The discriminatory value of cardiorespiratory interactions in distinguishing awake from anaesthetised states: a randomised observational study
Summary Depth of anaesthesia monitors usually analyse cerebral function with or without other physiological signals; non‐invasive monitoring of the measured cardiorespiratory signals alone would offer a simple, practical alternative. We aimed to investigate whether such signals, analysed with novel,...
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Published in | Anaesthesia Vol. 70; no. 12; pp. 1356 - 1368 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Blackwell Publishing Ltd
01.12.2015
John Wiley and Sons Inc |
Subjects | |
Online Access | Get full text |
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Summary: | Summary
Depth of anaesthesia monitors usually analyse cerebral function with or without other physiological signals; non‐invasive monitoring of the measured cardiorespiratory signals alone would offer a simple, practical alternative. We aimed to investigate whether such signals, analysed with novel, non‐linear dynamic methods, would distinguish between the awake and anaesthetised states. We recorded ECG, respiration, skin temperature, pulse and skin conductivity before and during general anaesthesia in 27 subjects in good cardiovascular health, randomly allocated to receive propofol or sevoflurane. Mean values, variability and dynamic interactions were determined. Respiratory rate (p = 0.0002), skin conductivity (p = 0.03) and skin temperature (p = 0.00006) changed with sevoflurane, and skin temperature (p = 0.0005) with propofol. Pulse transit time increased by 17% with sevoflurane (p = 0.02) and 11% with propofol (p = 0.007). Sevoflurane reduced the wavelet energy of heart (p = 0.0004) and respiratory (p = 0.02) rate variability at all frequencies, whereas propofol decreased only the heart rate variability below 0.021 Hz (p < 0.05). The phase coherence was reduced by both agents at frequencies below 0.145 Hz (p < 0.05), whereas the cardiorespiratory synchronisation time was increased (p < 0.05). A classification analysis based on an optimal set of discriminatory parameters distinguished with 95% success between the awake and anaesthetised states. We suggest that these results can contribute to the design of new monitors of anaesthetic depth based on cardiovascular signals alone. |
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Bibliography: | http://www.anaesthesiacorrespondence.com You can respond to this article at Correction: Tables S1‐S2 and Figures S1‐S2 were added after online publication on 22 October 2015. SourceType-Scholarly Journals-1 ObjectType-Feature-4 ObjectType-Undefined-1 ObjectType-News-2 content type line 23 ObjectType-Article-3 You can respond to this article at http://www.anaesthesiacorrespondence.com |
ISSN: | 0003-2409 1365-2044 |
DOI: | 10.1111/anae.13208 |