Skip to main content

Advertisement

Log in

Usefulness of permutation entropy as an anesthetic depth indicator in children

  • Original Paper
  • Published:
Journal of Pharmacokinetics and Pharmacodynamics Aims and scope Submit manuscript

Abstract

Permutation entropy (PE) as a complexity measure has been introduced to monitor anesthetic depth for adult. However, PE has not yet been evaluated for its clinical applicability as an indicator of anesthetic depth in children. Therefore, in order to investigate the validity of PE, we compared PE with BIS using pharmacodynamic (PD) modeling in children. Electroencephalogram (EEG) was obtained from BIS monitor during sevoflurane deepening and lightening protocol. End-tidal sevoflurane concentration (Etsevo) and BIS were measured simultaneously. PE was calculated from the processed EEG with the scale ranging from 0 to 100. NONMEM software was used to investigate the PD relationship between Etsevo with BIS and PE. Adjusted PE (APE) values were decreased as anesthesia deepened. APE and BIS showed significant linear correlation (P < 0.001), indicating that PE also reflects anesthesia depth. PD parameters for APE and BIS were estimated with a sigmoid Emax model which describes the relationship between Etsevo and APE/BIS (E o : 78, E max : 17.6, C e50 : 2.5 vol%; γ: 13.1, k eo : 0.47 min−1 for APE; E o : 89.4; E max : 15.7; C e50 : 2.2 vol%; γ: 6.6, keo: 0.52 min−1 for BIS). PE seems to be a useful indicator of anesthetic depth, which is comparable to BIS in children.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Kreuer S, Biedler A, Larsen R, Altmann S, Wilhelm W (2003) Narcotrend monitoring allows faster emergence and a reduction of drug consumption in propofol-remifentanil anesthesia. Anesthesiology 99(1):34–41

    Article  CAS  PubMed  Google Scholar 

  2. Yli-Hankala A, Vakkuri A, Annila P, Korttila K (1999) EEG bispectral index monitoring in sevoflurane or propofol anaesthesia: analysis of direct costs and immediate recovery. Acta Anaesthesiol Scand 43(5):545–549

    Article  CAS  PubMed  Google Scholar 

  3. Johansen JW, Sebel PS, Sigl JC (2000) Clinical impact of hypnotic-titration guidelines based on EEG bispectral index (BIS) monitoring during routine anesthetic care. J Clin Anesth 12(6):433–443

    Article  CAS  PubMed  Google Scholar 

  4. Heier T, Steen PA (1996) Assessment of anaesthesia depth. Acta Anaesthesiol Scand 40(9):1087–1100

    Article  CAS  PubMed  Google Scholar 

  5. Rampil IJ, Matteo RS (1987) Changes in EEG spectral edge frequency correlate with the hemodynamic response to laryngoscopy and intubation. Anesthesiology 67(1):139–142

    Article  CAS  PubMed  Google Scholar 

  6. Ellerkmann RK, Liermann VM, Alves TM, Wenningmann I, Kreuer S, Wilhelm W, Roepcke H, Hoeft A, Bruhn J (2004) Spectral entropy and bispectral index as measures of the electroencephalographic effects of sevoflurane. Anesthesiology 101(6):1275–1282

    Article  CAS  PubMed  Google Scholar 

  7. Elbert T, Ray WJ, Kowalik ZJ, Skinner JE, Graf KE, Birbaumer N (1994) Chaos and physiology: deterministic chaos in excitable cell assemblies. Physiol Rev 74(1):1–47

    CAS  PubMed  Google Scholar 

  8. Fell J, Roschke J, Mann K, Schäffner C (1996) Discrimination of sleep stages: a comparison between spectral and nonlinear EEG measures. Electroencephalogr Clin Neurophysiol 98(5):401–410

    Article  CAS  PubMed  Google Scholar 

  9. Grassberger P, Procaccia I (1983) Estimation of the Kolmogorov entropy from a chaotic signal. Phys Rev A 28(4):2591–2593

    Article  Google Scholar 

  10. Bruhn J, Ropcke H, Rehberg B, Bouillon T, Hoeft A (2000) Electroencephalogram approximate entropy correctly classifies the occurrence of burst suppression pattern as increasing anesthetic drug effect. Anesthesiology 93(4):981–985

    Article  CAS  PubMed  Google Scholar 

  11. Bruhn J, Ropcke H, Hoeft A (2000) Approximate entropy as an electroencephalographic measure of anesthetic drug effect during desflurane anesthesia. Anesthesiology 92(3):715–726

    Article  CAS  PubMed  Google Scholar 

  12. Bandt C, Pompe B (2002) Permutation entropy: a natural complexity measure for time series. Phys Rev Lett 88(17):174102

    Article  PubMed  Google Scholar 

  13. Cao YH, Tung WW, Gao JB, Protopopescu VA, Hively LM (2004) Detecting dynamical changes in time series using the permutation entropy. Phys Rev E 70(4 Pt 2):046217

    Article  Google Scholar 

  14. Olofsen E, Sleigh JW, Dahan A (2008) Permutation entropy of the electroencephalogram: a measure of anaesthetic drug effect. Br J Anaesth 101(6):810–821

    Article  CAS  PubMed  Google Scholar 

  15. Li XL, Cui SY, Voss LJ (2008) Using permutation entropy to measure the electroencephalographic effects of sevoflurane. Anesthesiology 109(3):448–456

    Article  CAS  PubMed  Google Scholar 

  16. Constant I, Sabourdin N (2012) The EEG signal: a window on the cortical brain activity. Paediatr Anaesth 22(6):539–552

    Article  PubMed  Google Scholar 

  17. Jensen EW, Litvan H, Struys M, Martinez Vazquez P (2004) Pitfalls and challenges when assessing the depth of hypnosis during general anaesthesia by clinical signs and electronic indices. Acta Anaesthesiol Scand 48(10):1260–1267

    Article  CAS  PubMed  Google Scholar 

  18. Jameson LC, Sloan TB (2006) Using EEG to monitor anesthesia drug effects during surgery. J Clin Monit Comput 20(6):445–472

    Article  PubMed  Google Scholar 

  19. Bandt C (2005) Ordinal time series analysis. Ecol Model 182(3–4):229–238

    Article  Google Scholar 

  20. Schnider TW, Minto CF, Shafer SL, Gambus PL, Andresen C, Goodale DB, Youngs EJ (1999) The influence of age on propofol pharmacodynamics. Anesthesiology 90(6):1502–1516

    Article  CAS  PubMed  Google Scholar 

  21. Jonsson EN1, Karlsson MO (1999) Xpose–an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM Comput Methods Progr Biomed 58(1):51–64

  22. March PA, Muir WW (2005) Bispectral analysis of the electroencephalogram: a review of its development and use in anesthesia. Vet Anaesth Analg 32(5):241–255

    Article  PubMed  Google Scholar 

  23. Goncharova II, McFarland DJ, Vaughan TM, Wolpaw JR (2003) EMG contamination of EEG: spectral and topographical characteristics. Clin Neurophysiol 114(9):1580–1593

    Article  CAS  PubMed  Google Scholar 

  24. Gasser T, Verleger R, Bacher P, Sroka L (1988) Development of the EEG of school-age children and adolescents. I. Analysis of band power. Electroencephalogr Clin Neurophysiol 69(2):91–99

    Article  CAS  PubMed  Google Scholar 

  25. Nunes RR, Chaves IM, de Alencar JC, Franco SB, de Oliveira YG, de Menezes DG (2012) Bispectral index and other processed parameters of electroencephalogram: an update. Rev Bras Anestesiol 62(1):105–117

    Article  PubMed  Google Scholar 

  26. Rampil IJ (1998) A Primer for EEG Signal Processing in Anesthesia. Anesthesiology 89(4):980–1002

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We are grateful to all members in Biomedical Knowledge Engineering Lab, Seoul National University, College of Dentistry for their assistance. And we are also grateful to Professor Satoshi Hagihria for providing Bispectrum Analyzer software.

Conflict of interest

The authors declared no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Hong-Gee Kim or Teo Jeon Shin.

Additional information

Teo Jeon Shin and Hong-Gee Kim equally contributed to this study.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PPTX 190 kb)

Appendix: NONMEM control code

Appendix: NONMEM control code

figure a

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, PJ., Kim, HG., Noh, GJ. et al. Usefulness of permutation entropy as an anesthetic depth indicator in children. J Pharmacokinet Pharmacodyn 42, 123–134 (2015). https://doi.org/10.1007/s10928-015-9405-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10928-015-9405-5

Keywords

Navigation