Literature DB >> 8688265

Heart rate variability in patients recovering from general anaesthesia.

N Ireland1, J Meagher, J W Sleigh, J D Henderson.   

Abstract

We studied heart rate variability (HRV) using spectral analysis techniques in 58 adult patients recovering from general anaesthesia. The aim was to discover how HRV was affected by a variety of common preoperative, intraoperative and postoperative factors. ECG, respiration, level of consciousness, nausea, pain and arterial pressure were recorded during the first hour of recovery from general anaesthesia. HRV was found to decrease with increased weight, age, complexity of operation, use of reversal agents for neuromuscular block and preoperative beta-block. These effects were not mediated by changes in respiration. HRV was unaffected by administration of morphine. The level of nausea or pain had no effect on HRV except that pain decreased the relative ratio of high frequency to low frequency power within the power spectrum. In the group of patients that did not receive reversal agents, there was an abrupt increase in HRV when patients became responsive to verbal command.

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Year:  1996        PMID: 8688265     DOI: 10.1093/bja/76.5.657

Source DB:  PubMed          Journal:  Br J Anaesth        ISSN: 0007-0912            Impact factor:   9.166


  5 in total

1.  Pediatric anesthesia monitoring with the help of EEG and ECG.

Authors:  L Senhadji; G Carrault; H Gauvrit; E Wodey; P Pladys; F Carré
Journal:  Acta Biotheor       Date:  2000-12       Impact factor: 1.774

2.  Assessment of short-term blood pressure variability in anesthetized children: a comparative study between intraarterial and finger blood pressure.

Authors:  I Constant; D Laude; J L Elghozi; I Murat
Journal:  J Clin Monit Comput       Date:  1999-05       Impact factor: 2.502

3.  Spectral Gini Index for Quantifying the Depth of Consciousness.

Authors:  Kyung-Jin You; Gyu-Jeong Noh; Hyun-Chool Shin
Journal:  Comput Intell Neurosci       Date:  2016-10-20

4.  Novel Methods for Measuring Depth of Anesthesia by Quantifying Dominant Information Flow in Multichannel EEGs.

Authors:  Kab-Mun Cha; Byung-Moon Choi; Gyu-Jeong Noh; Hyun-Chool Shin
Journal:  Comput Intell Neurosci       Date:  2017-03-16

5.  Heart rate variability-derived features based on deep neural network for distinguishing different anaesthesia states.

Authors:  Jian Zhan; Zhuo-Xi Wu; Zhen-Xin Duan; Gui-Ying Yang; Zhi-Yong Du; Xiao-Hang Bao; Hong Li
Journal:  BMC Anesthesiol       Date:  2021-03-02       Impact factor: 2.217

  5 in total

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