Advertisement

Pharmacodynamic modeling of propofol-induced tidal volume depression in children

  • Jin-Oh HahnEmail author
  • Sara Khosravi
  • Maryam Dosani
  • Guy A. Dumont
  • J. Mark Ansermino
Article

Abstract

Objective

This investigation aimed to develop a pediatric pharmacodynamic model of propofol-induced tidal volume depression towards an ultimate goal of developing a dosing schedule that would preserve spontaneous breathing following a loading dose of propofol.

Methods

Fifty two ASA 1 and 2 children aged 6–15 year presenting for gastrointestinal endoscopy were enrolled. Subjects were administered a loading dose of 4 mg/kg of propofol intravenously at a constant infusion rate determined by a randomization schedule. Respiratory parameters including tidal volume, respiratory rate, minute volume, and end-tidal CO2 were recorded at 5 s intervals. Using the predicted plasma concentration, based on the Paedfusor pharmacokinetic model, propofol-induced tidal volume depression was modeled by 3 different approaches (2-stage, pooled, and mixed effects) and results were compared using prediction residual, median percentage errors, median absolute percentage errors, and root-mean-squared normalized errors. The effects of age and body weight as covariates were examined.

Results

Respiratory rate and end-tidal CO2 did not show clear dependence on the predicted plasma concentration. The pharmacodynamic models for tidal volume derived from different modeling approaches were highly consistent. The 2-stage, pooled, and mixed effects approaches yielded ke0 of 1.06, 1.24, and 0.72 min−1; γ of 1.10, 0.83, and 0.93; EC50 of 3.18, 3.44, and 3.00 mcg/ml. Including age and body weight as covariates did not significantly improve the predictive performance of the models.

Conclusions

A pediatric pharmacodynamic model of propofol-induced tidal volume depression was developed. Models derived from 3 different approaches were shown to be consistent with each other; however, the individual pharmacodynamic parameters exhibited significant inter-individual variability without strong dependence on age and body weight. This would suggest the desirability of adapting the pharmacodynamic model to each subject in real time.

Keywords

pharmacodynamics pediatrics propofol tidal volume respiratory depression anesthesia 

Notes

Conflict of interest

Conflict of interest: None.

References

  1. 1.
    McCormack J. Total intravenous anaesthesia in children. Current Anaesthesia & Critical Care. 2008;19:309–14.CrossRefGoogle Scholar
  2. 2.
    Muñoz HR, León PJ, Fuentes RS, Echevarría GC, Cortínez LI. Prospective evaluation of the time to peak effect of propofol to target the effect site in children. Acta Anaesthesiol Scand. 2009;53:883–90.PubMedCrossRefGoogle Scholar
  3. 3.
    Dosani M, McCormack J, Reimer E, Brant R, Dumont GA, Lim J, Ansermino JM. Slower administration of propofol preserves adequate respiration in children. Pediatric Anesthesia. 2010;20:1001–8.PubMedCrossRefGoogle Scholar
  4. 4.
    Kataria BK, Ved SA, Nicodemus HF, Hoy GR, Lea D, Dubois MY, Mandema JW, Shafer SL. The pharmacokinetics of propofol in children using three different data analysis approaches. Anesthesiology. 1994;80:104–22.PubMedCrossRefGoogle Scholar
  5. 5.
    Abosalom A, Kenny G. “Paedfusor” pharmacokinetic data set. British Journal of Aneasthesia. 2005;95:110.CrossRefGoogle Scholar
  6. 6.
    Cortínez LI, Muñoz HR, López R. Pharmacodynamics of propofol in children and adults: comparison based on the auditory evoked potentials index. Revista Española de Anestesiología y Reanimación. 2006;53:289–96.PubMedGoogle Scholar
  7. 7.
    Jeleazcov C, Ihmsen H, Schmidt J, Ammon C, Schwilden H, Schüttler J, Fechner J. Pharmacodynamic modeling of the bispectral index response to propofol-based anesthesia during general surgery in children. Br J Anaesth. 2008;100:509–16.PubMedCrossRefGoogle Scholar
  8. 8.
    MATLAB Optimization Toolbox User’s Guide. Natick: MathWorks, 2010: 468–495.Google Scholar
  9. 9.
    MATLAB Statistics Toolbox User’s Guide. Natick: MathWorks, 2010: 1588–1601.Google Scholar
  10. 10.
    Varvel JR, Donoho DL, Shafer SL. Measuring the predictive performance of computer-controlled infusion pumps. J Pharmacokinet Biopharm. 1992;20:63–94.PubMedCrossRefGoogle Scholar
  11. 11.
    Bouillon T, Bruhn J, Radu-Radulescu L, Andresen C, Cohane C, Shafer SL. Mixed-effects modeling of the intrinsic ventilatory depressant potency of propofol in the non-steady-state. Anesthesiology. 2004;100:240–50.PubMedCrossRefGoogle Scholar
  12. 12.
    Olofsen E, Boom M, Nieuwenhuijs D, Sarton E, Teppema L, Aarts L, Dahan A. Modeling the non-steady state respiratory effects of remifentanil in awake and propofol-sedated healthy volunteers. Anesthesiology. 2010;112:1382–95.PubMedCrossRefGoogle Scholar
  13. 13.
    Muñoz HR, Cortínez LI, Ibacache ME, Leon PJ. Estimation of the plasma effect site equilibration rate constant (ke0) of propofol in children using the time to peak effect: comparison with adults. Anesthesiology. 2004;101:1269–74.PubMedGoogle Scholar
  14. 14.
    Nieuwenhuijs D, Olofsen E, Romberg R, Sarton E, Ward D, Engbers F, Vuyk J, Mooren R, Teppema L, Dahan A. Response surface modeling of remifentanil-propofol interaction on cardiorespiratory control and bispectral index. Anesthesiology. 2003;98:312–22.PubMedCrossRefGoogle Scholar
  15. 15.
    Gilhuly TJ, Hutchings SR, Dumont GA, MacLeod BA. Development and pilot testing of the neuromuscular blockade advisory system. Comput Methods Programs Biomed. 2008;89:179–88.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Jin-Oh Hahn
    • 1
    Email author
  • Sara Khosravi
    • 2
  • Maryam Dosani
    • 3
  • Guy A. Dumont
    • 2
  • J. Mark Ansermino
    • 3
  1. 1.Department of Mechanical EngineeringUniversity of AlbertaEdmontonCanada
  2. 2.Department of Electrical and Computer EngineeringUniversity of British ColumbiaVancouverCanada
  3. 3.Department of Anesthesiology, Pharmacology and TherapeuticsUniversity of British ColumbiaVancouverCanada

Personalised recommendations