Standardization of Transthoracic Impedance Values for Estimating Heart Failure and its Utility
Daisuke Nose, Yuta Ibayashi, Tadaaki Arimura, Tomokazu Matsui, Yuki Matsuda, Takuya Otsuka, Keiichi Yasumoto, Masahiro Sugimoto, Shin-Ichiro Miura: “Standardization of Transthoracic Impedance Values for Estimating Heart Failure and its Utility,”
European Heart Journal, Vol.45, No.Supplement_1, p.ehae666.3453, 2024.
Abstract
Background: The use of intrathoracic impedance for examining pleural effusion in heart failure patients has been explored previously. However, due to concerns about its accuracy and complexity, transthoracic impedance values have had limitations in quantifying extravascular lung water. Our dual objectives were to clarify the relationship between intrathoracic conditions and percutaneous transthoracic impedance values, and to establish a basic model for a new machine learning-based estimation system for assessing intrathoracic conditions in patients with heart failure. Methods: First, we developed a live porcine congested lung model that induced pleural effusion by substantial fluid loading, and then longitudinally evaluated its correlation with percutaneous transthoracic impedance values. Second, we conducted multi-frequency bioelectrical impedance analysis to simultaneously collect electrical, physical, and hematological data from 63 hospitalized heart failure patients and 82 healthy volunteers. Results: In the porcine model, pleural effusion correlated with a concurrent decrease in SpO2 and a gradual decrease in impedance. We indexed and generated features from the measured values and developed an intrathoracic estimation model based on electrical measurements and clinical findings using a decision tree-based machine learning approach. Among the 286 features collected per individual, the model used 16 features. Notably, the model demonstrated high accuracy in discriminating patients with pleural effusion, achieving an AUC of 0.905 (95% CI: 0.870-0.940) in cross-validation, significantly outperforming the conventional frequency-based method. Conclusions: Transthoracic impedance values, when indexed, reflect intrathoracic conditions and improve estimation. Our results highlighted the potential of machine learning and thoracic impedance measurement for accurate estimation of pleural effusion. This approach provides an effective means of assessing intrathoracic conditions.
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@inproceedings{bib:nose_heartFailure_EHJ2024,
author={Nose, Daisuke and Ibayashi, Yuta and Arimura, Tadaaki and Matsui, Tomokazu and Matsuda, Yuki and Otsuka, Takuya and Yasumoto, Keiichi and Sugimoto, Masahiro and Miura, Shin-Ichiro},
title={Standardization of transthoracic impedance values for estimating heart failure and its utility},
journal={European Heart Journal},
volume={45},
number={Supplement_1},
year={2024},
pages={ehae666.3453},
doi={10.1093/eurheartj/ehae666.3453}
}
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