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Published in: Journal of Clinical Monitoring and Computing 5/2020

01-10-2020 | Affective Disorder | Original Research

Pre-apneic capnography waveform abnormalities during procedural sedation and analgesia

Authors: Aaron Conway, Peter Collins, Kristina Chang, Sebastian Mafeld, Joanna Sutherland, James Fingleton, Matteo Parotto

Published in: Journal of Clinical Monitoring and Computing | Issue 5/2020

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Abstract

Capnography monitoring is recommended for use during procedural sedation. This study examined associations between capnography waveform abnormalities and the onset of apnea. Capnography waveforms from a sample of 102 participants undergoing moderate procedural sedation with bolus doses of midazolam and fentanyl were analyzed using a mixed effects Cox model. Patients were at increased risk of apnea (classified as end-tidal carbon dioxide concentration of zero) while demonstrating a capnography waveform abnormality classified as hypopnea (more than 10% increase or decrease from baseline end-tidal carbon dioxide concentration) (Hazard Ratio 2.14; 95% CI 1.75 to 2.62). Risk of apnea was not increased during capnography waveform abnormalities classified as bradypnea (capnography-derived respiratory rate less than 8 breaths/min) (Hazard Ratio 0.64; 95% CI 0.33 to 1.25). These estimates were similar when apneic episodes were defined as only those that lasted more than 20 s duration. Deciphering which capnography waveform abnormalities should promote intervention (and therefore alarms to signal the event to clinicians) from those that do not is an essential step towards successful implementation of this technology into practice. Our results indicate that using information about the history of previous capnography waveform abnormalities may be a promising solution to assist prediction of apneic episodes.
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Metadata
Title
Pre-apneic capnography waveform abnormalities during procedural sedation and analgesia
Authors
Aaron Conway
Peter Collins
Kristina Chang
Sebastian Mafeld
Joanna Sutherland
James Fingleton
Matteo Parotto
Publication date
01-10-2020
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 5/2020
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-019-00391-z

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