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(v1.7.0.9001) CLSI 2020 guideline

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dr. M.S. (Matthijs) Berends
2021-06-01 15:33:06 +02:00
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man/as.rsi.Rd
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@ -104,9 +104,9 @@ your_data \%>\% mutate(across(where(is.disk), as.rsi)) # since dplyr 1.0.0
\subsection{Supported Guidelines}{
For interpreting MIC values as well as disk diffusion diameters, currently supported guidelines to be used as input for the \code{guideline} argument are: "EUCAST 2021", "EUCAST 2020", "EUCAST 2019", "EUCAST 2018", "EUCAST 2017", "EUCAST 2016", "EUCAST 2015", "EUCAST 2014", "EUCAST 2013", "EUCAST 2012", "EUCAST 2011", "CLSI 2019", "CLSI 2018", "CLSI 2017", "CLSI 2016", "CLSI 2015", "CLSI 2014", "CLSI 2013", "CLSI 2012", "CLSI 2011" and "CLSI 2010".
For interpreting MIC values as well as disk diffusion diameters, currently implemented guidelines are EUCAST (2011-2021) and CLSI (2010-2020).
Simply using \code{"CLSI"} or \code{"EUCAST"} as input will automatically select the latest version of that guideline. You can set your own data set using the \code{reference_data} argument. The \code{guideline} argument will then be ignored.
Thus, the \code{guideline} argument must be set to e.g., \code{"EUCAST 2021"} or \code{"CLSI 2020"}. By simply using \code{"EUCAST"} (the default) or \code{"CLSI"} as input, the latest version of that guideline will automatically be selected. You can set your own data set using the \code{reference_data} argument. The \code{guideline} argument will then be ignored.
}
\subsection{After Interpretation}{
@ -116,7 +116,7 @@ After using \code{\link[=as.rsi]{as.rsi()}}, you can use the \code{\link[=eucast
\subsection{Machine-Readable Interpretation Guidelines}{
The repository of this package \href{https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt}{contains a machine-readable version} of all guidelines. This is a CSV file consisting of 20,486 rows and 10 columns. This file is machine-readable, since it contains one row for every unique combination of the test method (MIC or disk diffusion), the antimicrobial agent and the microorganism. \strong{This allows for easy implementation of these rules in laboratory information systems (LIS)}. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.
The repository of this package \href{https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt}{contains a machine-readable version} of all guidelines. This is a CSV file consisting of 21,996 rows and 10 columns. This file is machine-readable, since it contains one row for every unique combination of the test method (MIC or disk diffusion), the antimicrobial agent and the microorganism. \strong{This allows for easy implementation of these rules in laboratory information systems (LIS)}. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.
}
\subsection{Other}{
@ -138,7 +138,7 @@ A microorganism is categorised as \emph{Susceptible, standard dosing regimen}, w
A microorganism is categorised as \emph{Susceptible, Increased exposure} when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
}
This AMR package honours this new insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
}
\section{Stable Lifecycle}{
@ -156,7 +156,7 @@ All reference data sets (about microorganisms, antibiotics, R/SI interpretation,
\section{Read more on Our Website!}{
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
}
\examples{