Noninvasive Arterial CO2 Estimation for Neonatal Ventilation Using Gated Recurrent Neural Networks in the Preterm Ovine Model.

Bibliographic Details
Title:	Noninvasive Arterial CO2 Estimation for Neonatal Ventilation Using Gated Recurrent Neural Networks in the Preterm Ovine Model.
Authors:	Pfannschmidt V, Aydin Y, Hutten M, Kowalewski S, Schoberer M, Stollenwerk A
Source:	Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2025 Jul; Vol. 2025, pp. 1-4.
Publication Type:	Journal Article
Language:	English
Journal Info:	Publisher: [IEEE] Country of Publication: United States NLM ID: 101763872 Publication Model: Print Cited Medium: Internet ISSN: 2694-0604 (Electronic) Linking ISSN: 23757477 NLM ISO Abbreviation: Annu Int Conf IEEE Eng Med Biol Soc Subsets: MEDLINE
Imprint Name(s):	Original Publication: [Piscataway, NJ] : [IEEE], [2007]-
MeSH Terms:	Carbon Dioxide/blood , Neural Networks, Computer , Respiration, Artificial*, Blood Gas Analysis/methods ; Animals ; Sheep ; Animals, Newborn ; Arteries ; Recurrent Neural Networks
Abstract:	We present two Gated Recurrent Unit (GRU) neural networks for estimating the arterial partial pressure of carbon dioxide (PaCO2) in mechanically ventilated neonates, using time series data of the end-tidal partial pressure of carbon dioxide (PetCO2) and noninvasive respiratory and vital measurements. To train and validate these models, we use secondary data of preterm lambs. 1,182 arterial blood gas analyses (ABGs) from 58 animals are included. We compare our approaches to two clinical methods: (i) using PetCO2 as a surrogate for PaCO2 and (ii) adjusting PetCO2 with a constant offset based on invasive ABG analysis. Estimation errors are evaluated by comparing model outputs with PaCO2 measurements from ABGs via Bland-Altman analyses. Estimation by PetCO2 and the GRU model using a univariate time series of PetCO2 results the lowest accuracy. The invasive PetCO2+Offset method shows improvement, while the highest accuracy is achieved with a GRU model that incorporates a noninvasive multivariate time series of PetCO2 along with vital and respiratory measurements.
Substance Nomenclature:	142M471B3J (Carbon Dioxide)
Entry Date(s):	Date Created: 20251203 Date Completed: 20251203 Latest Revision: 20251203
Update Code:	20260130
DOI:	10.1109/EMBC58623.2025.11253346
PMID:	41336271
Database:	MEDLINE

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