A Parameter Identification Approach towards Hemodynamics based on Capnography

Authors

DOI:

https://doi.org/10.31247/agnj.v2iS1.53

Abstract

Research question

Pulse detection decisions during cardiopulmonary resuscitation (CPR) are commonly augmented by end-tidal CO2-concentration (etCO2) levels and trend as etCO2 is a surrogate measure of systemic blood flow during (CPR)1. However, ventilatory and circulatory parameters influence the interpretability of etCO2 heavily. Recently developed methods of continuous cardiac output measurement based on capnography are not applicable during CPR due to the required controlled ventilation settings2. In this study, a parameter identification for a model of CO2 transport during resuscitation is used to estimate cardiac output based on capnography and tidal flow.

Methodology

After development of a compartmental ordinary differential equation (ODE) model to represent CO2 transport during CPR, parameters such as airway dead space and the level of systemic perfusion are estimated by a multishooting parameter identification approach3. To evaluate the method, tests are conducted on experimental data from a porcine model (approved by an ethics committee vote of the Austrian Federal Ministry of Education, Science and Research (GZ: 2021-0.895.386)). The estimated level of systemic perfusion is compared visually to invasively measured mean arterial pressure due to a lack of continuous cardiac output measurements as a ground truth.

Results

For exemplary data from a female pig (weight 50.4 kg), airway resistance was estimated to 20.8 hPa s /L, compliance: 25.2 mL/hPa, and dead space: 109 mL. Changes in cardiac output can be identified qualitatively as shown in Fig. 1.

Conclusion

A validated, simple ODE model for CO2 extraction during CPR could contribute quantifying the impact of ventilatory parameters on etCO2 and elucidate CO2 production, storage and transport during cardiac arrest. Assumptions on CO2 production during cardiac arrest and redistribution in the body, and the lacking cardiac output measurements complicate the analysis.

 

Conflicts of Interest

All authors have no conflict of interest to declare.

References

Soar J, et al., European resuscitation council guidelines 2021: Adult advanced life support. Resuscitation 2021;161:115–151. https://doi.org/10.1016/j.resuscitation.2021.02.010.

Peyton PJ, Kozub M. Performance of a second generation pulmonary capnotracking system for continuous monitoring of cardiac output. Journal of clinical monitoring and computing 2018; 32:1057-1064. https://doi.org/10.1007/s10877-018-0110-y.

vanDomselaar B, Hemker, PW. Nonlinear parameter estimation in initial value problems. Stichting Mathematisch Centrum. Numerieke Wiskunde 1975; no. NW 18/75.

Published

2024-04-04

How to Cite

A Parameter Identification Approach towards Hemodynamics based on Capnography. (2024). AGN Journal, 2(S1). https://doi.org/10.31247/agnj.v2iS1.53

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