heart rate, and relevant laboratory results, IVCO2 continuously calculates the probability of CO2 retention, providing care teams with information to support assessment of ventilation adequacy, as an adjunct to other clinical measurements.. This allows for earlier detection and proactive clinical decision-making, without the need for skin-based sensors that may harm vulnerable neonates.
“This technology could be a significant step forward in neonatal care,” said Dr. Zachary A. Vesoulis, a neonatologist at Washington University School of Medicine in St. Louis and senior author of the study. “The study indicates that the ability to monitor for CO2 retention without disrupting the skin barrier offers a safer and more sustainable option for managing ventilation in fragile
infants.”
The validation cohort of 180 neonates confirmed the algorithm’s strong performance across diverse clinical conditions and monitoring setups. Patients with minimum IVCO2 index values (<1) had nearly a six-fold reduction in the risk of hypercapnia at the >50mmHg threshold and greater than a ten-fold reduction at the >60 mmHg threshold. Conversely, those with maximum scores (>99) had a five-fold reduction in the risk of normocapnia at the >50 mmHg threshold and a greater than three-fold reduction in the risk of hypercapnia at the >60 mmHg threshold.These findings highlight the value of analytics tools to improve patient monitoring, and represent a promising advance that could enable earlier detection of ventilation inadequacy without requiring additional sensors or blood sampling.
This study underscores Etiometry’s continued commitment to advancing neonatal and critical care through intelligent, data-driven tools that enable clinicians to intervene earlier and more confidently.
Read the full study here: https://doi.org/10.1038/s41372-025-02369-z
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About Etiometry
Founded in 2010, Etiometry is a leader in clinical decision-support software designed to help clinicians in intensive care units make data-driven, proactive decisions. By leveraging advanced analytics and AI-powered insights, the company empowers care teams to detect subtle changes in patient conditions, prevent complications, and improve recovery times.
Etiometry has received ten FDA clearances and is trusted by leading healthcare institutions worldwide, including top-ranked academic medical centers and pediatric hospitals. The company is committed to advancing patient safety, improving clinical efficiency, and lowering the cost of care through smarter data utilization.
To learn more, visit www.etiometry.com.
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