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Adhering to previously described approaches (see Source) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki et al., these functions provides flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports.">< meta property = "og:description" content = "Create detailed antibiograms with options for traditional , combination , syndromic , and Bayesian WISCA methods .
Adhering to previously described approaches (see Source) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki et al., these functions provides flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports.">< meta property = "og:image" content = "https://msberends.github.io/AMR/logo.svg" > < / head > < body >
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< ul class = "dropdown-menu" aria-labelledby = "dropdown-how-to" > < li > < a class = "dropdown-item" href = "../articles/AMR.html" > < span class = "fa fa-directions" > < / span > Conduct AMR Analysis< / a > < / li >
< li > < a class = "dropdown-item" href = "../reference/antibiogram.html" > < span class = "fa fa-file-prescription" > < / span > Generate Antibiogram (Trad./Syndromic/WISCA)< / a > < / li >
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< li > < a class = "dropdown-item" href = "../reference/ab_property.html" > < span class = "fa fa-capsules" > < / span > Get Properties of an Antibiotic Drug< / a > < / li >
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< img src = "../logo.svg" class = "logo" alt = "" > < h1 > Generate Traditional, Combination, Syndromic, or WISCA Antibiograms< / h1 >
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< small class = "dont-index" > Source: < a href = "https://github.com/msberends/AMR/blob/main/R/antibiogram.R" class = "external-link" > < code > R/antibiogram.R< / code > < / a > < / small >
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< div class = "d-none name" > < code > antibiogram.Rd< / code > < / div >
< / div >
< div class = "ref-description section level2" >
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< p > Create detailed antibiograms with options for traditional, combination, syndromic, and Bayesian WISCA methods.< / p >
< p > Adhering to previously described approaches (see < em > Source< / em > ) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki < em > et al.< / em > , these functions provides flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports.< / p >
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< / div >
< div class = "section level2" >
< h2 id = "ref-usage" > Usage< a class = "anchor" aria-label = "anchor" href = "#ref-usage" > < / a > < / h2 >
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< div class = "sourceCode" > < pre class = "sourceCode r" > < code > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > x< / span > , antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://tidyselect.r-lib.org/reference/where.html" class = "external-link" > where< / a > < / span > < span class = "op" > (< / span > < span class = "va" > is.sir< / span > < span class = "op" > )< / span > , mo_transform < span class = "op" > =< / span > < span class = "st" > "shortname"< / span > ,< / span >
< span > ab_transform < span class = "op" > =< / span > < span class = "st" > "name"< / span > , syndromic_group < span class = "op" > =< / span > < span class = "cn" > NULL< / span > , add_total_n < span class = "op" > =< / span > < span class = "cn" > FALSE< / span > ,< / span >
< span > only_all_tested < span class = "op" > =< / span > < span class = "cn" > FALSE< / span > , digits < span class = "op" > =< / span > < span class = "fl" > 0< / span > ,< / span >
< span > formatting_type < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/options.html" class = "external-link" > getOption< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "AMR_antibiogram_formatting_type"< / span > ,< / span >
< span > < span class = "fu" > < a href = "https://rdrr.io/r/base/ifelse.html" class = "external-link" > ifelse< / a > < / span > < span class = "op" > (< / span > < span class = "va" > wisca< / span > , < span class = "fl" > 18< / span > , < span class = "fl" > 10< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > , col_mo < span class = "op" > =< / span > < span class = "cn" > NULL< / span > , language < span class = "op" > =< / span > < span class = "fu" > < a href = "translate.html" > get_AMR_locale< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > ,< / span >
< span > minimum < span class = "op" > =< / span > < span class = "fl" > 30< / span > , combine_SI < span class = "op" > =< / span > < span class = "cn" > TRUE< / span > , sep < span class = "op" > =< / span > < span class = "st" > " + "< / span > , wisca < span class = "op" > =< / span > < span class = "cn" > FALSE< / span > ,< / span >
< span > simulations < span class = "op" > =< / span > < span class = "fl" > 1000< / span > , conf_interval < span class = "op" > =< / span > < span class = "fl" > 0.95< / span > , interval_side < span class = "op" > =< / span > < span class = "st" > "two-tailed"< / span > ,< / span >
< span > info < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/interactive.html" class = "external-link" > interactive< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < / span >
< span > < / span >
< span > < span class = "fu" > wisca< / span > < span class = "op" > (< / span > < span class = "va" > x< / span > , antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://tidyselect.r-lib.org/reference/where.html" class = "external-link" > where< / a > < / span > < span class = "op" > (< / span > < span class = "va" > is.sir< / span > < span class = "op" > )< / span > , mo_transform < span class = "op" > =< / span > < span class = "st" > "shortname"< / span > ,< / span >
< span > ab_transform < span class = "op" > =< / span > < span class = "st" > "name"< / span > , syndromic_group < span class = "op" > =< / span > < span class = "cn" > NULL< / span > , add_total_n < span class = "op" > =< / span > < span class = "cn" > FALSE< / span > ,< / span >
< span > only_all_tested < span class = "op" > =< / span > < span class = "cn" > FALSE< / span > , digits < span class = "op" > =< / span > < span class = "fl" > 0< / span > ,< / span >
< span > formatting_type < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/options.html" class = "external-link" > getOption< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "AMR_antibiogram_formatting_type"< / span > , < span class = "fl" > 18< / span > < span class = "op" > )< / span > ,< / span >
< span > col_mo < span class = "op" > =< / span > < span class = "cn" > NULL< / span > , language < span class = "op" > =< / span > < span class = "fu" > < a href = "translate.html" > get_AMR_locale< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > , minimum < span class = "op" > =< / span > < span class = "fl" > 30< / span > ,< / span >
< span > combine_SI < span class = "op" > =< / span > < span class = "cn" > TRUE< / span > , sep < span class = "op" > =< / span > < span class = "st" > " + "< / span > , simulations < span class = "op" > =< / span > < span class = "fl" > 1000< / span > ,< / span >
< span > info < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/interactive.html" class = "external-link" > interactive< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < / span >
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< span > < / span >
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< span > < span class = "co" > # S3 method for class 'antibiogram'< / span > < / span >
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< span > < span class = "fu" > < a href = "plot.html" > plot< / a > < / span > < span class = "op" > (< / span > < span class = "va" > x< / span > , < span class = "va" > ...< / span > < span class = "op" > )< / span > < / span >
< span > < / span >
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< span > < span class = "co" > # S3 method for class 'antibiogram'< / span > < / span >
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< span > < span class = "fu" > < a href = "https://ggplot2.tidyverse.org/reference/autoplot.html" class = "external-link" > autoplot< / a > < / span > < span class = "op" > (< / span > < span class = "va" > object< / span > , < span class = "va" > ...< / span > < span class = "op" > )< / span > < / span >
< span > < / span >
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< span > < span class = "co" > # S3 method for class 'antibiogram'< / span > < / span >
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< span > < span class = "fu" > knit_print< / span > < span class = "op" > (< / span > < span class = "va" > x< / span > , italicise < span class = "op" > =< / span > < span class = "cn" > TRUE< / span > ,< / span >
< span > na < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/options.html" class = "external-link" > getOption< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "knitr.kable.NA"< / span > , default < span class = "op" > =< / span > < span class = "st" > ""< / span > < span class = "op" > )< / span > , < span class = "va" > ...< / span > < span class = "op" > )< / span > < / span > < / code > < / pre > < / div >
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< / div >
< div class = "section level2" >
< h2 id = "source" > Source< a class = "anchor" aria-label = "anchor" href = "#source" > < / a > < / h2 >
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< ul > < li > < p > Bielicki JA < em > et al.< / em > (2016). < strong > Selecting appropriate empirical antibiotic regimens for paediatric bloodstream infections: application of a Bayesian decision model to local and pooled antimicrobial resistance surveillance data< / strong > < em > Journal of Antimicrobial Chemotherapy< / em > 71(3); < a href = "https://doi.org/10.1093/jac/dkv397" class = "external-link" > doi:10.1093/jac/dkv397< / a > < / p > < / li >
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< li > < p > Bielicki JA < em > et al.< / em > (2020). < strong > Evaluation of the coverage of 3 antibiotic regimens for neonatal sepsis in the hospital setting across Asian countries< / strong > < em > JAMA Netw Open.< / em > 3(2):e1921124; < a href = "https://doi.org/10.1001.jamanetworkopen.2019.21124" class = "external-link" > doi:10.1001.jamanetworkopen.2019.21124< / a > < / p > < / li >
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< li > < p > Klinker KP < em > et al.< / em > (2021). < strong > Antimicrobial stewardship and antibiograms: importance of moving beyond traditional antibiograms< / strong > . < em > Therapeutic Advances in Infectious Disease< / em > , May 5;8:20499361211011373; < a href = "https://doi.org/10.1177/20499361211011373" class = "external-link" > doi:10.1177/20499361211011373< / a > < / p > < / li >
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< li > < p > Barbieri E < em > et al.< / em > (2021). < strong > Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach< / strong > < em > Antimicrobial Resistance & Infection Control< / em > May 1;10(1):74; < a href = "https://doi.org/10.1186/s13756-021-00939-2" class = "external-link" > doi:10.1186/s13756-021-00939-2< / a > < / p > < / li >
< li > < p > < strong > M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition< / strong > , 2022, < em > Clinical and Laboratory Standards Institute (CLSI)< / em > . < a href = "https://clsi.org/standards/products/microbiology/documents/m39/" class = "external-link" > https://clsi.org/standards/products/microbiology/documents/m39/< / a > .< / p > < / li >
< / ul > < / div >
< div class = "section level2" >
< h2 id = "arguments" > Arguments< a class = "anchor" aria-label = "anchor" href = "#arguments" > < / a > < / h2 >
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< dl > < dt id = "arg-x" > x< a class = "anchor" aria-label = "anchor" href = "#arg-x" > < / a > < / dt >
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< dd > < p > a < a href = "https://rdrr.io/r/base/data.frame.html" class = "external-link" > data.frame< / a > containing at least a column with microorganisms and columns with antimicrobial results (class 'sir', see < code > < a href = "as.sir.html" > as.sir()< / a > < / code > )< / p > < / dd >
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< dt id = "arg-antibiotics" > antibiotics< a class = "anchor" aria-label = "anchor" href = "#arg-antibiotics" > < / a > < / dt >
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< dd > < p > vector of any antimicrobial name or code (will be evaluated with < code > < a href = "as.ab.html" > as.ab()< / a > < / code > , column name of < code > x< / code > , or (any combinations of) < a href = "antimicrobial_class_selectors.html" > antimicrobial selectors< / a > such as < code > < a href = "antimicrobial_class_selectors.html" > aminoglycosides()< / a > < / code > or < code > < a href = "antimicrobial_class_selectors.html" > carbapenems()< / a > < / code > . For combination antibiograms, this can also be set to values separated with < code > "+"< / code > , such as "TZP+TOB" or "cipro + genta", given that columns resembling such antimicrobials exist in < code > x< / code > . See < em > Examples< / em > .< / p > < / dd >
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< dt id = "arg-mo-transform" > mo_transform< a class = "anchor" aria-label = "anchor" href = "#arg-mo-transform" > < / a > < / dt >
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< dd > < p > a character to transform microorganism input - must be < code > "name"< / code > , < code > "shortname"< / code > (default), < code > "gramstain"< / code > , or one of the column names of the < a href = "microorganisms.html" > microorganisms< / a > data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "mycobank", "mycobank_parent", "mycobank_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be < code > NULL< / code > to not transform the input.< / p > < / dd >
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< dt id = "arg-ab-transform" > ab_transform< a class = "anchor" aria-label = "anchor" href = "#arg-ab-transform" > < / a > < / dt >
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< dd > < p > a character to transform antimicrobial input - must be one of the column names of the < a href = "antibiotics.html" > antibiotics< / a > data set (defaults to < code > "name"< / code > ): "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units", or "loinc". Can also be < code > NULL< / code > to not transform the input.< / p > < / dd >
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< dt id = "arg-syndromic-group" > syndromic_group< a class = "anchor" aria-label = "anchor" href = "#arg-syndromic-group" > < / a > < / dt >
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< dd > < p > a column name of < code > x< / code > , or values calculated to split rows of < code > x< / code > , e.g. by using < code > < a href = "https://rdrr.io/r/base/ifelse.html" class = "external-link" > ifelse()< / a > < / code > or < code > < a href = "https://dplyr.tidyverse.org/reference/case_when.html" class = "external-link" > case_when()< / a > < / code > . See < em > Examples< / em > .< / p > < / dd >
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< dt id = "arg-add-total-n" > add_total_n< a class = "anchor" aria-label = "anchor" href = "#arg-add-total-n" > < / a > < / dt >
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< dd > < p > a < a href = "https://rdrr.io/r/base/logical.html" class = "external-link" > logical< / a > to indicate whether total available numbers per pathogen should be added to the table (default is < code > TRUE< / code > ). This will add the lowest and highest number of available isolates per antimicrobial (e.g, if for < em > E. coli< / em > 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200").< / p > < / dd >
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< dt id = "arg-only-all-tested" > only_all_tested< a class = "anchor" aria-label = "anchor" href = "#arg-only-all-tested" > < / a > < / dt >
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< dd > < p > (for combination antibiograms): a < a href = "https://rdrr.io/r/base/logical.html" class = "external-link" > logical< / a > to indicate that isolates must be tested for all antimicrobials, see < em > Details< / em > < / p > < / dd >
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< dt id = "arg-digits" > digits< a class = "anchor" aria-label = "anchor" href = "#arg-digits" > < / a > < / dt >
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< dd > < p > number of digits to use for rounding the susceptibility percentage< / p > < / dd >
< dt id = "arg-formatting-type" > formatting_type< a class = "anchor" aria-label = "anchor" href = "#arg-formatting-type" > < / a > < / dt >
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< dd > < p > numeric value (1– < em > Details< / em > > < em > Formatting Type< / em > for a list of options.< / p > < / dd >
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< dt id = "arg-col-mo" > col_mo< a class = "anchor" aria-label = "anchor" href = "#arg-col-mo" > < / a > < / dt >
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< dd > < p > column name of the names or codes of the microorganisms (see < code > < a href = "as.mo.html" > as.mo()< / a > < / code > ) - the default is the first column of class < code > < a href = "as.mo.html" > mo< / a > < / code > . Values will be coerced using < code > < a href = "as.mo.html" > as.mo()< / a > < / code > .< / p > < / dd >
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< dt id = "arg-language" > language< a class = "anchor" aria-label = "anchor" href = "#arg-language" > < / a > < / dt >
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< dd > < p > language to translate text, which defaults to the system language (see < code > < a href = "translate.html" > get_AMR_locale()< / a > < / code > )< / p > < / dd >
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< dt id = "arg-minimum" > minimum< a class = "anchor" aria-label = "anchor" href = "#arg-minimum" > < / a > < / dt >
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< dd > < p > the minimum allowed number of available (tested) isolates. Any isolate count lower than < code > minimum< / code > will return < code > NA< / code > with a warning. The default number of < code > 30< / code > isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see < em > Source< / em > .< / p > < / dd >
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< dt id = "arg-combine-si" > combine_SI< a class = "anchor" aria-label = "anchor" href = "#arg-combine-si" > < / a > < / dt >
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< dd > < p > a < a href = "https://rdrr.io/r/base/logical.html" class = "external-link" > logical< / a > to indicate whether all susceptibility should be determined by results of either S, SDD, or I, instead of only S (default is < code > TRUE< / code > )< / p > < / dd >
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< dt id = "arg-sep" > sep< a class = "anchor" aria-label = "anchor" href = "#arg-sep" > < / a > < / dt >
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< dd > < p > a separating character for antimicrobial columns in combination antibiograms< / p > < / dd >
< dt id = "arg-wisca" > wisca< a class = "anchor" aria-label = "anchor" href = "#arg-wisca" > < / a > < / dt >
< dd > < p > a < a href = "https://rdrr.io/r/base/logical.html" class = "external-link" > logical< / a > to indicate whether a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) must be generated (default is < code > FALSE< / code > ). This will use a Bayesian hierarchical model to estimate regimen coverage probabilities using Montecarlo simulations. Set < code > simulations< / code > to adjust.< / p > < / dd >
< dt id = "arg-simulations" > simulations< a class = "anchor" aria-label = "anchor" href = "#arg-simulations" > < / a > < / dt >
< dd > < p > (for WISCA) a numerical value to set the number of Montecarlo simulations< / p > < / dd >
< dt id = "arg-conf-interval" > conf_interval< a class = "anchor" aria-label = "anchor" href = "#arg-conf-interval" > < / a > < / dt >
< dd > < p > (for WISCA) a numerical value to set confidence interval (default is < code > 0.95< / code > )< / p > < / dd >
< dt id = "arg-interval-side" > interval_side< a class = "anchor" aria-label = "anchor" href = "#arg-interval-side" > < / a > < / dt >
< dd > < p > (for WISCA) the side of the confidence interval, either < code > "two-tailed"< / code > (default), < code > "left"< / code > or < code > "right"< / code > < / p > < / dd >
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< dt id = "arg-info" > info< a class = "anchor" aria-label = "anchor" href = "#arg-info" > < / a > < / dt >
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< dd > < p > a < a href = "https://rdrr.io/r/base/logical.html" class = "external-link" > logical< / a > to indicate info should be printed - the default is < code > TRUE< / code > only in interactive mode< / p > < / dd >
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< dt id = "arg--" > ...< a class = "anchor" aria-label = "anchor" href = "#arg--" > < / a > < / dt >
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< dd > < p > when used in < a href = "https://rdrr.io/pkg/knitr/man/kable.html" class = "external-link" > R Markdown or Quarto< / a > : arguments passed on to < code > < a href = "https://rdrr.io/pkg/knitr/man/kable.html" class = "external-link" > knitr::kable()< / a > < / code > (otherwise, has no use)< / p > < / dd >
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< dt id = "arg-object" > object< a class = "anchor" aria-label = "anchor" href = "#arg-object" > < / a > < / dt >
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< dd > < p > an < code > antibiogram()< / code > object< / p > < / dd >
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< dt id = "arg-italicise" > italicise< a class = "anchor" aria-label = "anchor" href = "#arg-italicise" > < / a > < / dt >
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< dd > < p > a < a href = "https://rdrr.io/r/base/logical.html" class = "external-link" > logical< / a > to indicate whether the microorganism names in the < a href = "https://rdrr.io/pkg/knitr/man/kable.html" class = "external-link" > knitr< / a > table should be made italic, using < code > < a href = "italicise_taxonomy.html" > italicise_taxonomy()< / a > < / code > .< / p > < / dd >
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< dt id = "arg-na" > na< a class = "anchor" aria-label = "anchor" href = "#arg-na" > < / a > < / dt >
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< dd > < p > character to use for showing < code > NA< / code > values< / p > < / dd >
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< / dl > < / div >
< div class = "section level2" >
< h2 id = "details" > Details< a class = "anchor" aria-label = "anchor" href = "#details" > < / a > < / h2 >
< p > This function returns a table with values between 0 and 100 for < em > susceptibility< / em > , not resistance.< / p >
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< p > < strong > Remember that you should filter your data to let it contain only first isolates!< / strong > This is needed to exclude duplicates and to reduce selection bias. Use < code > < a href = "first_isolate.html" > first_isolate()< / a > < / code > to determine them in your data set with one of the four available algorithms.< / p >
< p > For estimating antimicrobial coverage, especially when creating a WISCA, the outcome might become more reliable by only including the top < em > n< / em > species encountered in the data. You can filter on this top < em > n< / em > using < code > < a href = "top_n_microorganisms.html" > top_n_microorganisms()< / a > < / code > . For example, use < code > top_n_microorganisms(your_data, n = 10)< / code > as a pre-processing step to only include the top 10 species in the data.< / p >
< p > The numeric values of an antibiogram are stored in a long format as the < a href = "https://rdrr.io/r/base/attributes.html" class = "external-link" > attribute< / a > < code > long_numeric< / code > . You can retrieve them using < code > attributes(x)$long_numeric< / code > , where < code > x< / code > is the outcome of < code > antibiogram()< / code > or < code > wisca()< / code > . This is ideal for e.g. advanced plotting.< / p > < div class = "section" >
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< h3 id = "formatting-type" > Formatting Type< a class = "anchor" aria-label = "anchor" href = "#formatting-type" > < / a > < / h3 >
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< p > The formatting of the 'cells' of the table can be set with the argument < code > formatting_type< / code > . In these examples, < code > 5< / code > is the susceptibility percentage (for WISCA: < code > 4-6< / code > indicates the confidence level), < code > 15< / code > the numerator, and < code > 300< / code > the denominator:< / p > < ol > < li > < p > 5< / p > < / li >
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< li > < p > 15< / p > < / li >
< li > < p > 300< / p > < / li >
< li > < p > 15/300< / p > < / li >
< li > < p > 5 (300)< / p > < / li >
< li > < p > 5% (300)< / p > < / li >
< li > < p > 5 (N=300)< / p > < / li >
< li > < p > 5% (N=300)< / p > < / li >
< li > < p > 5 (15/300)< / p > < / li >
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< li > < p > 5% (15/300) - < strong > default for non-WISCA< / strong > < / p > < / li >
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< li > < p > 5 (N=15/300)< / p > < / li >
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< li > < p > 5% (N=15/300)< / p >
< p > Additional options for WISCA (using < code > antibiogram(..., wisca = TRUE)< / code > or < code > wisca()< / code > ):< / p > < / li >
< li > < p > 5 (4-6)< / p > < / li >
< li > < p > 5% (4-6%)< / p > < / li >
< li > < p > 5 (4-6,300)< / p > < / li >
< li > < p > 5% (4-6%,300)< / p > < / li >
< li > < p > 5 (4-6,N=300)< / p > < / li >
< li > < p > 5% (4-6%,N=300) - < strong > default for WISCA< / strong > < / p > < / li >
< li > < p > 5 (4-6,15/300)< / p > < / li >
< li > < p > 5% (4-6%,15/300)< / p > < / li >
< li > < p > 5 (4-6,N=15/300)< / p > < / li >
< li > < p > 5% (4-6%,N=15/300)< / p > < / li >
< / ol > < p > The default is < code > 18< / code > for WISCA and < code > 10< / code > for non-WISCA, which can be set globally with the package option < code > < a href = "AMR-options.html" > AMR_antibiogram_formatting_type< / a > < / code > , e.g. < code > options(AMR_antibiogram_formatting_type = 5)< / code > .< / p >
< p > Set < code > digits< / code > (defaults to < code > 0< / code > ) to alter the rounding of the susceptibility percentages.< / p >
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< / div >
< div class = "section" >
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< h3 id = "antibiogram-types" > Antibiogram Types< a class = "anchor" aria-label = "anchor" href = "#antibiogram-types" > < / a > < / h3 >
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< p > There are various antibiogram types, as summarised by Klinker < em > et al.< / em > (2021, < a href = "https://doi.org/10.1177/20499361211011373" class = "external-link" > doi:10.1177/20499361211011373< / a >
), and they are all supported by < code > antibiogram()< / code > .< / p >
< p > < strong > Use WISCA whenever possible< / strong > , since it provides more precise coverage estimates by accounting for pathogen incidence and antimicrobial susceptibility, as has been shown by Bielicki < em > et al.< / em > (2020, < a href = "https://doi.org/10.1001.jamanetworkopen.2019.21124" class = "external-link" > doi:10.1001.jamanetworkopen.2019.21124< / a >
). See the section < em > Why Use WISCA?< / em > on this page.< / p > < ol > < li > < p > < strong > Traditional Antibiogram< / strong > < / p >
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< p > Case example: Susceptibility of < em > Pseudomonas aeruginosa< / em > to piperacillin/tazobactam (TZP)< / p >
< p > Code example:< / p >
< p > < / p > < div class = "sourceCode r" > < pre > < code > < span > < span class = "fu" > < a href = "../reference/antibiogram.html" > antibiogram< / a > < / span > < span class = "op" > (< / span > < span class = "va" > your_data< / span > ,< / span >
< span > antibiotics < span class = "op" > =< / span > < span class = "st" > "TZP"< / span > < span class = "op" > )< / span > < / span > < / code > < / pre > < p > < / p > < / div > < / li >
< li > < p > < strong > Combination Antibiogram< / strong > < / p >
< p > Case example: Additional susceptibility of < em > Pseudomonas aeruginosa< / em > to TZP + tobramycin versus TZP alone< / p >
< p > Code example:< / p >
< p > < / p > < div class = "sourceCode r" > < pre > < code > < span > < span class = "fu" > < a href = "../reference/antibiogram.html" > antibiogram< / a > < / span > < span class = "op" > (< / span > < span class = "va" > your_data< / span > ,< / span >
< span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > , < span class = "st" > "TZP+GEN"< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < / span > < / code > < / pre > < p > < / p > < / div > < / li >
< li > < p > < strong > Syndromic Antibiogram< / strong > < / p >
< p > Case example: Susceptibility of < em > Pseudomonas aeruginosa< / em > to TZP among respiratory specimens (obtained among ICU patients only)< / p >
< p > Code example:< / p >
< p > < / p > < div class = "sourceCode r" > < pre > < code > < span > < span class = "fu" > < a href = "../reference/antibiogram.html" > antibiogram< / a > < / span > < span class = "op" > (< / span > < span class = "va" > your_data< / span > ,< / span >
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< span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "../reference/antimicrobial_class_selectors.html" > penicillins< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > ,< / span >
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< span > syndromic_group < span class = "op" > =< / span > < span class = "st" > "ward"< / span > < span class = "op" > )< / span > < / span > < / code > < / pre > < p > < / p > < / div > < / li >
< li > < p > < strong > Weighted-Incidence Syndromic Combination Antibiogram (WISCA)< / strong > < / p >
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< p > WISCA can be applied to any antibiogram, see the section < em > Why Use WISCA?< / em > on this page for more information.< / p >
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< p > Code example:< / p >
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< p > < / p > < div class = "sourceCode r" > < pre > < code > < span > < span class = "fu" > < a href = "../reference/antibiogram.html" > antibiogram< / a > < / span > < span class = "op" > (< / span > < span class = "va" > your_data< / span > ,< / span >
< span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > , < span class = "st" > "TZP+GEN"< / span > < span class = "op" > )< / span > ,< / span >
< span > wisca < span class = "op" > =< / span > < span class = "cn" > TRUE< / span > < span class = "op" > )< / span > < / span >
< span > < / span >
< span > < span class = "co" > # this is equal to:< / span > < / span >
< span > < span class = "fu" > < a href = "../reference/antibiogram.html" > wisca< / a > < / span > < span class = "op" > (< / span > < span class = "va" > your_data< / span > ,< / span >
< span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > , < span class = "st" > "TZP+GEN"< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < / span > < / code > < / pre > < p > < / p > < / div >
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< p > WISCA uses a sophisticated Bayesian decision model to combine both local and pooled antimicrobial resistance data. This approach not only evaluates local patterns but can also draw on multi-centre datasets to improve regimen accuracy, even in low-incidence infections like paediatric bloodstream infections (BSIs).< / p > < / li >
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< / ol > < p > Grouped < a href = "https://tibble.tidyverse.org/reference/tibble.html" class = "external-link" > tibbles< / a > can also be used to calculate susceptibilities over various groups.< / p >
< p > Code example:< / p >
< p > < / p > < div class = "sourceCode r" > < pre > < code > < span > < span class = "va" > your_data< / span > < span class = "op" > < a href = "https://magrittr.tidyverse.org/reference/pipe.html" class = "external-link" > %> %< / a > < / span > < / span >
< span > < span class = "fu" > < a href = "https://dplyr.tidyverse.org/reference/group_by.html" class = "external-link" > group_by< / a > < / span > < span class = "op" > (< / span > < span class = "va" > has_sepsis< / span > , < span class = "va" > is_neonate< / span > , < span class = "va" > sex< / span > < span class = "op" > )< / span > < span class = "op" > < a href = "https://magrittr.tidyverse.org/reference/pipe.html" class = "external-link" > %> %< / a > < / span > < / span >
< span > < span class = "fu" > < a href = "../reference/antibiogram.html" > wisca< / a > < / span > < span class = "op" > (< / span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > , < span class = "st" > "TZP+GEN"< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < / span > < / code > < / pre > < p > < / p > < / div >
< / div >
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< div class = "section" >
< h3 id = "inclusion-in-combination-antibiogram-and-syndromic-antibiogram" > Inclusion in Combination Antibiogram and Syndromic Antibiogram< a class = "anchor" aria-label = "anchor" href = "#inclusion-in-combination-antibiogram-and-syndromic-antibiogram" > < / a > < / h3 >
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< p > Note that for types 2 and 3 (Combination Antibiogram and Syndromic Antibiogram), it is important to realise that susceptibility can be calculated in two ways, which can be set with the < code > only_all_tested< / code > argument (default is < code > FALSE< / code > ). See this example for two antimicrobials, Drug A and Drug B, about how < code > antibiogram()< / code > works to calculate the %SI:< / p >
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< p > < / p > < div class = "sourceCode" > < pre > < code > < span id = "cb1-1" > < a href = "#cb1-1" tabindex = "-1" > < / a > < span class = "sc" > --------------------------------------------------------------------< / span > < / span >
< span id = "cb1-2" > < a href = "#cb1-2" tabindex = "-1" > < / a > only_all_tested < span class = "ot" > =< / span > < span class = "cn" > FALSE< / span > only_all_tested < span class = "ot" > =< / span > < span class = "cn" > TRUE< / span > < / span >
< span id = "cb1-3" > < a href = "#cb1-3" tabindex = "-1" > < / a > < span class = "sc" > -----------------------< / span > < span class = "sc" > -----------------------< / span > < / span >
< span id = "cb1-4" > < a href = "#cb1-4" tabindex = "-1" > < / a > Drug A Drug B include as include as include as include as< / span >
< span id = "cb1-5" > < a href = "#cb1-5" tabindex = "-1" > < / a > numerator denominator numerator denominator< / span >
< span id = "cb1-6" > < a href = "#cb1-6" tabindex = "-1" > < / a > < span class = "sc" > --------< / span > < span class = "sc" > --------< / span > < span class = "sc" > ----------< / span > < span class = "sc" > -----------< / span > < span class = "sc" > ----------< / span > < span class = "sc" > -----------< / span > < / span >
< span id = "cb1-7" > < a href = "#cb1-7" tabindex = "-1" > < / a > S or I S or I X X X X< / span >
< span id = "cb1-8" > < a href = "#cb1-8" tabindex = "-1" > < / a > R S or I X X X X< / span >
< span id = "cb1-9" > < a href = "#cb1-9" tabindex = "-1" > < / a > < span class = "sc" > < < / span > < span class = "cn" > NA< / span > < span class = "sc" > > < / span > S or I X X < span class = "sc" > -< / span > < span class = "sc" > -< / span > < / span >
< span id = "cb1-10" > < a href = "#cb1-10" tabindex = "-1" > < / a > S or I R X X X X< / span >
< span id = "cb1-11" > < a href = "#cb1-11" tabindex = "-1" > < / a > R R < span class = "sc" > -< / span > X < span class = "sc" > -< / span > X< / span >
< span id = "cb1-12" > < a href = "#cb1-12" tabindex = "-1" > < / a > < span class = "sc" > < < / span > < span class = "cn" > NA< / span > < span class = "sc" > > < / span > R < span class = "sc" > -< / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < / span >
< span id = "cb1-13" > < a href = "#cb1-13" tabindex = "-1" > < / a > S or I < span class = "sc" > < < / span > < span class = "cn" > NA< / span > < span class = "sc" > > < / span > X X < span class = "sc" > -< / span > < span class = "sc" > -< / span > < / span >
< span id = "cb1-14" > < a href = "#cb1-14" tabindex = "-1" > < / a > R < span class = "sc" > < < / span > < span class = "cn" > NA< / span > < span class = "sc" > > < / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < / span >
< span id = "cb1-15" > < a href = "#cb1-15" tabindex = "-1" > < / a > < span class = "er" > < < / span > < span class = "cn" > NA< / span > < span class = "sc" > > < / span > < span class = "er" > < < / span > < span class = "cn" > NA< / span > < span class = "sc" > > < / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < span class = "sc" > -< / span > < / span >
< span id = "cb1-16" > < a href = "#cb1-16" tabindex = "-1" > < / a > < span class = "sc" > --------------------------------------------------------------------< / span > < / span > < / code > < / pre > < p > < / p > < / div >
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< / div >
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< div class = "section" >
< h3 id = "plotting" > Plotting< a class = "anchor" aria-label = "anchor" href = "#plotting" > < / a > < / h3 >
< p > All types of antibiograms as listed above can be plotted (using < code > < a href = "https://ggplot2.tidyverse.org/reference/autoplot.html" class = "external-link" > ggplot2::autoplot()< / a > < / code > or base < span style = "R" > R< / span > 's < code > < a href = "plot.html" > plot()< / a > < / code > and < code > < a href = "https://rdrr.io/r/graphics/barplot.html" class = "external-link" > barplot()< / a > < / code > ).< / p >
< p > THe outcome of < code > antibiogram()< / code > can also be used directly in R Markdown / Quarto (i.e., < code > knitr< / code > ) for reports. In this case, < code > < a href = "https://rdrr.io/pkg/knitr/man/kable.html" class = "external-link" > knitr::kable()< / a > < / code > will be applied automatically and microorganism names will even be printed in italics at default (see argument < code > italicise< / code > ).< / p >
< p > You can also use functions from specific 'table reporting' packages to transform the output of < code > antibiogram()< / code > to your needs, e.g. with < code > flextable::as_flextable()< / code > or < code > gt::gt()< / code > .< / p >
< / div >
< / div >
< div class = "section level2" >
< h2 id = "why-use-wisca-" > Why Use WISCA?< a class = "anchor" aria-label = "anchor" href = "#why-use-wisca-" > < / a > < / h2 >
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< p > WISCA, as outlined by Barbieri < em > et al.< / em > (< a href = "https://doi.org/10.1186/s13756-021-00939-2" class = "external-link" > doi:10.1186/s13756-021-00939-2< / a >
), stands for
Weighted-Incidence Syndromic Combination Antibiogram, which estimates the probability
of adequate empirical antimicrobial regimen coverage for specific infection syndromes.
This method leverages a Bayesian hierarchical logistic regression framework with random
effects for pathogens and regimens, enabling robust estimates in the presence of sparse
data.< / p >
< p > The Bayesian model assumes conjugate priors for parameter estimation. For example, the
coverage probability $theta$ for a given antimicrobial regimen
is modeled using a Beta distribution as a prior:< / p >
< p > < img src = "figures/beta_prior.png" width = "300" alt = "Beta prior" > < / p >
< p > where \($alpha$_0\) and \($beta$_0\) represent prior successes and failures, respectively,
informed by expert knowledge or weakly informative priors (e.g., \($alpha$_0 = 1, $beta$_0 = 1\)).< / p >
< p > The likelihood function is constructed based on observed data, where the number of covered
cases for a regimen follows a binomial distribution:< / p >
< p > < img src = "figures/binomial_likelihood.png" width = "300" alt = "Binomial likelihood" > < / p >
< p > Posterior parameter estimates are obtained by combining the prior and likelihood using
Bayes' theorem. The posterior distribution of \($theta$\) is also a Beta distribution:< / p >
< p > < img src = "figures/posterior_beta.png" width = "300" alt = "Beta posterior" > < / p >
< p > For hierarchical modeling, pathogen-level effects (e.g., differences in resistance
patterns) and regimen-level effects are modelled using Gaussian priors on log-odds.
This hierarchical structure ensures partial pooling of estimates across groups,
improving stability in strata with small sample sizes. The model is implemented using
Hamiltonian Monte Carlo (HMC) sampling.< / p >
< p > Stratified results are provided based on covariates such as age, sex, and clinical
complexity (e.g., prior antimicrobial treatments or renal/urological comorbidities).
For example, posterior odds ratios (ORs) are derived to quantify the effect of these
covariates on coverage probabilities:< / p >
< p > < img src = "figures/odds_ratio.png" width = "300" alt = "Odds ratio formula" > < / p >
< p > By combining empirical data with prior knowledge, WISCA overcomes the limitations
of traditional combination antibiograms, offering disease-specific, patient-stratified
estimates with robust uncertainty quantification. This tool is invaluable for antimicrobial
stewardship programs and empirical treatment guideline refinement.< / p >
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< / div >
< div class = "section level2" >
< h2 id = "ref-examples" > Examples< a class = "anchor" aria-label = "anchor" href = "#ref-examples" > < / a > < / h2 >
< div class = "sourceCode" > < pre class = "sourceCode r" > < code > < span class = "r-in" > < span > < span class = "co" > # example_isolates is a data set available in the AMR package.< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # run ?example_isolates for more info.< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "va" > example_isolates< / span > < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # A tibble: 2,000 × < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > date patient age gender ward mo PEN OXA FLC AMX < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494; font-style: italic;" > < date> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < dbl> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < mo> < / span > < span style = "color: #949494; font-style: italic;" > < sir> < / span > < span style = "color: #949494; font-style: italic;" > < sir> < / span > < span style = "color: #949494; font-style: italic;" > < sir> < / span > < span style = "color: #949494; font-style: italic;" > < sir> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > 2002-01-02 A77334 65 F Clinical B_ESCHR_COLI R NA NA NA < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > 2002-01-03 A77334 65 F Clinical B_ESCHR_COLI R NA NA NA < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 3< / span > 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R NA < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 4< / span > 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R NA < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 5< / span > 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R NA < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 6< / span > 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R NA < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 7< / span > 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S R < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 8< / span > 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S R < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 9< / span > 2002-01-16 067927 45 F ICU B_STPHY_EPDR R NA R NA < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 10< / span > 2002-01-17 858515 79 F ICU B_STPHY_EPDR R NA S NA < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ℹ < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ℹ < sir> , AMP < sir> , TZP < sir> , CZO < sir> , FEP < sir> ,< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # CXM < sir> , FOX < sir> , CTX < sir> , CAZ < sir> , CRO < sir> , GEN < sir> ,< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # TOB < sir> , AMK < sir> , KAN < sir> , TMP < sir> , SXT < sir> , NIT < sir> ,< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # FOS < sir> , LNZ < sir> , CIP < sir> , MFX < sir> , VAN < sir> , TEC < sir> ,< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # TCY < sir> , TGC < sir> , DOX < sir> , ERY < sir> , CLI < sir> , AZM < sir> ,< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # IPM < sir> , MEM < sir> , MTR < sir> , CHL < sir> , COL < sir> , MUP < sir> , …< / span > < / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "co" > # \donttest{< / span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "co" > # Traditional antibiogram ----------------------------------------------< / span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
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< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > aminoglycosides< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > , < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > carbapenems< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < / span > < / span >
2023-02-12 17:20:08 +01:00
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)< / span >
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (non-WISCA): 10 × < / span > < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > Pathogen Amikacin Gentamicin Imipenem Kanamycin Meropenem Tobramycin< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > CoNS 0% (0/43) 86% (267/… 52% (25… 0% (0/43) 52% (25/… 22% (12/5…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > E. coli 100% (171/… 98% (451/… 100% (4… < span style = "color: #BB0000;" > NA< / span > 100% (41… 97% (450/…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 3< / span > E. faecalis 0% (0/39) 0% (0/39) 100% (3… 0% (0/39) < span style = "color: #BB0000;" > NA< / span > 0% (0/39) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 4< / span > K. pneumoniae < span style = "color: #BB0000;" > NA< / span > 90% (52/5… 100% (5… < span style = "color: #BB0000;" > NA< / span > 100% (53… 90% (52/5…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 5< / span > P. aeruginosa < span style = "color: #BB0000;" > NA< / span > 100% (30/… < span style = "color: #BB0000;" > NA< / span > 0% (0/30) < span style = "color: #BB0000;" > NA< / span > 100% (30/…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 6< / span > P. mirabilis < span style = "color: #BB0000;" > NA< / span > 94% (32/3… 94% (30… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > 94% (32/3…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 7< / span > S. aureus < span style = "color: #BB0000;" > NA< / span > 99% (231/… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > 98% (84/8…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 8< / span > S. epidermidis 0% (0/44) 79% (128/… < span style = "color: #BB0000;" > NA< / span > 0% (0/44) < span style = "color: #BB0000;" > NA< / span > 51% (45/8…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 9< / span > S. hominis < span style = "color: #BB0000;" > NA< / span > 92% (74/8… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > 85% (53/6…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 10< / span > S. pneumoniae 0% (0/117) 0% (0/117) < span style = "color: #BB0000;" > NA< / span > 0% (0/11… < span style = "color: #BB0000;" > NA< / span > 0% (0/117)< / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
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< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > aminoglycosides< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > ,< / span > < / span >
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< span class = "r-in" > < span > ab_transform < span class = "op" > =< / span > < span class = "st" > "atc"< / span > ,< / span > < / span >
< span class = "r-in" > < span > mo_transform < span class = "op" > =< / span > < span class = "st" > "gramstain"< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (non-WISCA): 2 × < / span > < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > Pathogen J01GB01 J01GB03 J01GB04 J01GB06 < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > Gram-negative 96% (658/686) 96% (659/684) 0% (0/35) 98% (251/256)< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > Gram-positive 34% (228/665) 63% (740/1170) 0% (0/436) 0% (0/436) < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
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< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > carbapenems< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > ,< / span > < / span >
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< span class = "r-in" > < span > ab_transform < span class = "op" > =< / span > < span class = "st" > "name"< / span > ,< / span > < / span >
< span class = "r-in" > < span > mo_transform < span class = "op" > =< / span > < span class = "st" > "name"< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (non-WISCA): 5 × < / span > < / span >
2024-09-22 11:55:27 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > Pathogen Imipenem Meropenem < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > Coagulase-negative Staphylococcus (CoNS) 52% (25/48) 52% (25/48) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > Enterococcus faecalis 100% (38/38) < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 3< / span > Escherichia coli 100% (422/422) 100% (418/418)< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 4< / span > Klebsiella pneumoniae 100% (51/51) 100% (53/53) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 5< / span > Proteus mirabilis 94% (30/32) < span style = "color: #BB0000;" > NA< / span > < / span >
2024-07-16 15:00:55 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
2023-02-08 17:01:47 +01:00
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # Combined antibiogram -------------------------------------------------< / span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # combined antibiotics yield higher empiric coverage< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
2023-02-12 17:20:08 +01:00
< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > , < span class = "st" > "TZP+GEN"< / span > < span class = "op" > )< / span > ,< / span > < / span >
< span class = "r-in" > < span > mo_transform < span class = "op" > =< / span > < span class = "st" > "gramstain"< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
2025-01-27 22:16:06 +01:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (non-WISCA): 2 × < / span > < / span >
2024-09-22 11:55:27 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > Pathogen Piperacillin/tazobac…¹ Piperacillin/tazobac…² Piperacillin/tazobac…³< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > Gram-neg… 88% (565/641) 99% (681/691) 98% (679/693) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > Gram-pos… 86% (296/345) 98% (1018/1044) 95% (524/550) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ℹ < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ²`Piperacillin/tazobactam + Gentamicin`,< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ³`Piperacillin/tazobactam + Tobramycin`< / span > < / span >
2024-07-16 15:00:55 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
2023-02-12 17:20:08 +01:00
< span class = "r-in" > < span > < / span > < / span >
2023-02-22 15:50:02 +01:00
< span class = "r-in" > < span > < span class = "co" > # names of antibiotics do not need to resemble columns exactly:< / span > < / span > < / span >
2023-02-08 17:01:47 +01:00
< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
2023-02-22 15:50:02 +01:00
< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "Cipro"< / span > , < span class = "st" > "cipro + genta"< / span > < span class = "op" > )< / span > ,< / span > < / span >
2023-02-12 17:20:08 +01:00
< span class = "r-in" > < span > mo_transform < span class = "op" > =< / span > < span class = "st" > "gramstain"< / span > ,< / span > < / span >
< span class = "r-in" > < span > ab_transform < span class = "op" > =< / span > < span class = "st" > "name"< / span > ,< / span > < / span >
< span class = "r-in" > < span > sep < span class = "op" > =< / span > < span class = "st" > " & "< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
2025-01-27 22:16:06 +01:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (non-WISCA): 2 × < / span > < / span >
2024-09-22 11:55:27 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > Pathogen Ciprofloxacin `Ciprofloxacin & Gentamicin`< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > Gram-negative 91% (621/684) 99% (684/694) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > Gram-positive 77% (560/724) 93% (784/847) < / span >
2024-07-16 15:00:55 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
2023-02-08 17:01:47 +01:00
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # Syndromic antibiogram ------------------------------------------------< / span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # the data set could contain a filter for e.g. respiratory specimens< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
2025-01-17 12:18:49 +01:00
< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > aminoglycosides< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > , < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > carbapenems< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > ,< / span > < / span >
2023-02-12 17:20:08 +01:00
< span class = "r-in" > < span > syndromic_group < span class = "op" > =< / span > < span class = "st" > "ward"< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
2025-01-27 22:16:06 +01:00
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)< / span >
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (non-WISCA): 14 × < / span > < / span >
2024-09-22 11:55:27 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > `Syndromic Group` Pathogen Amikacin Gentamicin Imipenem Kanamycin Meropenem< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > Clinical CoNS < span style = "color: #BB0000;" > NA< / span > 89% (183/… 57% (20… < span style = "color: #BB0000;" > NA< / span > 57% (20/…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > ICU CoNS < span style = "color: #BB0000;" > NA< / span > 79% (58/7… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 3< / span > Outpatient CoNS < span style = "color: #BB0000;" > NA< / span > 84% (26/3… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 4< / span > Clinical E. coli 100% (1… 98% (291/… 100% (2… < span style = "color: #BB0000;" > NA< / span > 100% (27…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 5< / span > ICU E. coli 100% (5… 99% (135/… 100% (1… < span style = "color: #BB0000;" > NA< / span > 100% (11…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 6< / span > Clinical K. pneumo… < span style = "color: #BB0000;" > NA< / span > 92% (47/5… 100% (4… < span style = "color: #BB0000;" > NA< / span > 100% (46…< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 7< / span > Clinical P. mirabi… < span style = "color: #BB0000;" > NA< / span > 100% (30/… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 8< / span > Clinical S. aureus < span style = "color: #BB0000;" > NA< / span > 99% (148/… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 9< / span > ICU S. aureus < span style = "color: #BB0000;" > NA< / span > 100% (66/… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 10< / span > Clinical S. epider… < span style = "color: #BB0000;" > NA< / span > 82% (65/7… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 11< / span > ICU S. epider… < span style = "color: #BB0000;" > NA< / span > 72% (54/7… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 12< / span > Clinical S. hominis < span style = "color: #BB0000;" > NA< / span > 96% (43/4… < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 13< / span > Clinical S. pneumo… 0% (0/7… 0% (0/78) < span style = "color: #BB0000;" > NA< / span > 0% (0/78) < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 14< / span > ICU S. pneumo… 0% (0/3… 0% (0/30) < span style = "color: #BB0000;" > NA< / span > 0% (0/30) < span style = "color: #BB0000;" > NA< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ℹ < chr> < / span > < / span >
2024-07-16 15:00:55 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
2023-02-08 17:01:47 +01:00
< span class = "r-in" > < span > < / span > < / span >
2023-02-10 16:26:36 +01:00
< span class = "r-in" > < span > < span class = "co" > # now define a data set with only E. coli< / span > < / span > < / span >
2023-02-08 17:01:47 +01:00
< span class = "r-in" > < span > < span class = "va" > ex1< / span > < span class = "op" > < -< / span > < span class = "va" > example_isolates< / span > < span class = "op" > [< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/which.html" class = "external-link" > which< / a > < / span > < span class = "op" > (< / span > < span class = "fu" > < a href = "mo_property.html" > mo_genus< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > < span class = "op" > ==< / span > < span class = "st" > "Escherichia"< / span > < span class = "op" > )< / span > , < span class = "op" > ]< / span > < / span > < / span >
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
2023-02-10 16:26:36 +01:00
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # with a custom language, though this will be determined automatically< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # (i.e., this table will be in Spanish on Spanish systems)< / span > < / span > < / span >
2023-02-08 17:01:47 +01:00
< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > ex1< / span > ,< / span > < / span >
2025-01-17 12:18:49 +01:00
< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > aminoglycosides< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > ,< / span > < / span >
2023-03-11 14:32:27 +01:00
< span class = "r-in" > < span > ab_transform < span class = "op" > =< / span > < span class = "st" > "name"< / span > ,< / span > < / span >
< span class = "r-in" > < span > syndromic_group < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/ifelse.html" class = "external-link" > ifelse< / a > < / span > < span class = "op" > (< / span > < span class = "va" > ex1< / span > < span class = "op" > $< / span > < span class = "va" > ward< / span > < span class = "op" > ==< / span > < span class = "st" > "ICU"< / span > ,< / span > < / span >
< span class = "r-in" > < span > < span class = "st" > "UCI"< / span > , < span class = "st" > "No UCI"< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > ,< / span > < / span >
< span class = "r-in" > < span > language < span class = "op" > =< / span > < span class = "st" > "es"< / span > < / span > < / span >
2023-02-12 17:20:08 +01:00
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
2025-01-27 22:16:06 +01:00
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
< span class = "r-msg co" > < span class = "r-pr" > #> < / span > (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (non-WISCA): 2 × < / span > < / span >
2024-09-22 11:55:27 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > `Grupo sindrómico` Patógeno Amikacina Gentamicina Tobramicina < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > No UCI E. coli 100% (119/119) 98% (316/323) 98% (318/325)< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > UCI E. coli 100% (52/52) 99% (135/137) 96% (132/137)< / span >
2024-07-16 15:00:55 +02:00
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
2023-02-08 17:01:47 +01:00
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "co" > # WISCA antibiogram ----------------------------------------------------< / span > < / span > < / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "co" > # can be used for any of the above types - just add `wisca = TRUE`< / span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
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< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > , < span class = "st" > "TZP+GEN"< / span > < span class = "op" > )< / span > ,< / span > < / span >
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< span class = "r-in" > < span > mo_transform < span class = "op" > =< / span > < span class = "st" > "gramstain"< / span > ,< / span > < / span >
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< span class = "r-in" > < span > wisca < span class = "op" > =< / span > < span class = "cn" > TRUE< / span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # An Antibiogram (WISCA / 95% CI): 2 × < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > Pathogen Piperacillin/tazobac…¹ Piperacillin/tazobac…² Piperacillin/tazobac…³< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > *< / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < span style = "color: #949494; font-style: italic;" > < chr> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 1< / span > Gram-neg… 88% (85-90%,N=641) 98% (97-99%,N=691) 98% (97-99%,N=693) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #BCBCBC;" > 2< / span > Gram-pos… 86% (82-89%,N=345) 97% (96-98%,N=1044) 95% (93-97%,N=550) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ℹ < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ²`Piperacillin/tazobactam + Gentamicin`,< / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < span style = "color: #949494;" > # ³`Piperacillin/tazobactam + Tobramycin`< / span > < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > # or use it directly in R Markdown or https://quarto.org, see ?antibiogram< / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "co" > # Print the output for R Markdown / Quarto -----------------------------< / span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "va" > ureido< / span > < span class = "op" > < -< / span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
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< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "antimicrobial_class_selectors.html" > ureidopenicillins< / a > < / span > < span class = "op" > (< / span > < span class = "op" > )< / span > ,< / span > < / span >
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< span class = "r-in" > < span > ab_transform < span class = "op" > =< / span > < span class = "st" > "name"< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-msg co" > < span class = "r-pr" > #> < / span > ℹ < / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "co" > # in an Rmd file, you would just need to return `ureido` in a chunk,< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # but to be explicit here:< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "kw" > if< / span > < span class = "op" > (< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/ns-load.html" class = "external-link" > requireNamespace< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "knitr"< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < span class = "op" > {< / span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "fu" > < a href = "https://rdrr.io/r/base/cat.html" class = "external-link" > cat< / a > < / span > < span class = "op" > (< / span > < span class = "fu" > knitr< / span > < span class = "fu" > ::< / span > < span class = "fu" > < a href = "https://rdrr.io/pkg/knitr/man/knit_print.html" class = "external-link" > knit_print< / a > < / span > < span class = "op" > (< / span > < span class = "va" > ureido< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "op" > }< / span > < / span > < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
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< span class = "r-out co" > < span class = "r-pr" > #> < / span > |Pathogen |Piperacillin/tazobactam |< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > |:---------------|:-----------------------|< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > |CoNS |30% (10/33) |< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > |*E. coli* |94% (393/416) |< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > |*K. pneumoniae* |89% (47/53) |< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > |*S. pneumoniae* |100% (112/112) |< / span >
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< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "co" > # Generate plots with ggplot2 or base R --------------------------------< / span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "va" > ab1< / span > < span class = "op" > < -< / span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
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< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "AMC"< / span > , < span class = "st" > "CIP"< / span > , < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > < span class = "op" > )< / span > ,< / span > < / span >
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< span class = "r-in" > < span > mo_transform < span class = "op" > =< / span > < span class = "st" > "gramstain"< / span > ,< / span > < / span >
< span class = "r-in" > < span > wisca < span class = "op" > =< / span > < span class = "cn" > TRUE< / span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "va" > ab2< / span > < span class = "op" > < -< / span > < span class = "fu" > antibiogram< / span > < span class = "op" > (< / span > < span class = "va" > example_isolates< / span > ,< / span > < / span >
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< span class = "r-in" > < span > antibiotics < span class = "op" > =< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/c.html" class = "external-link" > c< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "AMC"< / span > , < span class = "st" > "CIP"< / span > , < span class = "st" > "TZP"< / span > , < span class = "st" > "TZP+TOB"< / span > < span class = "op" > )< / span > ,< / span > < / span >
< span class = "r-in" > < span > mo_transform < span class = "op" > =< / span > < span class = "st" > "gramstain"< / span > ,< / span > < / span >
< span class = "r-in" > < span > syndromic_group < span class = "op" > =< / span > < span class = "st" > "ward"< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > )< / span > < / span > < / span >
< span class = "r-in" > < span > < / span > < / span >
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< span class = "r-in" > < span > < span class = "kw" > if< / span > < span class = "op" > (< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/ns-load.html" class = "external-link" > requireNamespace< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "ggplot2"< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < span class = "op" > {< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "fu" > ggplot2< / span > < span class = "fu" > ::< / span > < span class = "fu" > < a href = "https://ggplot2.tidyverse.org/reference/autoplot.html" class = "external-link" > autoplot< / a > < / span > < span class = "op" > (< / span > < span class = "va" > ab1< / span > < span class = "op" > )< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > }< / span > < / span > < / span >
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< span class = "r-plt img" > < img src = "antibiogram-1.png" alt = "" width = "700" height = "433" > < / span >
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< span class = "r-in" > < span > < span class = "kw" > if< / span > < span class = "op" > (< / span > < span class = "fu" > < a href = "https://rdrr.io/r/base/ns-load.html" class = "external-link" > requireNamespace< / a > < / span > < span class = "op" > (< / span > < span class = "st" > "ggplot2"< / span > < span class = "op" > )< / span > < span class = "op" > )< / span > < span class = "op" > {< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "fu" > ggplot2< / span > < span class = "fu" > ::< / span > < span class = "fu" > < a href = "https://ggplot2.tidyverse.org/reference/autoplot.html" class = "external-link" > autoplot< / a > < / span > < span class = "op" > (< / span > < span class = "va" > ab2< / span > < span class = "op" > )< / span > < / span > < / span >
< span class = "r-in" > < span > < span class = "op" > }< / span > < / span > < / span >
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< span class = "r-plt img" > < img src = "antibiogram-2.png" alt = "" width = "700" height = "433" > < / span >
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< span class = "r-in" > < span > < / span > < / span >
< span class = "r-in" > < span > < span class = "fu" > < a href = "plot.html" > plot< / a > < / span > < span class = "op" > (< / span > < span class = "va" > ab1< / span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-plt img" > < img src = "antibiogram-3.png" alt = "" width = "700" height = "433" > < / span >
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< span class = "r-in" > < span > < span class = "fu" > < a href = "plot.html" > plot< / a > < / span > < span class = "op" > (< / span > < span class = "va" > ab2< / span > < span class = "op" > )< / span > < / span > < / span >
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< span class = "r-plt img" > < img src = "antibiogram-4.png" alt = "" width = "700" height = "433" > < / span >
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< span class = "r-in" > < span > < span class = "co" > # }< / span > < / span > < / span >
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< / code > < / pre > < / div >
< / div >
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< / main > < aside class = "col-md-3" > < nav id = "toc" aria-label = "Table of contents" > < h2 > On this page< / h2 >
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< / nav > < / aside > < / div >
< footer > < div class = "pkgdown-footer-left" >
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