Journal of Clinical Monitoring and Computing

, Volume 28, Issue 6, pp 525–536 | Cite as

Individualizing propofol dosage: a multivariate linear model approach

  • Conceição RochaEmail author
  • Teresa Mendonça
  • Maria Eduarda Silva
Original Research


In the last decades propofol became established as an intravenous agent for the induction and maintenance of both sedation and general anesthesia procedures. In order to achieve the desired clinical effects appropriate infusion rate strategies must be designed. Moreover, it is important to avoid or minimize associated side effects namely adverse cardiorespiratory effects and delayed recovery. Nowadays, to attain these purposes the continuous propofol delivery is usually performed through target-controlled infusion (TCI) systems whose algorithms rely on pharmacokinetic and pharmacodynamic models. This work presents statistical models to estimate both the infusion rate and the bolus administration. The modeling strategy relies on multivariate linear models, based on patient characteristics such as age, height, weight and gender along with the desired target concentration. A clinical database collected with a RugLoopII device on 84 patients undergoing ultrasonographic endoscopy under sedation-analgesia with propofol and remifentanil is used to estimate the models (training set with 74 cases) and assess their performance (test set with 10 cases). The results obtained in the test set comprising a broad range of characteristics are satisfactory since the models are able to predict bolus, infusion rates and the effect-site concentrations comparable to those of TCI. Furthermore, comparisons of the effect-site concentrations for dosages predicted by the proposed Linear model and the Marsh model for the same target concentration is achieved using Schnider model and a factorial design on the factors (patients characteristics). The results indicate that the Linear model predicts a dosage profile that is faster in leading to an effect-site concentration closer to the desired target concentration.


Model approximation Estimation parameters Regression analysis Error analysis Linear prediction Medical applications 



This work was supported by FEDER funds through COMPETE–Operational Programme Factors of Competitiveness (“Programa Operacional Factores de Competitividade”) and by Portuguese funds through the Center for Research and Development in Mathematics and Applications (University of Aveiro) and the Portuguese Foundation for Science and Technology (“FCT–Fundação para a Ciência e a Tecnologia”), within projects PEst-C/MAT/UI4106/2011 with COMPETE number FCOMP-01-0124-FEDER-022690 and GALENO - Modeling and Control for personalized drug administration, PTDC/SAU-BEB/103 667/2008. Conceição Rocha acknowledges the grant SFRH/BD/61781 /2009 by FCT/ESF. The authors thank Pedro Gambus (PhD) and Eric Jensen (PhD) in Proclinic Hospital in Barcelona, Spain for providing the clinical database.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Conceição Rocha
    • 1
    • 3
    Email author
  • Teresa Mendonça
    • 1
    • 3
  • Maria Eduarda Silva
    • 2
    • 3
  1. 1.Faculdade de Ciências da Universidade do PortoPortoPortugal
  2. 2.Faculdade de Economia da Universidade do PortoPortoPortugal
  3. 3.Center for Research & Development in Mathematics and Applications (CIDMA)AveiroPortugal

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