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Mathematical method to build an empirical model for inhaled anesthetic agent wash-in
BACKGROUND: The wide range of fresh gas flow - vaporizer setting (FGF - F(D)) combinations used by different anesthesiologists during the wash-in period of inhaled anesthetics indicates that the selection of FGF and F(D )is based on habit and personal experience. An empirical model could rationalize...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3224103/ https://www.ncbi.nlm.nih.gov/pubmed/21702937 http://dx.doi.org/10.1186/1471-2253-11-13 |
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author | Hendrickx, Jan FA Lemmens, Harry De Cooman, Sofie Van Zundert, André AJ Grouls, René EJ Mortier, Eric De Wolf, Andre M |
author_facet | Hendrickx, Jan FA Lemmens, Harry De Cooman, Sofie Van Zundert, André AJ Grouls, René EJ Mortier, Eric De Wolf, Andre M |
author_sort | Hendrickx, Jan FA |
collection | PubMed |
description | BACKGROUND: The wide range of fresh gas flow - vaporizer setting (FGF - F(D)) combinations used by different anesthesiologists during the wash-in period of inhaled anesthetics indicates that the selection of FGF and F(D )is based on habit and personal experience. An empirical model could rationalize FGF - F(D )selection during wash-in. METHODS: During model derivation, 50 ASA PS I-II patients received desflurane in O(2 )with an ADU(® )anesthesia machine with a random combination of a fixed FGF - F(D )setting. The resulting course of the end-expired desflurane concentration (F(A)) was modeled with Excel Solver, with patient age, height, and weight as covariates; NONMEM was used to check for parsimony. The resulting equation was solved for F(D), and prospectively tested by having the formula calculate F(D )to be used by the anesthesiologist after randomly selecting a FGF, a target F(A )(F(At)), and a specified time interval (1 - 5 min) after turning on the vaporizer after which F(At )had to be reached. The following targets were tested: desflurane F(At )3.5% after 3.5 min (n = 40), 5% after 5 min (n = 37), and 6% after 4.5 min (n = 37). RESULTS: Solving the equation derived during model development for F(D )yields F(D)=-(e((-FGF*-0.23+FGF*0.24))*(e((FGF*-0.23))*F(At)*Ht*0.1-e((FGF*-0.23))*FGF*2.55+40.46-e((FGF*-0.23))*40.46+e((FGF*-0.23+Time/-4.08))*40.46-e((Time/-4.08))*40.46))/((-1+e((FGF*0.24)))*(-1+e((Time/-4.08)))*39.29). Only height (Ht) could be withheld as a significant covariate. Median performance error and median absolute performance error were -2.9 and 7.0% in the 3.5% after 3.5 min group, -3.4 and 11.4% in the 5% after 5 min group, and -16.2 and 16.2% in the 6% after 4.5 min groups, respectively. CONCLUSIONS: An empirical model can be used to predict the FGF - F(D )combinations that attain a target end-expired anesthetic agent concentration with clinically acceptable accuracy within the first 5 min of the start of administration. The sequences are easily calculated in an Excel file and simple to use (one fixed FGF - F(D )setting), and will minimize agent consumption and reduce pollution by allowing to determine the lowest possible FGF that can be used. Different anesthesia machines will likely have different equations for different agents. |
format | Online Article Text |
id | pubmed-3224103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32241032011-11-26 Mathematical method to build an empirical model for inhaled anesthetic agent wash-in Hendrickx, Jan FA Lemmens, Harry De Cooman, Sofie Van Zundert, André AJ Grouls, René EJ Mortier, Eric De Wolf, Andre M BMC Anesthesiol Research Article BACKGROUND: The wide range of fresh gas flow - vaporizer setting (FGF - F(D)) combinations used by different anesthesiologists during the wash-in period of inhaled anesthetics indicates that the selection of FGF and F(D )is based on habit and personal experience. An empirical model could rationalize FGF - F(D )selection during wash-in. METHODS: During model derivation, 50 ASA PS I-II patients received desflurane in O(2 )with an ADU(® )anesthesia machine with a random combination of a fixed FGF - F(D )setting. The resulting course of the end-expired desflurane concentration (F(A)) was modeled with Excel Solver, with patient age, height, and weight as covariates; NONMEM was used to check for parsimony. The resulting equation was solved for F(D), and prospectively tested by having the formula calculate F(D )to be used by the anesthesiologist after randomly selecting a FGF, a target F(A )(F(At)), and a specified time interval (1 - 5 min) after turning on the vaporizer after which F(At )had to be reached. The following targets were tested: desflurane F(At )3.5% after 3.5 min (n = 40), 5% after 5 min (n = 37), and 6% after 4.5 min (n = 37). RESULTS: Solving the equation derived during model development for F(D )yields F(D)=-(e((-FGF*-0.23+FGF*0.24))*(e((FGF*-0.23))*F(At)*Ht*0.1-e((FGF*-0.23))*FGF*2.55+40.46-e((FGF*-0.23))*40.46+e((FGF*-0.23+Time/-4.08))*40.46-e((Time/-4.08))*40.46))/((-1+e((FGF*0.24)))*(-1+e((Time/-4.08)))*39.29). Only height (Ht) could be withheld as a significant covariate. Median performance error and median absolute performance error were -2.9 and 7.0% in the 3.5% after 3.5 min group, -3.4 and 11.4% in the 5% after 5 min group, and -16.2 and 16.2% in the 6% after 4.5 min groups, respectively. CONCLUSIONS: An empirical model can be used to predict the FGF - F(D )combinations that attain a target end-expired anesthetic agent concentration with clinically acceptable accuracy within the first 5 min of the start of administration. The sequences are easily calculated in an Excel file and simple to use (one fixed FGF - F(D )setting), and will minimize agent consumption and reduce pollution by allowing to determine the lowest possible FGF that can be used. Different anesthesia machines will likely have different equations for different agents. BioMed Central 2011-06-24 /pmc/articles/PMC3224103/ /pubmed/21702937 http://dx.doi.org/10.1186/1471-2253-11-13 Text en Copyright ©2011 Hendrickx et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Hendrickx, Jan FA Lemmens, Harry De Cooman, Sofie Van Zundert, André AJ Grouls, René EJ Mortier, Eric De Wolf, Andre M Mathematical method to build an empirical model for inhaled anesthetic agent wash-in |
title | Mathematical method to build an empirical model for inhaled anesthetic agent wash-in |
title_full | Mathematical method to build an empirical model for inhaled anesthetic agent wash-in |
title_fullStr | Mathematical method to build an empirical model for inhaled anesthetic agent wash-in |
title_full_unstemmed | Mathematical method to build an empirical model for inhaled anesthetic agent wash-in |
title_short | Mathematical method to build an empirical model for inhaled anesthetic agent wash-in |
title_sort | mathematical method to build an empirical model for inhaled anesthetic agent wash-in |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3224103/ https://www.ncbi.nlm.nih.gov/pubmed/21702937 http://dx.doi.org/10.1186/1471-2253-11-13 |
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