Accuracy of the composite variability index as a measure of the balance between nociception and antinociception during anesthesia.

BACKGROUND: The Composite Variability Index (CVI), derived from the electroencephalogram, was developed to assess the antinociception-nociception balance, whereas the Bispectral Index (BIS) was developed to assess the hypnotic state during anesthesia. We studied the relationships between these indices, level of hypnosis (BIS level), and antinociception (predicted remifentanil effect-site concentrations, CeREMI) before and after stimulation. Also, we measured their association with movement in response to a noxious stimulus. METHODS: We randomized 120 patients to one of 12 groups targeting different hypnotic levels (BIS 70, 50, and 30) and various CeREMI (0, 2, 4, or 6 ng/mL). At pseudo-steady state, baseline values were observed, and a series of stimuli were applied. Changes in BIS, CVI, heart rate (HR), and mean arterial blood pressure (MAP) between baseline and response period were analyzed in relation to level of hypnosis, antinociception, and somatic response to the stimuli. RESULTS: CVI and BIS more accurately correlate with somatic response to an Observer Assessment of Alertness and Sedation-noxious stimulation than HR, MAP, CeREMI, and propofol effect-site concentration (Tukey post hoc tests P < 0.01). Change in CVI is more adequate to monitor response to stimulation than changes in BIS, HR, or MAP (as described by the Mathews Correlation Coefficient with significance level set at P < 0.001). In contrast, none of the candidate analgesic state indices was uniquely related to a specific opioid concentration and is extensively influenced by the hypnotic state as measured by BIS. CONCLUSIONS: CVI appears to correlate with somatic responses to noxious stimuli. However, unstimulated CVI depends more on hypnotic drug effect than on opioid concentration.

Population pharmacokinetics and pharmacodynamics in anesthesia, intensive care and pain medicine.

PURPOSE OF REVIEW: Population modeling is a relatively new pharmacological discipline, the development of which has largely been stimulated by the need for accurate models for the pharmacokinetics and dynamics of anesthetic agents. RECENT FINDINGS: Population-based modeling is now considered superior to older, more traditional modeling methods. Nonlinear mixed-effect modeling - a commonly used population-based modeling approach - estimates intraindividual and interindividual variability, limits the influence of outlying samples and individuals through the use of Bayesian statistical analysis, and provides a potential means of optimizing drug delivery regimens, especially when used to define pharmacokinetic-dynamic models for target-controlled infusion systems. In addition to being used for pharmacokinetic modeling, in which the influence of factors such as age, weight and illness can be studied, it is a powerful tool for the study of the influence of multiple factors on drug pharmacodynamics. SUMMARY: Nonlinear mixed-effect population-based modeling has become the gold standard method of pharmacokinetic and pharmacodynamic analysis during new drug development and during subsequent pharmacological studies. Population-based modeling techniques have been applied to numerous aspects of drug delivery in anesthesia, intensive care and pain medicine.