Temporal linear mode complexity as a surrogate measure of the effect of remifentanil on the central nervous system in healthy volunteers
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Remifentanil, an intravenous ultra short‐acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic par...
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Published in | British journal of clinical pharmacology Vol. 71; no. 6; pp. 871 - 885 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford, UK
Blackwell Publishing Ltd
01.06.2011
Blackwell Blackwell Science Inc |
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Abstract | WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT
• Remifentanil, an intravenous ultra short‐acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic parameters, including 95% spectral edge frequency, the canonical univariate parameter and electroencephalographic approximate entropy.
• A sigmoid Emax model, in which the highest predicted values of processed electroencephalographic parameters are restricted to the baseline value, cannot describe a rebound of these parameters.
• Electroencephalographic approximate entropy correlated well with the remifentanil blood concentration and demonstrated high baseline stability.
WHAT THIS STUDY ADDS
• A combined effect and tolerance model effectively characterized the time course of the remifentanil effect on the central nervous system, including the rebound which occurred during recovery from the remifentanil effect.
• Temporal linear mode complexity was comparable with approximate entropy as a univariate electroencephalographic descriptor of the effect of remifentanil on the central nervous system.
AIMS Previously, electroencephalographic approximate entropy (ApEn) effectively described both depression of central nervous system (CNS) activity and rebound during and after remifentanil infusion. ApEn is heavily dependent on the record length. Linear mode complexity, which is algorithmatically independent of the record length, was investigated to characterize the effect of remifentanil on the CNS using the combined effect and tolerance, feedback and sigmoid Emax models.
METHODS The remifentanil blood concentrations and electroencephalographic data obtained in our previous study were used. With the recording of the electroencephalogram, remifentanil was infused at a rate of 1, 2, 3, 4, 5, 6, 7 or 8 µg kg−1 min−1 for 15–20 min. The areas below (AUCeffect) or above (AACrebound) the effect vs. time curve of temporal linear mode complexity (TLMC) and ApEn were calculated to quantitate the decrease of the CNS activity and rebound. The coefficients of variation (CV) of median baseline (E0), maximal (Emax), and individual median E0 minus Emax values of TLMC were compared with those of ApEn. The concentration–TLMC relationship was characterized by population analysis using non‐linear mixed effects modelling.
RESULTS Median AUCeffect and AACrebound were 1016 and 5.3 (TLMC), 787 and 4.5 (ApEn). The CVs of individual median E0 minus Emax were 35.6, 32.5% (TLMC, ApEn). The combined effect and tolerance model demonstrated the lowest Akaike information criteria value and the highest positive predictive value of rebound in tolerance.
CONCLUSIONS The combined effect and tolerance model effectively characterized the time course of TLMC as a surrogate measure of the effect of remifentanil on the CNS. |
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AbstractList | • Remifentanil, an intravenous ultra short-acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic parameters, including 95% spectral edge frequency, the canonical univariate parameter and electroencephalographic approximate entropy. • A sigmoid Emax model, in which the highest predicted values of processed electroencephalographic parameters are restricted to the baseline value, cannot describe a rebound of these parameters. • Electroencephalographic approximate entropy correlated well with the remifentanil blood concentration and demonstrated high baseline stability.WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Remifentanil, an intravenous ultra short-acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic parameters, including 95% spectral edge frequency, the canonical univariate parameter and electroencephalographic approximate entropy. • A sigmoid Emax model, in which the highest predicted values of processed electroencephalographic parameters are restricted to the baseline value, cannot describe a rebound of these parameters. • Electroencephalographic approximate entropy correlated well with the remifentanil blood concentration and demonstrated high baseline stability.• A combined effect and tolerance model effectively characterized the time course of the remifentanil effect on the central nervous system, including the rebound which occurred during recovery from the remifentanil effect. • Temporal linear mode complexity was comparable with approximate entropy as a univariate electroencephalographic descriptor of the effect of remifentanil on the central nervous system. AIMS Previously, electroencephalographic approximate entropy (ApEn) effectively described both depression of central nervous system (CNS) activity and rebound during and after remifentanil infusion. ApEn is heavily dependent on the record length. Linear mode complexity, which is algorithmatically independent of the record length, was investigated to characterize the effect of remifentanil on the CNS using the combined effect and tolerance, feedback and sigmoid E(max) models. METHODS The remifentanil blood concentrations and electroencephalographic data obtained in our previous study were used. With the recording of the electroencephalogram, remifentanil was infused at a rate of 1, 2, 3, 4, 5, 6, 7 or 8 µg kg(-1) min(-1) for 15-20 min. The areas below (AUC(effect) ) or above (AAC(rebound) ) the effect vs. time curve of temporal linear mode complexity (TLMC) and ApEn were calculated to quantitate the decrease of the CNS activity and rebound. The coefficients of variation (CV) of median baseline (E(0)), maximal (E(max)), and individual median E(0) minus E(max) values of TLMC were compared with those of ApEn. The concentration-TLMC relationship was characterized by population analysis using non-linear mixed effects modelling.WHAT THIS STUDY ADDS• A combined effect and tolerance model effectively characterized the time course of the remifentanil effect on the central nervous system, including the rebound which occurred during recovery from the remifentanil effect. • Temporal linear mode complexity was comparable with approximate entropy as a univariate electroencephalographic descriptor of the effect of remifentanil on the central nervous system. AIMS Previously, electroencephalographic approximate entropy (ApEn) effectively described both depression of central nervous system (CNS) activity and rebound during and after remifentanil infusion. ApEn is heavily dependent on the record length. Linear mode complexity, which is algorithmatically independent of the record length, was investigated to characterize the effect of remifentanil on the CNS using the combined effect and tolerance, feedback and sigmoid E(max) models. METHODS The remifentanil blood concentrations and electroencephalographic data obtained in our previous study were used. With the recording of the electroencephalogram, remifentanil was infused at a rate of 1, 2, 3, 4, 5, 6, 7 or 8 µg kg(-1) min(-1) for 15-20 min. The areas below (AUC(effect) ) or above (AAC(rebound) ) the effect vs. time curve of temporal linear mode complexity (TLMC) and ApEn were calculated to quantitate the decrease of the CNS activity and rebound. The coefficients of variation (CV) of median baseline (E(0)), maximal (E(max)), and individual median E(0) minus E(max) values of TLMC were compared with those of ApEn. The concentration-TLMC relationship was characterized by population analysis using non-linear mixed effects modelling.Median AUC(effect) and AAC(rebound) were 1016 and 5.3 (TLMC), 787 and 4.5 (ApEn). The CVs of individual median E(0) minus E(max) were 35.6, 32.5% (TLMC, ApEn). The combined effect and tolerance model demonstrated the lowest Akaike information criteria value and the highest positive predictive value of rebound in tolerance.RESULTSMedian AUC(effect) and AAC(rebound) were 1016 and 5.3 (TLMC), 787 and 4.5 (ApEn). The CVs of individual median E(0) minus E(max) were 35.6, 32.5% (TLMC, ApEn). The combined effect and tolerance model demonstrated the lowest Akaike information criteria value and the highest positive predictive value of rebound in tolerance.The combined effect and tolerance model effectively characterized the time course of TLMC as a surrogate measure of the effect of remifentanil on the CNS.CONCLUSIONSThe combined effect and tolerance model effectively characterized the time course of TLMC as a surrogate measure of the effect of remifentanil on the CNS. times Remifentanil, an intravenous ultra short-acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic parameters, including 95% spectral edge frequency, the canonical univariate parameter and electroencephalographic approximate entropy. times A sigmoid Emax model, in which the highest predicted values of processed electroencephalographic parameters are restricted to the baseline value, cannot describe a rebound of these parameters. times Electroencephalographic approximate entropy correlated well with the remifentanil blood concentration and demonstrated high baseline stability. WHAT THIS STUDY ADDS times A combined effect and tolerance model effectively characterized the time course of the remifentanil effect on the central nervous system, including the rebound which occurred during recovery from the remifentanil effect. times Temporal linear mode complexity was comparable with approximate entropy as a univariate electroencephalographic descriptor of the effect of remifentanil on the central nervous system. AIMS Previously, electroencephalographic approximate entropy (ApEn) effectively described both depression of central nervous system (CNS) activity and rebound during and after remifentanil infusion. ApEn is heavily dependent on the record length. Linear mode complexity, which is algorithmatically independent of the record length, was investigated to characterize the effect of remifentanil on the CNS using the combined effect and tolerance, feedback and sigmoid Emax models. METHODS The remifentanil blood concentrations and electroencephalographic data obtained in our previous study were used. With the recording of the electroencephalogram, remifentanil was infused at a rate of 1, 2, 3, 4, 5, 6, 7 or 8 mu gkg-1min-1 for 15-20min. The areas below (AUCeffect) or above (AACrebound) the effect vs. time curve of temporal linear mode complexity (TLMC) and ApEn were calculated to quantitate the decrease of the CNS activity and rebound. The coefficients of variation (CV) of median baseline (E0), maximal (Emax), and individual median E0 minus Emax values of TLMC were compared with those of ApEn. The concentration-TLMC relationship was characterized by population analysis using non-linear mixed effects modelling. RESULTS Median AUCeffect and AACrebound were 1016 and 5.3 (TLMC), 787 and 4.5 (ApEn). The CVs of individual median E0 minus Emax were 35.6, 32.5% (TLMC, ApEn). The combined effect and tolerance model demonstrated the lowest Akaike information criteria value and the highest positive predictive value of rebound in tolerance. CONCLUSIONS The combined effect and tolerance model effectively characterized the time course of TLMC as a surrogate measure of the effect of remifentanil on the CNS.Original Abstract: WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Remifentanil, an intravenous ultra short‐acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic parameters, including 95% spectral edge frequency, the canonical univariate parameter and electroencephalographic approximate entropy. • A sigmoid Emax model, in which the highest predicted values of processed electroencephalographic parameters are restricted to the baseline value, cannot describe a rebound of these parameters. • Electroencephalographic approximate entropy correlated well with the remifentanil blood concentration and demonstrated high baseline stability. WHAT THIS STUDY ADDS • A combined effect and tolerance model effectively characterized the time course of the remifentanil effect on the central nervous system, including the rebound which occurred during recovery from the remifentanil effect. • Temporal linear mode complexity was comparable with approximate entropy as a univariate electroencephalographic descriptor of the effect of remifentanil on the central nervous system. AIMS Previously, electroencephalographic approximate entropy (ApEn) effectively described both depression of central nervous system (CNS) activity and rebound during and after remifentanil infusion. ApEn is heavily dependent on the record length. Linear mode complexity, which is algorithmatically independent of the record length, was investigated to characterize the effect of remifentanil on the CNS using the combined effect and tolerance, feedback and sigmoid E max models. METHODS The remifentanil blood concentrations and electroencephalographic data obtained in our previous study were used. With the recording of the electroencephalogram, remifentanil was infused at a rate of 1, 2, 3, 4, 5, 6, 7 or 8 µg kg −1 min −1 for 15–20 min. The areas below (AUC effect ) or above (AAC rebound ) the effect vs. time curve of temporal linear mode complexity (TLMC) and ApEn were calculated to quantitate the decrease of the CNS activity and rebound. The coefficients of variation (CV) of median baseline (E 0 ), maximal (E max ), and individual median E 0 minus E max values of TLMC were compared with those of ApEn. The concentration–TLMC relationship was characterized by population analysis using non‐linear mixed effects modelling. RESULTS Median AUC effect and AAC rebound were 1016 and 5.3 (TLMC), 787 and 4.5 (ApEn). The CVs of individual median E 0 minus E max were 35.6, 32.5% (TLMC, ApEn). The combined effect and tolerance model demonstrated the lowest Akaike information criteria value and the highest positive predictive value of rebound in tolerance. CONCLUSIONS The combined effect and tolerance model effectively characterized the time course of TLMC as a surrogate measure of the effect of remifentanil on the CNS. • Remifentanil, an intravenous ultra short-acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic parameters, including 95% spectral edge frequency, the canonical univariate parameter and electroencephalographic approximate entropy. • A sigmoid Emax model, in which the highest predicted values of processed electroencephalographic parameters are restricted to the baseline value, cannot describe a rebound of these parameters. • Electroencephalographic approximate entropy correlated well with the remifentanil blood concentration and demonstrated high baseline stability. • A combined effect and tolerance model effectively characterized the time course of the remifentanil effect on the central nervous system, including the rebound which occurred during recovery from the remifentanil effect. • Temporal linear mode complexity was comparable with approximate entropy as a univariate electroencephalographic descriptor of the effect of remifentanil on the central nervous system. AIMS Previously, electroencephalographic approximate entropy (ApEn) effectively described both depression of central nervous system (CNS) activity and rebound during and after remifentanil infusion. ApEn is heavily dependent on the record length. Linear mode complexity, which is algorithmatically independent of the record length, was investigated to characterize the effect of remifentanil on the CNS using the combined effect and tolerance, feedback and sigmoid E(max) models. METHODS The remifentanil blood concentrations and electroencephalographic data obtained in our previous study were used. With the recording of the electroencephalogram, remifentanil was infused at a rate of 1, 2, 3, 4, 5, 6, 7 or 8 µg kg(-1) min(-1) for 15-20 min. The areas below (AUC(effect) ) or above (AAC(rebound) ) the effect vs. time curve of temporal linear mode complexity (TLMC) and ApEn were calculated to quantitate the decrease of the CNS activity and rebound. The coefficients of variation (CV) of median baseline (E(0)), maximal (E(max)), and individual median E(0) minus E(max) values of TLMC were compared with those of ApEn. The concentration-TLMC relationship was characterized by population analysis using non-linear mixed effects modelling. Median AUC(effect) and AAC(rebound) were 1016 and 5.3 (TLMC), 787 and 4.5 (ApEn). The CVs of individual median E(0) minus E(max) were 35.6, 32.5% (TLMC, ApEn). The combined effect and tolerance model demonstrated the lowest Akaike information criteria value and the highest positive predictive value of rebound in tolerance. The combined effect and tolerance model effectively characterized the time course of TLMC as a surrogate measure of the effect of remifentanil on the CNS. WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Remifentanil, an intravenous ultra short‐acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta activation after discontinuation, resulting in a rebound of the processed electroencephalographic parameters, including 95% spectral edge frequency, the canonical univariate parameter and electroencephalographic approximate entropy. • A sigmoid Emax model, in which the highest predicted values of processed electroencephalographic parameters are restricted to the baseline value, cannot describe a rebound of these parameters. • Electroencephalographic approximate entropy correlated well with the remifentanil blood concentration and demonstrated high baseline stability. WHAT THIS STUDY ADDS • A combined effect and tolerance model effectively characterized the time course of the remifentanil effect on the central nervous system, including the rebound which occurred during recovery from the remifentanil effect. • Temporal linear mode complexity was comparable with approximate entropy as a univariate electroencephalographic descriptor of the effect of remifentanil on the central nervous system. AIMS Previously, electroencephalographic approximate entropy (ApEn) effectively described both depression of central nervous system (CNS) activity and rebound during and after remifentanil infusion. ApEn is heavily dependent on the record length. Linear mode complexity, which is algorithmatically independent of the record length, was investigated to characterize the effect of remifentanil on the CNS using the combined effect and tolerance, feedback and sigmoid Emax models. METHODS The remifentanil blood concentrations and electroencephalographic data obtained in our previous study were used. With the recording of the electroencephalogram, remifentanil was infused at a rate of 1, 2, 3, 4, 5, 6, 7 or 8 µg kg−1 min−1 for 15–20 min. The areas below (AUCeffect) or above (AACrebound) the effect vs. time curve of temporal linear mode complexity (TLMC) and ApEn were calculated to quantitate the decrease of the CNS activity and rebound. The coefficients of variation (CV) of median baseline (E0), maximal (Emax), and individual median E0 minus Emax values of TLMC were compared with those of ApEn. The concentration–TLMC relationship was characterized by population analysis using non‐linear mixed effects modelling. RESULTS Median AUCeffect and AACrebound were 1016 and 5.3 (TLMC), 787 and 4.5 (ApEn). The CVs of individual median E0 minus Emax were 35.6, 32.5% (TLMC, ApEn). The combined effect and tolerance model demonstrated the lowest Akaike information criteria value and the highest positive predictive value of rebound in tolerance. CONCLUSIONS The combined effect and tolerance model effectively characterized the time course of TLMC as a surrogate measure of the effect of remifentanil on the CNS. |
Author | Lee, Soo‐Han Choi, Byung‐Moon Noh, Moon‐Ho Noh, Gyu‐Jeong Jeong, Yong‐Bo Shin, Da‐Huin Kim, Young‐Hac Lee, Eun‐Kyung |
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CitedBy_id | crossref_primary_10_1111_1440_1681_12677 crossref_primary_10_1016_j_psychres_2017_06_041 crossref_primary_10_1016_j_xphs_2018_08_017 crossref_primary_10_1155_2017_3521261 crossref_primary_10_1155_2016_2304356 crossref_primary_10_4097_kjae_2013_65_5_385 |
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Keywords | Human Agonist Pharmacodynamics Healthy subject Toxicity μ Opioid receptor Central nervous system Tolerance Opiates feedback model Narcotic analgesic Biological activity Remifentanil Complexity temporal linear mode complexity Feedback Models model Phenylpiperidine derivatives Sedative sigmoid E combined effect and tolerance model |
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Snippet | WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT
• Remifentanil, an intravenous ultra short‐acting opioid, depresses central nervous system activity with an increase... WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Remifentanil, an intravenous ultra short‐acting opioid, depresses central nervous system activity with an increase... • Remifentanil, an intravenous ultra short-acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes beta... times Remifentanil, an intravenous ultra short-acting opioid, depresses central nervous system activity with an increase in the delta band power, and causes... |
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SubjectTerms | Adult Algorithms Analgesics, Opioid - pharmacokinetics Anesthetics, Intravenous - pharmacokinetics Biological and medical sciences Blood Blood levels Central nervous system Central Nervous System - drug effects combined effect and tolerance model Data processing Depression Drug Tolerance EEG Electroencephalography - drug effects Entropy Feedback feedback model Female Humans Intravenous administration Male Medical sciences Models, Biological Models, Statistical Opioids Pharmacodynamics Pharmacology. Drug treatments Piperidines - pharmacokinetics remifentanil sigmoid Emax model temporal linear mode complexity Young Adult |
Title | Temporal linear mode complexity as a surrogate measure of the effect of remifentanil on the central nervous system in healthy volunteers |
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