Intensive Care Medicine

, Volume 33, Issue 1, pp 133–136 | Cite as

Entropy is more resistant to artifacts than bispectral index in brain-dead organ donors

  • Johanna Wennervirta
  • Tapani Salmi
  • Markku Hynynen
  • Arvi Yli-Hankala
  • Anna-Maria Koivusalo
  • Mark Van Gils
  • Reino Pöyhiä
  • Anne Vakkuri
Brief Report



To evaluate the usefulness of entropy and the bispectral index (BIS) in brain-dead subjects.

Design and setting

A prospective, open, nonselective, observational study in the university hospital.

Patients and participants

16 brain-dead organ donors.


Time-domain electroencephalography (EEG), spectral entropy of the EEG, and BIS were recorded during solid organ harvest.

Measurements and results

State entropy differed significantly from 0 (isoelectric EEG) 28%, response entropy 29%, and BIS 68% of the total recorded time. The median values during the operation were state entropy 0.0, response entropy 0.0, and BIS 3.0. In four of 16 organ donors studied the EEG was not isoelectric, and nonreactive rhythmic activity was noted in time-domain EEG. After excluding the results from subjects with persistent residual EEG activity state entropy, response entropy, and BIS values differed from zero 17%, 18%, and 62% of the recorded time, respectively. Median values were 0.0, 0.0, and 2.0 for state entropy, response entropy, and BIS, respectively. The highest index values in entropy and BIS monitoring were recorded without neuromuscular blockade. The main sources of artifacts were electrocauterization, 50-Hz artifact, handling of the donor, ballistocardiography, electromyography, and electrocardiography.


Both entropy and BIS showed nonzero values due to artifacts after brain death diagnosis. BIS was more liable to artifacts than entropy. Neither of these indices are diagnostic tools, and care should be taken when interpreting EEG and EEG-derived indices in the evaluation of brain death.


Electroencephalography Brain death Entropy Bispectral Index 


  1. 1.
    Gan TJ, Glass PS, Windsor A, Payne F, Rosow C, Sebel P, Manberg P (1997) Bispectral index monitoring allows faster emergence and improved recovery from propofol, alfentanil, and nitrous oxide anesthesia. BIS Utility Study Group. Anesthesiology 87:808–815PubMedCrossRefGoogle Scholar
  2. 2.
    Vivien B, Paqueron X, Le Cosquer P, Langeron O, Coriat P, Riou B (2002) Detection of BD onset using the bispectral index in severely comatose patients. Intensive Care Med 28:419–425PubMedCrossRefGoogle Scholar
  3. 3.
    Vivien B, Di Maria S, Ouattara A, Langeron O, Coriat P, Riou B (2003) Overestimation of Bispectral Index in sedated intensive care unit patients revealed by administration of muscle relaxant. Anesthesiology 99:9–17PubMedCrossRefGoogle Scholar
  4. 4.
    Inoue S, Kawaguchi M, Sasaoka N, Hirai K, Furuya H (2006) Effects of neuromuscular block on systemic and cerebral hemodynamics and bispectral index during moderate or deep sedation in critically ill patients. Intensive Care Med 32:391–397PubMedCrossRefGoogle Scholar
  5. 5.
    Freye E, Levy JV (2005) Cerebral monitoring in the operating room and the intensive care unit: an introductory for the clinician and a guide for the novice wanting to open a window to the brain. I. The electroencephalogram. J Clin Monit Comput 19:1–76PubMedCrossRefGoogle Scholar
  6. 6.
    Goncharova I, McFarland DJ, Vaughan TM, Wolpaw JR (2003) EMG contamination of EEG: spectral and topographical characteristics. Clin Neurophysiol 114:1580–1593PubMedCrossRefGoogle Scholar
  7. 7.
    Rampil IJ (1998) A primer for EEG signal processing in anesthesia. Anesthesiology 89:980–1002PubMedCrossRefGoogle Scholar
  8. 8.
    Vakkuri A, Yli-Hankala A, Talja P, Mustola S, Tolvanen-Laakso H, Sampson T, Viertiö-Oja H (2004) Time-frequency balanced spectral entropy as a measure of anesthetic drug effect in central nervous system during sevoflurane, propofol, and thiopental anesthesia. Acta Anaesthesiol Scand 48:145–153PubMedCrossRefGoogle Scholar
  9. 9.
    Viertiö-Oja H, Maja V, Särkelä M, Talja P, Tenkanen N, Tolvanen-Laakso H, Paloheimo M, Vakkuri A, Yli-Hankala A, Meriläinen P (2004) Description of the Entropy algorithm as applied in the Datex-Ohmeda S/5 Entropy Module. Acta Anaesthesiol Scand 48:154–161PubMedCrossRefGoogle Scholar
  10. 10.
    White PF, Tang J, Romero GF, Wender RH, Naruse R, Sloninsky A, Kariger R (2006) A comparison of state and response entropy versus bispectral index values during the perioperative period. Anesth Analg 102:160–167PubMedCrossRefGoogle Scholar
  11. 11.
    Myles PS, Cairo S (2004) Artifact in the bispectral index in a patient with severe ischemic brain injury. Anesth Analg 98:706–707PubMedCrossRefGoogle Scholar
  12. 12.
    Grigg MM, Kelly MA, Celesia GG, Ghobrial MW, Ross ER (1987) Electroencephalographic activity after BD. Arch Neurol 44:948–954PubMedGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Johanna Wennervirta
    • 1
  • Tapani Salmi
    • 2
  • Markku Hynynen
    • 3
  • Arvi Yli-Hankala
    • 4
  • Anna-Maria Koivusalo
    • 5
  • Mark Van Gils
    • 6
  • Reino Pöyhiä
    • 1
  • Anne Vakkuri
    • 5
  1. 1.Department of Anesthesiology and Intensive Care MedicineHelsinki University HospitalHelsinkiFinland
  2. 2.Department of Clinical NeurophysiologyHelsinki University HospitalHelsinkiFinland
  3. 3.Department of Anesthesia and Intensive Care MedicineHelsinki University Hospital, Jorvi HospitalEspooFinland
  4. 4.Department of Anesthesia, Tampere University Hospital, and Medical SchoolUniversity of TampereTampereFinland
  5. 5.Department of Anesthesiology and Intensive Care MedicineHelsinki University Hospital, Surgical HospitalHelsinkiFinland
  6. 6.VTT Technical Research Centre of FinlandTampereFinland

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