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[Application of three compartment model and response surface model to clinical anesthesia using Microsoft Excel]
1Department of Anesthesiology, Kumamoto Regional Medical Center Kumamoto 860-0811.
Masui. the Japanese Journal of Anesthesiology
|August 25, 2011
Summary
This study introduces a Microsoft Excel tool for clinical anesthesia, predicting drug concentrations and patient responses. It simplifies applying advanced pharmacokinetic models to total intravenous anesthesia, aiding clinical practice.
Area of Science:
- Anesthesiology
- Clinical Pharmacology
- Pharmacokinetics
Background:
- Total intravenous anesthesia (TIVA) is increasingly used in clinical practice.
- Accurate prediction of anesthetic drug concentrations is crucial for patient safety.
- Understanding drug interactions is vital for optimizing TIVA.
Purpose of the Study:
- To present a user-friendly Microsoft Excel tool for applying pharmacokinetic models in clinical anesthesia.
- To predict effect-site concentrations of propofol, remifentanil, and fentanyl.
- To calculate the probability of patient response to stimuli during anesthesia.
Main Methods:
- Utilized a three-compartment model to predict drug effect-site concentrations.
- Employed a response surface model to correlate drug concentrations with patient responses.
- Developed a Microsoft Excel file for practical application and graphical visualization.
Main Results:
- The Excel file successfully predicts propofol, remifentanil, and fentanyl effect-site concentrations.
- Calculated probabilities of no response to stimuli (prodding, shaking, painful stimuli, laryngoscopy) based on predicted concentrations.
- Demonstrated time-dependent changes in predicted values graphically.
Conclusions:
- The developed Excel tool offers a simple and helpful method for applying pharmacokinetic and pharmacodynamic principles to clinical anesthesia.
- This approach aids in managing total intravenous anesthesia by predicting drug effects and patient responsiveness.
- Facilitates the practical application of recent advancements in anesthetic drug interaction studies.
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