Intra-tidal $ PaO_{2} $ oscillations associated with mechanical ventilation: a pilot study to identify discrete morphologies in a porcine model

Background Within-breath oscillations in arterial oxygen tension ($ PaO_{2} $) can be detected using fast responding intra-arterial oxygen sensors in animal models. These $ PaO_{2} $ signals, which rise in inspiration and fall in expiration, may represent cyclical recruitment/derecruitment and, therefore, a potential clinical monitor to allow titration of ventilator settings in lung injury. However, in hypovolaemia models, these oscillations have the potential to become inverted, such that they decline, rather than rise, in inspiration. This inversion suggests multiple aetiologies may underlie these oscillations. A correct interpretation of the various $ PaO_{2} $ oscillation morphologies is essential to translate this signal into a monitoring tool for clinical practice. We present a pilot study to demonstrate the feasibility of a new analysis method to identify these morphologies. Methods Seven domestic pigs (average weight 31.1 kg) were studied under general anaesthesia with muscle relaxation and mechanical ventilation. Three underwent saline-lavage lung injury and four were uninjured. Variations in PEEP, tidal volume and presence/absence of lung injury were used to induce different morphologies of $ PaO_{2} $ oscillation. Functional principal component analysis and k-means clustering were employed to separate $ PaO_{2} $ oscillations into distinct morphologies, and the cardiorespiratory physiology associated with these $ PaO_{2} $ morphologies was compared. Results $ PaO_{2} $ oscillations from 73 ventilatory conditions were included. Five functional principal components were sufficient to explain ≥ 95% of the variance of the recorded $ PaO_{2} $ signals. From these, five unique morphologies of $ PaO_{2} $ oscillation were identified, ranging from those which increased in inspiration and decreased in expiration, through to those which decreased in inspiration and increased in expiration. This progression was associated with the estimates of the first functional principal component (P < 0.001, R2 = 0.88). Intermediate morphologies demonstrated waveforms with two peaks and troughs per breath. The progression towards inverted oscillations was associated with increased pulse pressure variation (P = 0.03). Conclusions Functional principal component analysis and k-means clustering are appropriate to identify unique morphologies of $ PaO_{2} $ waveform associated with distinct cardiorespiratory physiology. We demonstrated novel intermediate morphologies of $ PaO_{2} $ waveform, which may represent a development of zone 2 physiologies within the lung. Future studies of $ PaO_{2} $ oscillations and modelling should aim to understand the aetiologies of these morphologies..

Medienart:	E-Artikel

Erscheinungsjahr:	2023
Erschienen:	2023

Enthalten in:	Zur Gesamtaufnahme - volume:11
Enthalten in:	Intensive Care Medicine Experimental - 11(2023), 1 vom: 06. Sept.

Sprache:	Englisch

Beteiligte Personen:	Cronin, John N. [VerfasserIn] Crockett, Douglas C. [VerfasserIn] Perchiazzi, Gaetano [VerfasserIn] Farmery, Andrew D. [VerfasserIn] Camporota, Luigi [VerfasserIn] Formenti, Federico [VerfasserIn]

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Themen:	Acute respiratory distress syndrome Arterial oxygen tension Functional principal component analysis Mechanical ventilation Oxygen oscillations

Anmerkungen:	© The Author(s) 2023

doi:	10.1186/s40635-023-00544-0

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PPN (Katalog-ID):	SPR053004140