• J Clin Monit Comput · Dec 2024

    Noninvasive estimation of PaCO2 from volumetric capnography in animals with injured lungs: an Artificial Intelligence approach.

    • Gerardo Tusman, Adriana G Scandurra, Stephan H Böhm, Noelia I Echeverría, Gustavo Meschino, P Kremeier, and Fernando Suarez Sipmann.
    • Department of Anesthesiology, Hospital Privado de Comunidad, Mar del Plata, Buenos Aires, 7600, Argentina. gtusman@hotmail.com.
    • J Clin Monit Comput. 2024 Dec 26.

    AbstractTo investigate the feasibility of non-invasively estimating the arterial partial pressure of carbon dioxide (PaCO2) using a computational Adaptive Neuro-Fuzzy Inference System (ANFIS) model fed by noninvasive volumetric capnography (VCap) parameters. In 14 lung-lavaged pigs, we continuously measured PaCO2 with an optical intravascular catheter and VCap on a breath-by-breath basis. Animals were mechanically ventilated with fixed settings and subjected to 0 to 22 cmH2O of positive end-expiratory pressure steps. The resultant 8599 pairs of data points - one PaCO2 value matched with twelve Vcap and ventilatory parameters derived in one breath - fed the ANFIS model. The data was separated into 7370 data points for training the model (85%) and 1229 for testing (15%). The ANFIS analysis was repeated 10 independent times, randomly mixing the total data points. Bland-Altman plot (accuracy and precision), root mean square error (quality of prediction) and four-quadrant and polar plots concordance indexes (trending ability) between reference and estimated PaCO2 were analyzed. The Bland-Altman plot performed in 10 independent tested ANFIS models showed a mean bias between reference and estimated PaCO2 of 0.03 ± 0.03 mmHg, with limits of agreement of 2.25 ± 0.42 mmHg, and a root mean square error of 1.15 ± 0.06 mmHg. A good trending ability was confirmed by four quadrant and polar plots concordance indexes of 95.5% and 94.3%, respectively. In an animal lung injury model, the Adaptive Neuro-Fuzzy Inference System model fed by noninvasive volumetric capnography parameters can estimate PaCO2 with high accuracy, acceptable precision, and good trending ability.© 2024. The Author(s), under exclusive licence to Springer Nature B.V.

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