Skip to main content

Advertisement

Log in

Age progression from vicenarians (20–29 year) to nonagenarians (90–99 year) among a population pharmacokinetic/pharmacodynamic (PopPk-PD) covariate analysis of propofol-bispectral index (BIS) electroencephalography

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

Abstract

Background

Pharmacokinetic/pharmacodynamic (PK/PD) modeling has made an enormous contribution to intravenous anesthesia. Because of their altered physiological, pharmacological and pathological aspects, titrating general anesthesia in the elderly is a challenging task.

Methods

Eighty patients were consecutively enrolled divided by decades from vicenarians (20–29 year) to nonagenarians (90–99 year) into eight groups. Using target controlled infusion (TCI) and electroencephalographic (EEG)-derived bispectral index (BIS) we set propofol plasma concentration (Cp) to gradually reach 3.5 μg mL−1 over 3.5-min. In each patient, we constructed a PK/PD model and conducted a population PK/PD (PopPK-PD) covariate analysis.

Results

Age was significant covariate for baseline BIS effect (E0), inhibitory propofol concentration at 50% BIS decline (IC50) and maximum BIS decline (Emax). First-order rate constant Ke0 of 0.47 min−1 in vicenarians (20–29 year) gradually increased with age-progression to 1.85 min−1 in nonagenarians (90–99 year). Simulation modelling showed that clinically recommended Cp of 3.5 μg mL−1 for 20–29 year BIS 50 should be reduced to 3.0 for 30–49 year, 2.5 for 50–69 year and 2.0 for 80–89 year.

Conclusion

We quantified and graded EEG-BIS age-progression among different age groups divided by decades. We demonstrated deeper BIS values with decades’ age progression. Our data has important implications for propofol dosing. The practical information for physicians in their daily clinical practice is using propofol Cp of 3.5 μg mL−1 might not yield BIS value of 50 in elderly patients. Our simulations showed that the recommended regimen of Cp 3.5 μg mL−1 for 20–29 year should be gradually decreased to 2.0 μg mL−1 for 80–89 year.

Clinical trial registry numbers

European Community Clinical Trials Database EudraCT (http://eudract.emea.eu) initial trial registration number: 2011-002847-81, and subsequently registered at www.clinicaltrials.gov; trial registration number: NCT02585284. Xijing Hospital of Fourth Military Medical University ethics committee approval number 20110707-4.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Ergina P, Gold S, Meakins J (1993) Perioperative care of the elderly patient. World J Surg 17:192–198

    Article  CAS  PubMed  Google Scholar 

  2. Sahinovic MM, Struys MMRF, Absalom AR (2018) Clinical pharmacokinetics and pharmacodynamics of propofol. Clin Pharmacokinet 57:1539–1558

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Tarr L, Oppenheimer B, Sager R (1933) The circulation time in various clinical conditions determined by the use of sodium dehydrochlorate. Am Heart J 8:766

    Article  CAS  Google Scholar 

  4. Raoof AA, Augustijns PR, Verbeeck RK (1996) In vivo assessment of intenstinal, hepatic, and pulmonary first pass metabolism of propofol in the rat. Pharm Res 13:891–895

    Article  CAS  PubMed  Google Scholar 

  5. Dawidowicz AL, Kalitynski R, Fijalkowska A (2003) Free and bound propofol concentrations in human cerebrospinal fluid. Br J Clin Pharmacol 56:545–550

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Engdahl O, Abrahams M, Björnsson A et al (1998) Cerebrospinal fluid concentrations of propofol during anaesthesia in humans. Br J Anaesth 81:957–959

    Article  CAS  PubMed  Google Scholar 

  7. Minto CF, Schnider TW (2008) Contributions of PK/PD modeling to intravenous anesthesia. Clin Pharmacol Ther 84:27–38

    Article  CAS  PubMed  Google Scholar 

  8. Eleveld DJ, Proost JH, Cortínez LI, Absalom AR, Struys MMRF (2014) A general purpose pharmacokinetic model for propofol. Anesth Analg 118:1221–1237

    Article  CAS  PubMed  Google Scholar 

  9. Eleveld DJ, Colin P, Absalom AR, Struys MMRF (2018) Pharmacokinetic-pharmacodynamic model for propofol for broad application in anaesthesia and sedation. Br J Anaesth 120:942–959

    Article  CAS  PubMed  Google Scholar 

  10. Schnider TW, Minto CF, Gambus PL et al (1998) The influence of method of administration and covariates on the pharmacokinetics of propofol in adult volunteers. Anesthesiology 88:1170–1182

    Article  CAS  PubMed  Google Scholar 

  11. Schnider TW, Minto CF, Shafer SL et al (1999) The influence of age on propofol pharmacodynamics. Anesthesiology 90:1502–1516

    Article  CAS  PubMed  Google Scholar 

  12. Sigl JC, Chamoun NG (1994) An introduction to bispectral analysis for the electroencephalogram. J Clin Monit 10:392–404

    Article  CAS  PubMed  Google Scholar 

  13. Lysakowski C, Dumont L, Pellegrini M, Clergue F, Tassonyi E (2001) Effects of fentanyl, alfentanil, remifentanil, and sufentanil on loss of consciousness and bispectral index during propofol induction of anaesthesia. Br J Anaesth 86:523–527

    Article  CAS  PubMed  Google Scholar 

  14. Bossuyt PM, Reitsma JB, Bruns DE et al (2003) The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Clin Chemistry 49:7–18

    Article  CAS  Google Scholar 

  15. Folstein MF, Folstein SE, McHugh PR (1975) ‘Mini-mental state’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatric Research 12:189–198

    Article  CAS  Google Scholar 

  16. Laalou FZ, Egard M, Guillot M, Noll E, Taglang G, Pain L (2010) Influence of preoperative cognitive status on propofol requirement to maintain hypnosis in the elderly. Br J Anaesth 105:342–346

    Article  CAS  PubMed  Google Scholar 

  17. Renna M, Handy J, Shah A (2003) Low baseline Bispectral Index of the electroencephalogram in patients with dementia. Anesth Analg 96:1380–1385

    Article  PubMed  Google Scholar 

  18. Dahaba AA, Xue JX, Xu GX, Liu QH, Metzler H (2011) Bilateral Bispectral Index (BIS)-Vista as a measure of physiologic sleep in sleep-deprived anaesthesiologists. Minerva Anestesiol 77:388–393

    CAS  PubMed  Google Scholar 

  19. Dahaba AA, Bornemann H, Hopfgartner, et al. Effect of sugammadex or neostigmine neuromuscular block reversal on bispectral index monitoring of propofol/remifentanil anaesthesia. Br J Anaesth. 2011; 108: 602–606.

  20. Mathews DM, Kumaran KR, Neuman GG (2003) Bispectral index-derived facial electromyography-guided fentanyl titration in the opiate-exposed patient. Anesth Analg 96:1062–1064

    Article  PubMed  Google Scholar 

  21. Smith C, McEwan AI, Jhaveri R et al (1994) The interaction of fentanyl on the Cp50 of propofol for loss of consciousness and skin incision. Anesthesiology 81:820–828

    Article  CAS  PubMed  Google Scholar 

  22. Dixon WJ, Massey FJ (1983) Introduction to statistical analysis, 4th edn. McGraw-Hill, New York, pp 426–441

    Google Scholar 

  23. Absalom AR, Mani V, De Smet T, Struys MM (2009) Pharmacokinetic models for propofol–defining and illuminating the devil in the detail. Br J Anaesth 103:26–37

    Article  CAS  PubMed  Google Scholar 

  24. Dahaba AA, Zhong T, Lu HS et al (2011) Geographic differences in target-controlled infusion estimated concentration of propofol: bispectral index response curves. Can J Anaesth 58:364–370

    Article  PubMed  Google Scholar 

  25. Buhrer M, Maitre PO, Hung OR, Ebling WR, Shafer SL, Stanski DR (1992) Thiopental pharmacodynamics: defining the pseudo-steady-state serum concentration-EEG effect relationship. Anesthesiology 77:226–236

    Article  CAS  PubMed  Google Scholar 

  26. Chernik DA, Gillings D, Laine H et al (1990) Validity and reliability of the Observer’s Assessment of Alertness/Sedation Scale: study with intravenous midazolam. J Clin Psychopharmacol 10:244–251

    Article  CAS  PubMed  Google Scholar 

  27. Dahaba AA, Lischnig U, Kronthaler R et al (2006) Bispectral-index-guided versus clinically guided remifentanil/propofol analgesia/sedation for interventional radiological procedures: an observer-blinded randomized study. Anesth Analg 103:378–384

    Article  CAS  PubMed  Google Scholar 

  28. Dahaba AA, Prax N, Gaube W, Gries M, Rehak PH, Metzler H (2006) Haemodynamic and catecholamine stress responses to Laryngeal Tube-Suction Airway and the Proseal Laryngeal Mask Airway. Anaesthesia 61:330–334

    Article  CAS  PubMed  Google Scholar 

  29. Mandema JW, Verotta D, Sheiner LB (1992) Building population pharmacokinetic–pharmacodynamic models. I. Models for covariate effects. J Pharmacokinet Biopharm 20:511–528

    Article  CAS  PubMed  Google Scholar 

  30. Zhang L, Beal SL, Sheiner LB (2003) Simultaneous vs sequential analysis for population PK/PD data I: best-case performance. J Pharmacokinet Pharmacodyn 30:387–404

    Article  PubMed  Google Scholar 

  31. Lindbom L, Ribbing J, Jonsson EN (2004) Perl-speaks-NONMEM (PsN): a Perl module for NONMEM related programming. Comput Methods Progr Biomed 75:85–94

    Article  Google Scholar 

  32. Katoh T, Bito H, Sato S (2000) Influence of age on hypnotic requirement, bispectral index, and 95% spectral edge frequency associated with sedation induced by sevoflurane. Anesthesiology 92:55–61

    Article  CAS  PubMed  Google Scholar 

  33. Vernon JM, Lang E, Sebel PS, Manberg P (1995) Prediction of movement using bispectral electroencephalographic analysis during propofol/alfentanil or isoflurane/alfentanil anesthesia. Anesth Analg 80:780–785

    CAS  PubMed  Google Scholar 

  34. Sebel PS, Lang E, Rampil IJ et al (1997) A multicenter study of bispectral electroencephalogram analysis for monitoring anesthetic effect. Anesth Analg 84:891–899

    Article  CAS  PubMed  Google Scholar 

  35. Ouattara A, Boccara G, Lemaire S et al (2003) Target-controlled infusion of propofol and remifentanil in cardiac anaesthesia: influence of age on predicted effect-site concentrations. Br J Anaesth 90:617–622

    Article  CAS  PubMed  Google Scholar 

  36. Kazama T, Ikeda K, Morita K et al (1999) Comparison of the effect-site ke0s of propofol for blood pressure and EEG bispectral index in elderly and younger patients. Anesthesiology 90:1517–1527

    Article  CAS  PubMed  Google Scholar 

  37. Sheiner LB, Rosenberg B, Melmon KL (1972) Modelling of individual pharmacokinetics for computer-aided drug dosage. Comput Biomed Res 5:411–459

    Article  CAS  PubMed  Google Scholar 

  38. Sheiner LB, Sheiner LB, Stanski DR, Vozeh S, Miller RD, Ham J (1979) Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine. Clin Pharmacol Ther 25:358–371

    Article  CAS  PubMed  Google Scholar 

  39. Holford NH, Sheiner LB (1981) Understanding the dose-effect relationship: clinical application of pharmacokinetic-pharmacodynamic models. Clin Pharmacokinet 6:429–453

    Article  CAS  PubMed  Google Scholar 

  40. Cortínez LI (2014) What is the ke0 and what does it tell me about propofol? Anaesthesia 69:399–402

    Article  PubMed  Google Scholar 

  41. Wang Y, Kikuchi T, Sakai M, Wu JL, Sato K, Okumura F (2000) Age-related modifications of effects of ketamine and propofol on rat hippocampal acetylcholine release studied by in vivo brain microdialysis. Acta Anaesthesiol Scand 44:112–117

    Article  CAS  PubMed  Google Scholar 

  42. Larsson JE, Wahlstrom G (1998) The influence of age and administration rate on the brain sensitivity to propofol in rats. Acta Anaesthesiol Scand 42:987–994

    Article  CAS  PubMed  Google Scholar 

  43. Schultz A, Grouven U, Zander I, Beger FA, Siedenberg M, Schultz B (2004) Age-related effects in the EEG during propofol anaesthesia. Acta Anaesthesiol Scand 48:27–34

    Article  CAS  PubMed  Google Scholar 

  44. Roubicek J (1977) The electroencephalogram in the middle-aged and the elderly. J Am Geriatr Soc 25:145–152

    Article  CAS  PubMed  Google Scholar 

  45. Lysakowski C, Elia N, Czarnetzki C et al (2009) Bispectral and spectral entropy indices at propofol-induced loss of consciousness in young and elderly patients. Br J Anaesth 103:387–393

    Article  CAS  PubMed  Google Scholar 

  46. Guignard B, Menigaux C, Dupont X, Fletcher D, Chauvin M (2000) The effect of remifentanil on the bispectral index change and hemodynamic responses after orotracheal intubation. Anesth Analg 90:161–167

    Article  CAS  PubMed  Google Scholar 

  47. Pan Y, Li D, Chen S, Pan H (2004) Activation of μ-opioid receptors excites a population of locus coeruleus-spinal neurons through presynaptic disinhibition. Brain Res 997:67–78

    Article  CAS  PubMed  Google Scholar 

  48. Bouillon T, Bruhn J, Radu-Radulescu L, Bertaccini E, Park S, Shafer S (2002) Non-steady state analysis of the pharmacokinetic interaction between propofol and remifentanil. Anesthesiology 97:1350–1362

    Article  CAS  PubMed  Google Scholar 

  49. Lampotang S, Lizdas DE, Derendorf H, Gravenstein N, Lok B, Quarles JP (2016) Race-specific pharmacodynamic model of propofol-induced loss of consciousness. J Clin Pharmacol 56:1141–1150

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

All authors would like to thank Dr. Fengyan Xu, M.S. and Mr. Shuiyu Zhao, Shanghai Qiangshi Information Technology Co. Ltd., Shanghai, People’s Republic of China our two brilliant Kineticists for their great efforts in the data preparation, data streaming and their NONMEM pharmacokinetic statistical analysis. Thanks to them we have all these simulations and plotted figures. We would like to thank the great efforts of Renate Oberreither for her tremendous help and efforts with the samples assay.

Funding

The study was financed from National Natural Science Foundation of China (Beijing, People’s Republic of China), Grant No.: 81471373, and the National Natural Science Foundation of China (Beijing, People’s Republic of China), Grant No.: 81071052, both grants awarded to Professor Dr. Zhaoyang Xiao, Department of Anesthesiology, Xijing First Affiliated Hospital of Fourth Military Medical University, Xi’an, Shaanxi, and Department of Anesthesiology, Second Affiliated Hospital of Dalian Medical University, Dalian, People’s Republic of China.

Author information

Authors and Affiliations

Authors

Contributions

AAD: Primary investigator, conducted the study, participated in data collection, data analysis and manuscript writing. ZX: participated in perioperative anesthesia management, conducting the study, data collection, data analysis and manuscript writing. XZ: participated in perioperative anesthesia management, conducting the study and data collection, data analysis and manuscript writing. SZ: did the blood sample acquisition, handling, processing and propofol concentration assay. HD: participated in patients’ recruitment, fully informing/consenting patients, perioperative anaesthesia management and conducting the study as well as the team leader of the study project trouble shooting and problem solving. LX: participated in patients’ recruitment, fully informing/consenting patients, perioperative anesthesia management and conducting the study as well as trouble shooting and problem solving. PR: was the original methodologist for the study and he did the first statistical analysis before he passed away. KW: is the pharmacometrician who designed the population pharmacokinetic-pharmacodynamic analysis. GR: is Medical Chemist. He worked out the mathematics of the logistic model. He did fitting of the data to models.

Corresponding author

Correspondence to Zhaoyang Xiao.

Ethics declarations

Conflict of interest

All authors attest to the validity and legitimacy of the data and its interpretation, and agree to its submission. All authors have significantly contributed to the manuscript and no person or group of persons who actively contributed were excluded from the study. All authors confirm that they have read and approved the paper, have met the criteria for authorship as established by the International Committee of Medical Journals Editors, believe that the paper represents honest work, and are able to verify the validity of the results reported. All authors state that we have absolutely no conflicts of interest (including financial, consultant, institutional and other relationships that might lead to bias or a conflict of interest). None of the authors received honoraria from a company or were on the speaker’s bureau for any Organization, and there were no sources of financial support, corporate involvement or patent holdings other than the above mentioned grants from the Scientific Research Fund of Ministry of Health - Major Plan of Science and from above mentioned departmental sources. There was no support whatsoever from a pharmaceutical company or a manufacturer in editing of the protocol, financial support, drug supply, data analysis or writing of the paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

(JPG 159 kb)

Appendix

Appendix

See Figs. 5, 6, and 7.

Fig. 5
figure 5

Observed BIS vs Ages at different time (0, 60, 120, 180, and 210 s). The solid lines are the mean of each group. The corresponding shaded area represent 95% CI of each group

Fig. 6
figure 6

Goodness of fit plot of base model. Observed versus individual predicted concentrations (IPRED, left) and observed versus population predicted concentrations (PRED, right) for the final model. The solid black line in each plot is the line of identity. Conditional weighted residuals (CWRES) versus time on lower left, and PRED on lower right. Points are individual data. Red dashed lines represent the regression. Black dashed lines represent |CWRES|

Fig. 7
figure 7figure 7

ae 1000 times BIS simulation from final PK/PD model stratified by age groups. ae Corresponding to the setup of propofol Cp value to gradually reach 1, 1.5, 2, 2.5, and 3 μg/ml, respectively. The thick blue lines are the median BIS of 1000 simulation of each group. The boarder of shaded band in each group represents 95% CI (2.5th–97.5th percentile) of the 1000 simulation. The orange horizontal lines are BIS = 45, 50, and 55

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dahaba, A.A., Xiao, Z., Zhu, X. et al. Age progression from vicenarians (20–29 year) to nonagenarians (90–99 year) among a population pharmacokinetic/pharmacodynamic (PopPk-PD) covariate analysis of propofol-bispectral index (BIS) electroencephalography. J Pharmacokinet Pharmacodyn 47, 145–161 (2020). https://doi.org/10.1007/s10928-020-09678-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10928-020-09678-0

Keywords

Navigation