Predictive performance of Bayesian and nonlinear least-squares regression programs for lidocaine.
The predictive performance of two computer programs for lidocaine dosing were evaluated. Two-compartment Bayesian and nonlinear least-squares regression programs were used in two groups of patients (15 acute arrhythmia patients and 14 chronic arrhythmia patients). Lidocaine was given as a 1.5 mg/kg bolus and a 2.8 mg/min infusion for 48 h. A second bolus (0.5 mg/kg) was given 10 min after the first bolus over 2 min. Serum samples of the patients receiving lidocaine were drawn at 2, 15, 30 min and 1, 2, and 4 h and were used in forecasting the serum concentrations at 6, 8, 12, and 48 h. Predictive performance was assessed by mean error and mean-squared error. The results (mean +/- 95% confidence intervals) demonstrated the Bayesian program predicted a significant (p less than 0.05) difference at 12 h between the two arrhythmia groups (acute 0.52 [-0.95; -0.09] and chronic 0.28 [0.12; 0.44]). The results also demonstrated the Bayesian method was significantly more precise compared to the nonlinear least-squares regression program at 8, 12, and 48 h for the acute group. While caution is warranted, this study demonstrated that the predictive performance by a two-compartment Bayesian model is more accurate in predicting future lidocaine serum concentrations than that by nonlinear least-squares regression.
Destache
C J
CJ
Department of Pharmacy Practice, Creighton University School of Pharmacy, Omaha, NE 68178.
Hilleman
D E
DE
Mohiuddin
S J
SJ
Lang
P T
PT
D000208:Acute Disease; D001145:Arrhythmias, Cardiac / Q000097:blood* / Q000188:drug therapy; D001499:Bayes Theorem; D002908:Chronic Disease; D006801:Humans; D016018:Least-Squares Analysis; D008012:Lidocaine / Q000008:administration & dosage / Q000097:blood*; D008432:Mathematical Computing; D008875:Middle Aged; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012984:Software
D008012:Lidocaine