Comparison of predicted induction dose with predetermined physiologic characteristics of patients and with pharmacokinetic models incorporating those characteristics as covariates.
BACKGROUND
The relationship between patient characteristics and anesthesia induction dose at a high administration rate is unclear. This study was designed to investigate the relation between induction dose and patient characteristics and to compare it to the predicted induction dose using the previously reported pharmacokinetic model.


METHODS
Diluted propofol (0.5 mg/ml) dose required to reach loss of consciousness, when infused at an infusion rate per lean body mass (LBM) of 150 mg x kg(-1) x h(-1) (high rate), was determined in 82 patients, ages 10-85 yr. Cardiac output, blood volume, central blood volume (CBV), and hepatic blood flow were measured with indocyanine green pulse spectrophotometry. Stepwise multiple linear regression models were used to investigate the relations between the patient characteristics and induction dose. These were compared with our previously reported parameters at the rate of 40 mg x kg(-1) x h(-1) (low rate) and with predicted induction doses with two previously reported pharmacokinetic models.


RESULTS
Significant factors for predicting the induction dose at a high rate were age, LBM, and CBV. Induction dose with one pharmacokinetic model was 1.5 times that of the measured one and the other was half that of the measured one at a high rate. At a low rate, one pharmacokinetic model provided an accurate induction dose.


CONCLUSIONS
The prediction of induction dose from physiologic characteristics of patients provides reasonable accuracy at both high and low administration rates of propofol. A previously reported pharmacokinetic model that incorporated patient characteristics provides the same accurate induction dose at a low rate.
Kazama
Tomiei
T
Department of Anesthesiology and Intensive Care, Hamamatsu University School of Medicine, Japan. tkazama@hama-med.ac.jp
Morita
Koji
K
Ikeda
Takehiko
T
Kurita
Tadayoshi
T
Sato
Shigehito
S
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology; D000465:Algorithms; D000771:Anesthesia, Intravenous; D018686:Anesthetics, Intravenous / Q000008:administration & dosage* / Q000493:pharmacokinetics*; D001827:Body Height / Q000502:physiology; D001835:Body Weight / Q000502:physiology; D002302:Cardiac Output / Q000502:physiology; D002648:Child; D005260:Female; D006439:Hemodynamics / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012727:Sex Characteristics; D014018:Tissue Distribution
D018686:Anesthetics, Intravenous