Authors: Marianna Laviola, Jakub Ráfl, Martin Rozanek, Petr Kudrna and Karel Roubík

Citation

Laviola, M., Rafl, J., Rozanek, M., Kudrna, P. and Roubik, K., 2015, August. Models of a PaO2 course during a stepwise change of Continuous Distending Pressure in HFOV. In Mathematics and Computers in Sciences and in Industry (MCSI), 2015 Second International Conference on (pp. 66-71). IEEE.

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Published in Mathematics and Computers in Sciences and in Industry (MCSI), Second International Conference on, 2015, IEEE.

Abstract

Acute respiratory distress syndrome (ARDS) is an acute severe lung disease commonly encountered in intensive care units. High-frequency oscillatory ventilation (HFOV) could offer effective lung protective ventilation by delivering very low tidal volumes around constant relatively higher continuous distending pressure (CDP) at frequencies of 3 to 15 Hz. The rapid ventilatory rate can provide adequate gas exchange, the higher CDP and lower tidal volumes limit alveolar derecruitment and overdistension, respectively. Optimization of CDP is not an easy task and it is titrated empirically in the clinical practice. The aim of this study is to investigate if the level of CDP affects the shape of the PaO2 response of the organism to the CDP stepwise changes. Ten pigs were used in this study. In order to mimic ARDS, surfactant deficiency was induced by a double or triple lung lavage normal saline containing nonionic surfactant. When normocapnia was reached, the animals were switched to HFOV with FIO2=1.0. Every 10 minutes, CDP was stepwise increased by 2 cmH2O from 17±4 cmH2O, but when an animal did not tolerate low CDP levels after the lung lavage, CDP was rapidly increased in order to prevent further deterioration in severe hypoxia. The mean maximum CDP was 43±5 cmH2O and then CDP was stepwise decreased by 2 cmH2O to its initial value. In order to calculate the shape that PaO2 course follows during the CDP stepwise, for each CDP step performed, we fitted PaO2 with a one-term power model as follows: y = a·x b, where x is the length of CDP in terms of time, a is the amplitude of the model, exponents b reflects the shape of the model. PaO2 course can follow several shapes modelled by constant, root, linear and quadratic functions. For values of PaO2<200 mmHg, PaO2 course follows shapes modelled mainly by root, but also, linear and quadratic functions. For values of PaO2>200mmHg PaO2 course follows a shape modelled exclusively by a root function. It is not possible to describe a relationship between the shape of the PaO2 course and the values of CDP. When alveoli are not recruited at all or have not been fully recruited yet oxygenation is more sensitive to changes in lung volume and aeration and thus,PaO2 grows or drops rapidly following linear and/or quadratic functions. Instead of, when alveoli are open and recruited changes in PaO2 are less sensitive to relatively minor changes in lung aeration and thus, PaO2 grows and drops slower following only root function.The CDP level does not affect the response of organism in terms of shape change of PaO2, probably due to the fact that the recruitment occurs at different values in each pig.

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