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Research Article
  • Depth of Anesthesia as a Risk Factor for Perioperative Morbidity, Argyro Petsiti, Vassilios Tassoudis, George Vretzakis, Dimitrios Zacharoulis, Konstantinos Tepetes, Georgia Ganeli, and Menelaos Karanikolas
    Anesthesiology Research and Practice
    Research Article (7 pages), Article ID 829151, Volume 2015 (2015)
    Published 2 June 2015
Anesthesiology Research and Practice
Volume 2015, Article ID 301291, 2 pages
http://dx.doi.org/10.1155/2015/301291
Letter to the Editor

Comment on “Depth of Anesthesia as a Risk Factor for Perioperative Morbidity”

Department of Anesthesia, Endoscopy and Cardiology, Istituto Nazionale Tumori ‘Fondazione G. Pascale’, IRCCS, 80100 Naples, Italy

Received 12 September 2015; Accepted 3 November 2015

Academic Editor: Yukio Hayashi

Copyright © 2015 Marco Cascella. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Petsiti and colleagues recent study on causal relationship between depth of anesthesia and perioperative morbidity [1] is an attractive opportunity to discuss a significant topic: what do we know about Deep Hypnotic Status (DHS) during general anesthesia (GA) and how can we recognize it? In truth, though significant steps have been taken by neuroscience and the knowledge of pharmacodynamics has been fine-tuned, we do not have a comprehensive view of what really happens to the brain during GA. The real problem is driving the anesthesia in a middle earth, furthest from both the burst suppression and sudden emergencies. Thus, if we cannot define the exact anesthesia level of our patient, how can we establish a correlation between DHS and postoperative complications and morbidity? While the authors correctly cited previous studies on the topic, nevertheless we meet Sigl [2] among the authors of one of these references. It is not a big surprise for the scholars of brain monitoring because he was, along with Chamoun, the first to describe the bispectral (BIS) technology in 1994 [3].

It is questionable whether BIS monitor exactly expresses the depth of anesthesia (DOA). However, it may be impossible to measure the real DOA by the simple method accepted by all anesthesiologists. Thus, BIS monitor is regarded as the most reliable and clinically available monitoring for the DOA, although its efficacy is controversial [4].

An anesthesia status not sufficiently deep may cause events of AA; however according to Petsiti et al. a deep hypnotic time (DHT) is a new significant factor associated with postoperative outcome [1]. Petsiti et al. defined DHT as the cumulative period of BIS index values < 45 [1], in line with the previous observations of Lindholm et al. [5]. While single data are not indicative of the anesthesia status, the variable time adds more power to the BIS value. This is the most important issue of the paper by Petsiti et al. because it shows the efficacy of DHT as a risk factor for perioperative mortality, even if the BIS monitoring system is questionable [1].

BIS monitor was the first electroencephalography- (EEG-) based DOA monitor. It is the most widely used system to assess the monitoring of DOA; nevertheless during the last 15–20 years a number of EEG-based technologies have become commercially available. Although several algorithms have been used for patenting brain monitors and many indices are used as references for monitoring the DOA at the moment, there is no device to assess the exact level of anesthesia. Jensen and colleagues have long studied level of consciousness during GA. They published on the detrended fluctuation analysis of EEG, proponing several indexes in order to characterize the patient state (awake, sedated, and anesthetized states) [6]. Nevertheless, as stated by them, these indices are able to detect the loss of consciousness but not to assess the exact level of anesthesia. In the meantime, others have proposed complex algorithms combining EEG analysis and no EEG parameters. Schneider et al. [7] studied a combination of standard monitoring, EEG parameters, and patient and drug information demonstrating that it is possible to separate the different anesthetic levels. However, their pattern is a complex analysis with a late construction which is difficult to apply in order to immediately recognize intraoperative awakening, in particular under neuromuscular blockade. They concluded that “additional studies are required to validate results of the current study.” Recently, the authors of the Michigan Awareness Control Study [8] concluded that they were not able to find an alert threshold for both anesthetic drugs and BIS values and there is the necessity for an individualized anesthetic strategy.

Fortunately, as we are writing the progress of science does not stop. Thus, we are witnessing a rapid evolution of the brain monitoring EEG-based techniques. The studies of Boly et al. [9] on the spectral EEG changes after propofol administration are very important, and Purdon et al. [10] published their fascinating research, explaining that EEG pattern (and its changing) is indicative in real time of the patient transaction from consciousness to the anesthesia status. We hope that these technologies are perfected and soon on a large scale distributed to permanently solve the AA problem and cut down the postoperative complications due to DHT. At the same time the attempts as those of Petsiti are much appreciated.

Conflict of Interests

The author declares that there is no conflict of interests regarding the publication of this paper.

References

  1. A. Petsiti, V. Tassoudis, G. Vretzakis et al., “Depth of anesthesia as a risk factor for perioperative morbidity,” Anesthesiology Research and Practice, vol. 2015, Article ID 829151, 7 pages, 2015. View at Publisher · View at Google Scholar
  2. T. G. Monk, V. Saini, B. C. Weldon, and J. C. Sigl, “Anesthetic management and one-year mortality after noncardiac surgery,” Anesthesia and Analgesia, vol. 100, no. 1, pp. 4–10, 2005. View at Publisher · View at Google Scholar · View at Scopus
  3. J. C. Sigl and N. G. Chamoun, “An introduction to bispectral analysis for the electroencephalogram,” Journal of Clinical Monitoring, vol. 10, no. 6, pp. 392–404, 1994. View at Publisher · View at Google Scholar · View at Scopus
  4. J. Lang, “Awakening,” in The Best American Science and Nature Writing 2014, D. Blum and T. Folger, Eds., p. 181, Houghton Mifflin Harcourt, Boston, Mass, USA, 2014. View at Google Scholar
  5. M.-L. Lindholm, S. Träff, F. Granath et al., “Mortality within 2 years after surgery in relation to low intraoperative bispectral index values and preexisting malignant disease,” Anesthesia and Analgesia, vol. 108, no. 2, pp. 508–512, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. E. W. Jensen, J. F. Valencia, A. López et al., “Monitoring hypnotic effect and nociception with two EEG-derived indices, qCON and qNOX, during general anaesthesia,” Acta Anaesthesiologica Scandinavica, vol. 58, no. 8, pp. 933–941, 2014. View at Publisher · View at Google Scholar
  7. G. Schneider, D. Jordan, G. Schwarz et al., “Monitoring depth of anesthesia utilizing a combination of electroencephalographic and standard measures,” Anesthesiology, vol. 120, no. 4, pp. 819–828, 2014. View at Google Scholar
  8. A. M. Shanks, M. S. Avidan, S. Kheterpal et al., “Alerting thresholds for the prevention of intraoperative awareness with explicit recall: a secondary analysis of the Michigan Awareness Control Study,” European Journal of Anaesthesiology, vol. 32, no. 5, pp. 346–353, 2015. View at Publisher · View at Google Scholar
  9. M. Boly, R. Moran, M. Murphy et al., “Connectivity changes underlying spectral EEG changes during propofol-induced loss of consciousness,” Journal of Neuroscience, vol. 32, no. 20, pp. 7082–7090, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. P. L. Purdon, E. T. Pierce, E. A. Mukamel et al., “Electroencephalogram signatures of loss and recovery of consciousness from propofol,” Proceedings of the National Academy of Sciences of the United States of America, vol. 110, no. 12, pp. E1142–E1151, 2013. View at Publisher · View at Google Scholar · View at Scopus