mirror of
https://github.com/msberends/AMR.git
synced 2025-07-18 02:04:42 +02:00
(v2.1.1.9163) cleanup
This commit is contained in:
@ -183,7 +183,7 @@ Code example:
|
||||
\if{html}{\out{<div class="sourceCode r">}}\preformatted{antibiogram(your_data,
|
||||
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
|
||||
wisca = TRUE)
|
||||
|
||||
|
||||
# this is equal to:
|
||||
wisca(your_data,
|
||||
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
|
||||
@ -343,12 +343,14 @@ antibiogram(example_isolates,
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = aminoglycosides(),
|
||||
ab_transform = "atc",
|
||||
mo_transform = "gramstain")
|
||||
mo_transform = "gramstain"
|
||||
)
|
||||
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = carbapenems(),
|
||||
ab_transform = "name",
|
||||
mo_transform = "name")
|
||||
mo_transform = "name"
|
||||
)
|
||||
|
||||
|
||||
# Combined antibiogram -------------------------------------------------
|
||||
@ -356,14 +358,16 @@ antibiogram(example_isolates,
|
||||
# combined antibiotics yield higher empiric coverage
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
|
||||
mo_transform = "gramstain")
|
||||
mo_transform = "gramstain"
|
||||
)
|
||||
|
||||
# names of antibiotics do not need to resemble columns exactly:
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c("Cipro", "cipro + genta"),
|
||||
mo_transform = "gramstain",
|
||||
ab_transform = "name",
|
||||
sep = " & ")
|
||||
sep = " & "
|
||||
)
|
||||
|
||||
|
||||
# Syndromic antibiogram ------------------------------------------------
|
||||
@ -371,7 +375,8 @@ antibiogram(example_isolates,
|
||||
# the data set could contain a filter for e.g. respiratory specimens
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c(aminoglycosides(), carbapenems()),
|
||||
syndromic_group = "ward")
|
||||
syndromic_group = "ward"
|
||||
)
|
||||
|
||||
# now define a data set with only E. coli
|
||||
ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
|
||||
@ -384,7 +389,8 @@ antibiogram(ex1,
|
||||
syndromic_group = ifelse(ex1$ward == "ICU",
|
||||
"UCI", "No UCI"
|
||||
),
|
||||
language = "es")
|
||||
language = "es"
|
||||
)
|
||||
|
||||
|
||||
# WISCA antibiogram ----------------------------------------------------
|
||||
@ -393,7 +399,8 @@ antibiogram(ex1,
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
|
||||
syndromic_group = "ward",
|
||||
wisca = TRUE)
|
||||
wisca = TRUE
|
||||
)
|
||||
|
||||
|
||||
# Print the output for R Markdown / Quarto -----------------------------
|
||||
@ -401,7 +408,8 @@ antibiogram(example_isolates,
|
||||
ureido <- antibiogram(example_isolates,
|
||||
antibiotics = ureidopenicillins(),
|
||||
syndromic_group = "ward",
|
||||
wisca = TRUE)
|
||||
wisca = TRUE
|
||||
)
|
||||
|
||||
# in an Rmd file, you would just need to return `ureido` in a chunk,
|
||||
# but to be explicit here:
|
||||
@ -414,11 +422,13 @@ if (requireNamespace("knitr")) {
|
||||
|
||||
ab1 <- antibiogram(example_isolates,
|
||||
antibiotics = c("AMC", "CIP", "TZP", "TZP+TOB"),
|
||||
mo_transform = "gramstain")
|
||||
mo_transform = "gramstain"
|
||||
)
|
||||
ab2 <- antibiogram(example_isolates,
|
||||
antibiotics = c("AMC", "CIP", "TZP", "TZP+TOB"),
|
||||
mo_transform = "gramstain",
|
||||
syndromic_group = "ward")
|
||||
syndromic_group = "ward"
|
||||
)
|
||||
|
||||
if (requireNamespace("ggplot2")) {
|
||||
ggplot2::autoplot(ab1)
|
||||
|
||||
@ -2,8 +2,6 @@
|
||||
% Please edit documentation in R/amr_selectors.R
|
||||
\name{antimicrobial_selectors}
|
||||
\alias{antimicrobial_selectors}
|
||||
\alias{amr_class}
|
||||
\alias{amr_selector}
|
||||
\alias{aminoglycosides}
|
||||
\alias{aminopenicillins}
|
||||
\alias{antifungals}
|
||||
@ -35,17 +33,13 @@
|
||||
\alias{tetracyclines}
|
||||
\alias{trimethoprims}
|
||||
\alias{ureidopenicillins}
|
||||
\alias{amr_class}
|
||||
\alias{amr_selector}
|
||||
\alias{administrable_per_os}
|
||||
\alias{administrable_iv}
|
||||
\alias{not_intrinsic_resistant}
|
||||
\title{Antimicrobial Selectors}
|
||||
\usage{
|
||||
amr_class(amr_class, only_sir_columns = FALSE, only_treatable = TRUE,
|
||||
return_all = TRUE, ...)
|
||||
|
||||
amr_selector(filter, only_sir_columns = FALSE, only_treatable = TRUE,
|
||||
return_all = TRUE, ...)
|
||||
|
||||
aminoglycosides(only_sir_columns = FALSE, only_treatable = TRUE,
|
||||
return_all = TRUE, ...)
|
||||
|
||||
@ -114,6 +108,12 @@ trimethoprims(only_sir_columns = FALSE, return_all = TRUE, ...)
|
||||
|
||||
ureidopenicillins(only_sir_columns = FALSE, return_all = TRUE, ...)
|
||||
|
||||
amr_class(amr_class, only_sir_columns = FALSE, only_treatable = TRUE,
|
||||
return_all = TRUE, ...)
|
||||
|
||||
amr_selector(filter, only_sir_columns = FALSE, only_treatable = TRUE,
|
||||
return_all = TRUE, ...)
|
||||
|
||||
administrable_per_os(only_sir_columns = FALSE, return_all = TRUE, ...)
|
||||
|
||||
administrable_iv(only_sir_columns = FALSE, return_all = TRUE, ...)
|
||||
@ -122,8 +122,6 @@ not_intrinsic_resistant(only_sir_columns = FALSE, col_mo = NULL,
|
||||
version_expertrules = 3.3, ...)
|
||||
}
|
||||
\arguments{
|
||||
\item{amr_class}{an antimicrobial class or a part of it, such as \code{"carba"} and \code{"carbapenems"}. The columns \code{group}, \code{atc_group1} and \code{atc_group2} of the \link{antibiotics} data set will be searched (case-insensitive) for this value.}
|
||||
|
||||
\item{only_sir_columns}{a \link{logical} to indicate whether only columns of class \code{sir} must be selected (default is \code{FALSE}), see \code{\link[=as.sir]{as.sir()}}}
|
||||
|
||||
\item{only_treatable}{a \link{logical} to indicate whether antimicrobial drugs should be excluded that are only for laboratory tests (default is \code{TRUE}), such as gentamicin-high (\code{GEH}) and imipenem/EDTA (\code{IPE})}
|
||||
@ -132,6 +130,8 @@ not_intrinsic_resistant(only_sir_columns = FALSE, col_mo = NULL,
|
||||
|
||||
\item{...}{ignored, only in place to allow future extensions}
|
||||
|
||||
\item{amr_class}{an antimicrobial class or a part of it, such as \code{"carba"} and \code{"carbapenems"}. The columns \code{group}, \code{atc_group1} and \code{atc_group2} of the \link{antibiotics} data set will be searched (case-insensitive) for this value.}
|
||||
|
||||
\item{filter}{an \link{expression} to be evaluated in the \link{antibiotics} data set, such as \code{name \%like\% "trim"}}
|
||||
|
||||
\item{col_mo}{column name of the names or codes of the microorganisms (see \code{\link[=as.mo]{as.mo()}}) - the default is the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
|
||||
@ -160,10 +160,10 @@ All columns in the data in which these functions are called will be searched for
|
||||
|
||||
The \code{\link[=amr_class]{amr_class()}} function can be used to filter/select on a manually defined antimicrobial class. It searches for results in the \link{antibiotics} data set within the columns \code{group}, \code{atc_group1} and \code{atc_group2}.
|
||||
|
||||
The \code{\link[=amr_selector]{amr_selector()}} function can be used to internally filter the \link{antibiotics} data set on any results, see \emph{Examples}. It allows for filtering on a (part of) a certain name, and/or a group name or even a minimum of DDDs for oral treatment. This function yields the highest flexibility, but is also the least user-friendly, since it requires a hard-coded filter to set.
|
||||
|
||||
The \code{\link[=administrable_per_os]{administrable_per_os()}} and \code{\link[=administrable_iv]{administrable_iv()}} functions also rely on the \link{antibiotics} data set - antimicrobials will be matched where a DDD (defined daily dose) for resp. oral and IV treatment is available in the \link{antibiotics} data set.
|
||||
|
||||
The \code{\link[=amr_selector]{amr_selector()}} function can be used to internally filter the \link{antibiotics} data set on any results, see \emph{Examples}. It allows for filtering on a (part of) a certain name, and/or a group name or even a minimum of DDDs for oral treatment. This function yields the highest flexibility, but is also the least user-friendly, since it requires a hard-coded filter to set.
|
||||
|
||||
The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function can be used to only select antimicrobials that pose no intrinsic resistance for the microorganisms in the data set. For example, if a data set contains only microorganism codes or names of \emph{E. coli} and \emph{K. pneumoniae} and contains a column "vancomycin", this column will be removed (or rather, unselected) using this function. It currently applies \href{https://www.eucast.org/expert_rules_and_expected_phenotypes}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021) to determine intrinsic resistance, using the \code{\link[=eucast_rules]{eucast_rules()}} function internally. Because of this determination, this function is quite slow in terms of performance.
|
||||
}
|
||||
\section{Full list of supported (antimicrobial) classes}{
|
||||
|
||||
112
man/as.sir.Rd
112
man/as.sir.Rd
@ -258,69 +258,97 @@ if (require("dplyr")) {
|
||||
df_wide \%>\% mutate(across(where(is.mic), 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 \%>\%
|
||||
# given a certain data type, e.g. MIC values
|
||||
mutate_if(is.mic, as.sir,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
guideline = "CLSI")
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
df_long \%>\%
|
||||
mutate(across(where(is.mic),
|
||||
function(x) as.sir(x,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
guideline = "CLSI")))
|
||||
mutate(across(
|
||||
where(is.mic),
|
||||
function(x) {
|
||||
as.sir(x,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
}
|
||||
))
|
||||
df_wide \%>\%
|
||||
# given certain columns, e.g. from 'cipro' to 'genta'
|
||||
mutate_at(vars(cipro:genta), as.sir,
|
||||
mo = "bacteria",
|
||||
guideline = "CLSI")
|
||||
mo = "bacteria",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
df_wide \%>\%
|
||||
mutate(across(cipro:genta,
|
||||
function(x) as.sir(x,
|
||||
mo = "bacteria",
|
||||
guideline = "CLSI")))
|
||||
|
||||
mutate(across(
|
||||
cipro:genta,
|
||||
function(x) {
|
||||
as.sir(x,
|
||||
mo = "bacteria",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
}
|
||||
))
|
||||
|
||||
# for veterinary breakpoints, add 'host':
|
||||
df_long$animal_species <- c("cats", "dogs", "horses", "cattle")
|
||||
df_long \%>\%
|
||||
# given a certain data type, e.g. MIC values
|
||||
mutate_if(is.mic, as.sir,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI")
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
df_long \%>\%
|
||||
mutate(across(where(is.mic),
|
||||
function(x) as.sir(x,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI")))
|
||||
mutate(across(
|
||||
where(is.mic),
|
||||
function(x) {
|
||||
as.sir(x,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
}
|
||||
))
|
||||
df_wide \%>\%
|
||||
mutate_at(vars(cipro:genta), as.sir,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI")
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
df_wide \%>\%
|
||||
mutate(across(cipro:genta,
|
||||
function(x) as.sir(x,
|
||||
mo = "bacteria",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI")))
|
||||
|
||||
mutate(across(
|
||||
cipro:genta,
|
||||
function(x) {
|
||||
as.sir(x,
|
||||
mo = "bacteria",
|
||||
host = "animal_species",
|
||||
guideline = "CLSI"
|
||||
)
|
||||
}
|
||||
))
|
||||
|
||||
# to include information about urinary tract infections (UTI)
|
||||
data.frame(mo = "E. coli",
|
||||
nitrofuratoin = c("<= 2", 32),
|
||||
from_the_bladder = c(TRUE, FALSE)) \%>\%
|
||||
data.frame(
|
||||
mo = "E. coli",
|
||||
nitrofuratoin = c("<= 2", 32),
|
||||
from_the_bladder = c(TRUE, FALSE)
|
||||
) \%>\%
|
||||
as.sir(uti = "from_the_bladder")
|
||||
|
||||
data.frame(mo = "E. coli",
|
||||
nitrofuratoin = c("<= 2", 32),
|
||||
specimen = c("urine", "blood")) \%>\%
|
||||
data.frame(
|
||||
mo = "E. coli",
|
||||
nitrofuratoin = c("<= 2", 32),
|
||||
specimen = c("urine", "blood")
|
||||
) \%>\%
|
||||
as.sir() # automatically determines urine isolates
|
||||
|
||||
df_wide \%>\%
|
||||
|
||||
@ -81,7 +81,7 @@ Rules can also be applied to multiple antibiotics and antibiotic groups simultan
|
||||
\if{html}{\out{<div class="sourceCode r">}}\preformatted{x <- custom_eucast_rules(TZP == "R" ~ c(aminopenicillins, ureidopenicillins) == "R")
|
||||
x
|
||||
#> A set of custom EUCAST rules:
|
||||
#>
|
||||
#>
|
||||
#> 1. If TZP is "R" then set to "R":
|
||||
#> amoxicillin (AMX), ampicillin (AMP), azlocillin (AZL), mezlocillin (MEZ), piperacillin (PIP), piperacillin/tazobactam (TZP)
|
||||
}\if{html}{\out{</div>}}
|
||||
|
||||
@ -139,8 +139,10 @@ if (require("ggplot2") && require("dplyr")) {
|
||||
) \%>\%
|
||||
ggplot() +
|
||||
geom_col(aes(x = x, y = y, fill = z)) +
|
||||
scale_sir_colours(aesthetics = "fill",
|
||||
Value4 = "S", Value5 = "I", Value6 = "R")
|
||||
scale_sir_colours(
|
||||
aesthetics = "fill",
|
||||
Value4 = "S", Value5 = "I", Value6 = "R"
|
||||
)
|
||||
}
|
||||
if (require("ggplot2") && require("dplyr")) {
|
||||
# resistance of ciprofloxacine per age group
|
||||
|
||||
@ -262,10 +262,12 @@ mo_rank("Klebsiella pneumoniae")
|
||||
mo_url("Klebsiella pneumoniae")
|
||||
mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
|
||||
|
||||
mo_group_members(c("Streptococcus group A",
|
||||
"Streptococcus group C",
|
||||
"Streptococcus group G",
|
||||
"Streptococcus group L"))
|
||||
mo_group_members(c(
|
||||
"Streptococcus group A",
|
||||
"Streptococcus group C",
|
||||
"Streptococcus group G",
|
||||
"Streptococcus group L"
|
||||
))
|
||||
|
||||
|
||||
# scientific reference -----------------------------------------------------
|
||||
|
||||
74
man/plot.Rd
74
man/plot.Rd
@ -201,7 +201,6 @@ some_mic_values <- random_mic(size = 100)
|
||||
some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
|
||||
some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))
|
||||
|
||||
|
||||
\donttest{
|
||||
# Plotting using ggplot2's autoplot() for MIC, disk, and SIR -----------
|
||||
if (require("ggplot2")) {
|
||||
@ -213,17 +212,23 @@ if (require("ggplot2")) {
|
||||
}
|
||||
if (require("ggplot2")) {
|
||||
# support for 20 languages, various guidelines, and many options
|
||||
autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro",
|
||||
guideline = "CLSI 2024", language = "no",
|
||||
title = "Disk diffusion from the North")
|
||||
autoplot(some_disk_values,
|
||||
mo = "Escherichia coli", ab = "cipro",
|
||||
guideline = "CLSI 2024", language = "no",
|
||||
title = "Disk diffusion from the North"
|
||||
)
|
||||
}
|
||||
|
||||
|
||||
# Plotting using scale_x_mic() -----------------------------------------
|
||||
if (require("ggplot2")) {
|
||||
mic_plot <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
|
||||
counts = c(1, 1, 2, 2, 3, 3)),
|
||||
aes(mics, counts)) +
|
||||
mic_plot <- ggplot(
|
||||
data.frame(
|
||||
mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
|
||||
counts = c(1, 1, 2, 2, 3, 3)
|
||||
),
|
||||
aes(mics, counts)
|
||||
) +
|
||||
geom_col()
|
||||
mic_plot +
|
||||
labs(title = "without scale_x_mic()")
|
||||
@ -254,17 +259,25 @@ if (require("ggplot2")) {
|
||||
some_groups <- sample(LETTERS[1:5], 20, replace = TRUE)
|
||||
|
||||
if (require("ggplot2")) {
|
||||
ggplot(data.frame(mic = some_mic_values,
|
||||
group = some_groups),
|
||||
aes(group, mic)) +
|
||||
ggplot(
|
||||
data.frame(
|
||||
mic = some_mic_values,
|
||||
group = some_groups
|
||||
),
|
||||
aes(group, mic)
|
||||
) +
|
||||
geom_boxplot() +
|
||||
geom_violin(linetype = 2, colour = "grey", fill = NA) +
|
||||
scale_y_mic()
|
||||
}
|
||||
if (require("ggplot2")) {
|
||||
ggplot(data.frame(mic = some_mic_values,
|
||||
group = some_groups),
|
||||
aes(group, mic)) +
|
||||
ggplot(
|
||||
data.frame(
|
||||
mic = some_mic_values,
|
||||
group = some_groups
|
||||
),
|
||||
aes(group, mic)
|
||||
) +
|
||||
geom_boxplot() +
|
||||
geom_violin(linetype = 2, colour = "grey", fill = NA) +
|
||||
scale_y_mic(mic_range = c(NA, 0.25))
|
||||
@ -273,9 +286,13 @@ if (require("ggplot2")) {
|
||||
|
||||
# Plotting using scale_x_sir() -----------------------------------------
|
||||
if (require("ggplot2")) {
|
||||
ggplot(data.frame(x = c("I", "R", "S"),
|
||||
y = c(45,323, 573)),
|
||||
aes(x, y)) +
|
||||
ggplot(
|
||||
data.frame(
|
||||
x = c("I", "R", "S"),
|
||||
y = c(45, 323, 573)
|
||||
),
|
||||
aes(x, y)
|
||||
) +
|
||||
geom_col() +
|
||||
scale_x_sir()
|
||||
}
|
||||
@ -283,16 +300,21 @@ if (require("ggplot2")) {
|
||||
|
||||
# Plotting using scale_y_mic() and scale_colour_sir() ------------------
|
||||
if (require("ggplot2")) {
|
||||
plain <- ggplot(data.frame(mic = some_mic_values,
|
||||
group = some_groups,
|
||||
sir = as.sir(some_mic_values,
|
||||
mo = "E. coli",
|
||||
ab = "cipro")),
|
||||
aes(x = group, y = mic, colour = sir)) +
|
||||
plain <- ggplot(
|
||||
data.frame(
|
||||
mic = some_mic_values,
|
||||
group = some_groups,
|
||||
sir = as.sir(some_mic_values,
|
||||
mo = "E. coli",
|
||||
ab = "cipro"
|
||||
)
|
||||
),
|
||||
aes(x = group, y = mic, colour = sir)
|
||||
) +
|
||||
theme_minimal() +
|
||||
geom_boxplot(fill = NA, colour = "grey") +
|
||||
geom_jitter(width = 0.25)
|
||||
|
||||
|
||||
plain
|
||||
}
|
||||
if (require("ggplot2")) {
|
||||
@ -304,8 +326,10 @@ if (require("ggplot2")) {
|
||||
if (require("ggplot2")) {
|
||||
plain +
|
||||
scale_y_mic(mic_range = c(0.005, 32), name = "Our MICs!") +
|
||||
scale_colour_sir(language = "pt",
|
||||
name = "Support in 20 languages")
|
||||
scale_colour_sir(
|
||||
language = "pt",
|
||||
name = "Support in 20 languages"
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -29,15 +29,18 @@ This function is useful for preprocessing data before creating \link[=antibiogra
|
||||
\examples{
|
||||
# filter to the top 3 species:
|
||||
top_n_microorganisms(example_isolates,
|
||||
n = 3)
|
||||
n = 3
|
||||
)
|
||||
|
||||
# filter to any species in the top 5 genera:
|
||||
top_n_microorganisms(example_isolates,
|
||||
n = 5, property = "genus")
|
||||
n = 5, property = "genus"
|
||||
)
|
||||
|
||||
# filter to the top 3 species in each of the top 5 genera:
|
||||
top_n_microorganisms(example_isolates,
|
||||
n = 5, property = "genus", n_for_each = 3)
|
||||
n = 5, property = "genus", n_for_each = 3
|
||||
)
|
||||
}
|
||||
\seealso{
|
||||
\code{\link[=mo_property]{mo_property()}}, \code{\link[=as.mo]{as.mo()}}, \code{\link[=antibiogram]{antibiogram()}}
|
||||
|
||||
Reference in New Issue
Block a user