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Intra-breath arterial oxygen oscillations detected by a fast oxygen sensor in an animal model of acute respiratory distress syndrome

Research output: Contribution to journalArticle

F Formenti, Rongsheng Chen, H McPeak, P J Murison, M Matejovic, Clive E W Hahn, A D Farmery

Original languageEnglish
Pages (from-to)683-8
Number of pages6
JournalBritish Journal of Anaesthesia
Volume114
Issue number4
Early online date28 Jan 2015
DOIs
E-pub ahead of print28 Jan 2015
PublishedApr 2015

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Abstract

BACKGROUND: There is considerable interest in oxygen partial pressure (Po2) monitoring in physiology, and in tracking Po2 changes dynamically when it varies rapidly. For example, arterial Po2 ([Formula: see text]) can vary within the respiratory cycle in cyclical atelectasis (CA), where [Formula: see text] is thought to increase and decrease during inspiration and expiration, respectively. A sensor that detects these [Formula: see text] oscillations could become a useful diagnostic tool of CA during acute respiratory distress syndrome (ARDS).

METHODS: We developed a fibreoptic Po2 sensor (<200 µm diameter), suitable for human use, that has a fast response time, and can measure Po2 continuously in blood. By altering the inspired fraction of oxygen ([Formula: see text]) from 21 to 100% in four healthy animal models, we determined the linearity of the sensor's signal over a wide range of [Formula: see text] values in vivo. We also hypothesized that the sensor could measure rapid intra-breath [Formula: see text] oscillations in a large animal model of ARDS.

RESULTS: In the healthy animal models, [Formula: see text] responses to changes in [Formula: see text] were in agreement with conventional intermittent blood-gas analysis (n=39) for a wide range of [Formula: see text] values, from 10 to 73 kPa. In the animal lavage model of CA, the sensor detected [Formula: see text] oscillations, also at clinically relevant [Formula: see text] levels close to 9 kPa.

CONCLUSIONS: We conclude that these fibreoptic [Formula: see text] sensors have the potential to become a diagnostic tool for CA in ARDS.

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