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(v2.1.1.9057) fix for missing breakpoints

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dr. M.S. (Matthijs) Berends
2024-06-17 16:52:12 +02:00
parent d9e66fb118
commit a4dc37a4e4
7 changed files with 67 additions and 51 deletions
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25
man/as.sir.Rd
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@ -20,6 +20,7 @@ For interpretations of minimum inhibitory concentration (MIC) values and disk di
\item \strong{CLSI M100: Performance Standard for Antimicrobial Susceptibility Testing}, 2011-2024, \emph{Clinical and Laboratory Standards Institute} (CLSI). \url{https://clsi.org/standards/products/microbiology/documents/m100/}.
\item \strong{CLSI VET01: Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals}, 2019-2024, \emph{Clinical and Laboratory Standards Institute} (CLSI). \url{https://clsi.org/standards/products/veterinary-medicine/documents/vet01//}.
\item \strong{EUCAST Breakpoint tables for interpretation of MICs and zone diameters}, 2011-2024, \emph{European Committee on Antimicrobial Susceptibility Testing} (EUCAST). \url{https://www.eucast.org/clinical_breakpoints}.
\item \strong{WHONET} as a source for machine-reading clinical breakpoints ((read more here)\link{https://msberends.github.io/AMR/reference/clinical_breakpoints.html#imported-from-whonet}), 1989-2024, \emph{WHO Collaborating Centre for Surveillance of Antimicrobial Resistance}. \url{https://whonet.org/}.
}
}
\usage{
@ -259,10 +260,10 @@ summary(example_isolates) # see all SIR results at a glance
# example data sets, with combined MIC values and disk zones
df_wide <- data.frame(
microorganism = "Escherichia coli",
AMP = as.mic(8),
CIP = as.mic(0.256),
GEN = as.disk(18),
TOB = as.disk(16),
amoxicillin = as.mic(8),
cipro = as.mic(0.256),
tobra = as.disk(16),
genta = as.disk(18),
ERY = "R"
)
df_long <- data.frame(
@ -279,8 +280,8 @@ if (require("dplyr")) {
df_wide \%>\% mutate_if(is.mic, as.sir)
df_wide \%>\% mutate_if(function(x) is.mic(x) | is.disk(x), as.sir)
df_wide \%>\% mutate(across(where(is.mic), as.sir))
df_wide \%>\% mutate_at(vars(AMP:TOB), as.sir)
df_wide \%>\% mutate(across(AMP:TOB, as.sir))
df_wide \%>\% mutate_at(vars(amoxicillin:tobra), as.sir)
df_wide \%>\% mutate(across(amoxicillin:tobra, as.sir))
# approaches that all work with additional arguments:
df_long \%>\%
@ -295,17 +296,15 @@ if (require("dplyr")) {
mo = "bacteria",
ab = "antibiotic",
guideline = "CLSI")))
df_long \%>\%
df_wide \%>\%
# given certain columns, e.g. from 'cipro' to 'genta'
mutate_at(vars(cipro:genta), as.sir,
mo = "bacteria",
ab = "antibiotic",
guideline = "CLSI")
df_long \%>\%
df_wide \%>\%
mutate(across(cipro:genta,
function(x) as.sir(x,
mo = "bacteria",
ab = "antibiotic",
guideline = "CLSI")))
# for veterinary breakpoints, add 'host':
@ -324,18 +323,16 @@ if (require("dplyr")) {
ab = "antibiotic",
host = "animal_species",
guideline = "CLSI")))
df_long \%>\%
# given certain columns, e.g. from AMP to TOB
df_wide \%>\%
mutate_at(vars(cipro:genta), as.sir,
mo = "bacteria",
ab = "antibiotic",
host = "animal_species",
guideline = "CLSI")
df_long \%>\%
df_wide \%>\%
mutate(across(cipro:genta,
function(x) as.sir(x,
mo = "bacteria",
ab = "antibiotic",
host = "animal_species",
guideline = "CLSI")))