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v1.8.2
dr. M.S. (Matthijs) Berends 3 years ago
parent a7e538e562
commit f7eb6e4107
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  1. 1
      .gitignore
  2. 4
      DESCRIPTION
  3. 5
      NEWS.md
  4. 80
      data-raw/country_analysis.R
  5. 2
      docs/404.html
  6. 2
      docs/LICENSE-text.html
  7. 421
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@ -22,3 +22,4 @@ packrat/lib*/
packrat/src/
data-raw/taxon.tab
data-raw/DSMZ_bactnames.xlsx
data-raw/country_analysis_url_token.R

4
DESCRIPTION
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Package: AMR
Version: 0.9.0
Date: 2019-11-30
Version: 0.9.0.9002
Date: 2019-12-16
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

5
NEWS.md
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# AMR 0.9.0.9002
## <small>Last updated: 16-Dec-2019</small>
Website updates
# AMR 0.9.0
### Breaking

80
data-raw/country_analysis.R
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# Read and format data ----------------------------------------------------
library(tidyverse)
library(maps)
# get website analytics
source("data-raw/country_analysis_url_token.R")
url_json <- paste0(country_analysis_url,
"/index.php?&module=API&token_auth=",
country_analysis_token,
"&method=Live.getLastVisitsDetails&idSite=3&language=en&expanded=1&date=2018-01-01,2028-01-01&period=range&filter_limit=-1&format=JSON&segment=&translateColumnNames=1")
data_json <- jsonlite::read_json(url_json)
data <- tibble(
timestamp_server = as.POSIXct(sapply(data_json, function(x) x$serverTimestamp), origin = "1970-01-01"),
country = sapply(data_json, function(x) x$country))
# Plot world map ----------------------------------------------------------
countries_name <- sort(unique(data$country))
countries_name <- countries_name[countries_name != "Unknown"]
countries_iso <- countrycode::countrycode(countries_name, 'country.name', 'iso3c')
world1 <- sf::st_as_sf(map('world', plot = FALSE, fill = TRUE)) %>%
mutate(countries_code = countrycode::countrycode(ID, 'country.name', 'iso3c'),
included = as.integer(countries_code %in% countries_iso)) %>%
mutate(not_antarctica = as.integer(ID != "Antarctica"))
(ggplot(world1) +
geom_sf(aes(fill = included, colour = not_antarctica), size = 0.25) +
theme_minimal() +
theme(legend.position = "none",
panel.grid = element_blank(),
axis.title = element_blank(),
axis.text = element_blank()) +
scale_fill_gradient(low = "white", high = "#CAD6EA") +
# this makes the border Antarctica turn white (invisible):
scale_colour_gradient(low = "white", high = "#81899B") +
geom_text(aes(x = -170,
y = -70,
label = stringr::str_wrap(paste0("Accented countries (n = ",
length(countries_name), "): ",
paste(countries_name, collapse = ", ")),
225)),
hjust = 0,
size = 4)) %>%
ggsave("pkgdown/logos/countries.png", dpi = 300, plot = ., scale = 1.5)
# Gibberish ---------------------------------------------------------------
p1 <- data %>%
group_by(country) %>%
summarise(first = min(timestamp_server)) %>%
arrange(first) %>%
mutate(n = row_number()) %>%
ggplot(aes(x = first, y = n)) +
geom_line() +
geom_point(aes(x = max(first), y = max(n)), size = 3) +
scale_x_datetime(date_breaks = "2 months", date_labels = "%B %Y") +
labs(x = NULL, y = "Number of countries")
package_releases <- read_html("https://cran.r-project.org/src/contrib/Archive/AMR/") %>%
rvest::html_table() %>%
.[[1]] %>%
as_tibble(.name_repair = "unique") %>%
filter(`Last modified` != "") %>%
transmute(version = gsub("[^0-9.]", "",
gsub(".tar.gz", "", Name)),
datetime = as.POSIXct(`Last modified`)) %>%
# add current
bind_rows(tibble(version = as.character(packageVersion("AMR")),
datetime = as.POSIXct(packageDate("AMR")))) %>%
# remove the ones not plottable
filter(datetime > min(p1$data$first))
p1 + geom_linerange(data = package_releases, aes(x = datetime, ymin = 0, ymax = 80), colour = "red", inherit.aes = FALSE)

2
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@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.gitlab.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.9.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.9.0.9002</span>
</span>
</div>

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@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.9.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.9.0.9002</span>
</span>
</div>

421
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@ -187,7 +187,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">30 November 2019</h4>
<h4 class="date">11 December 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -196,7 +196,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 30 November 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 11 December 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -212,21 +212,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-11-30</td>
<td align="center">2019-12-11</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2019-11-30</td>
<td align="center">2019-12-11</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2019-11-30</td>
<td align="center">2019-12-11</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -321,70 +321,70 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2017-05-01</td>
<td align="center">L9</td>
<td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">2017-05-19</td>
<td align="center">J2</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2014-02-04</td>
<td align="center">U2</td>
<td align="center">2016-07-09</td>
<td align="center">K4</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2016-12-08</td>
<td align="center">P9</td>
<td align="center">Hospital B</td>
<td align="center">2014-05-10</td>
<td align="center">R6</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2014-11-30</td>
<td align="center">V1</td>
<td align="center">2011-06-29</td>
<td align="center">T4</td>
<td align="center">Hospital B</td>
<td align="center">Klebsiella pneumoniae</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2017-09-12</td>
<td align="center">T5</td>
<td align="center">Hospital D</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">2012-02-11</td>
<td align="center">O10</td>
<td align="center">Hospital A</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2010-01-31</td>
<td align="center">W3</td>
<td align="center">Hospital A</td>
<td align="center">2017-04-09</td>
<td align="center">D3</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
</tbody>
</table>
@ -406,8 +406,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,321 51.61% 10,321 51.61%
# 2 F 9,679 48.40% 20,000 100.00%</code></pre>
# 1 M 10,408 52.04% 10,408 52.04%
# 2 F 9,592 47.96% 20,000 100.00%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -422,8 +422,8 @@
<a class="sourceLine" id="cb14-3" data-line-number="3"><span class="co"># Other rules by this AMR package</span></a>
<a class="sourceLine" id="cb14-4" data-line-number="4"><span class="co"># Non-EUCAST: inherit amoxicillin results for unavailable ampicillin (no changes)</span></a>
<a class="sourceLine" id="cb14-5" data-line-number="5"><span class="co"># Non-EUCAST: inherit ampicillin results for unavailable amoxicillin (no changes)</span></a>
<a class="sourceLine" id="cb14-6" data-line-number="6"><span class="co"># Non-EUCAST: set amoxicillin/clav acid = S where ampicillin = S (2,960 values changed)</span></a>
<a class="sourceLine" id="cb14-7" data-line-number="7"><span class="co"># Non-EUCAST: set ampicillin = R where amoxicillin/clav acid = R (144 values changed)</span></a>
<a class="sourceLine" id="cb14-6" data-line-number="6"><span class="co"># Non-EUCAST: set amoxicillin/clav acid = S where ampicillin = S (2,997 values changed)</span></a>
<a class="sourceLine" id="cb14-7" data-line-number="7"><span class="co"># Non-EUCAST: set ampicillin = R where amoxicillin/clav acid = R (165 values changed)</span></a>
<a class="sourceLine" id="cb14-8" data-line-number="8"><span class="co"># Non-EUCAST: set piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
<a class="sourceLine" id="cb14-9" data-line-number="9"><span class="co"># Non-EUCAST: set piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb14-10" data-line-number="10"><span class="co"># Non-EUCAST: set trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
@ -448,14 +448,14 @@
<a class="sourceLine" id="cb14-29" data-line-number="29"><span class="co"># Pasteurella multocida (no changes)</span></a>
<a class="sourceLine" id="cb14-30" data-line-number="30"><span class="co"># Staphylococcus (no changes)</span></a>
<a class="sourceLine" id="cb14-31" data-line-number="31"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
<a class="sourceLine" id="cb14-32" data-line-number="32"><span class="co"># Streptococcus pneumoniae (997 values changed)</span></a>
<a class="sourceLine" id="cb14-32" data-line-number="32"><span class="co"># Streptococcus pneumoniae (1,063 values changed)</span></a>
<a class="sourceLine" id="cb14-33" data-line-number="33"><span class="co"># Viridans group streptococci (no changes)</span></a>
<a class="sourceLine" id="cb14-34" data-line-number="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-35" data-line-number="35"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,331 values changed)</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,242 values changed)</span></a>
<a class="sourceLine" id="cb14-37" data-line-number="37"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,705 values changed)</span></a>
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,782 values changed)</span></a>
<a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb14-42" data-line-number="42"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@ -463,15 +463,15 @@
<a class="sourceLine" id="cb14-44" data-line-number="44"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
<a class="sourceLine" id="cb14-45" data-line-number="45"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-46" data-line-number="46"><span class="co"># -------------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># EUCAST rules affected 6,481 out of 20,000 rows, making a total of 8,137 edits</span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># EUCAST rules affected 6,564 out of 20,000 rows, making a total of 8,249 edits</span></a>
<a class="sourceLine" id="cb14-48" data-line-number="48"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-49" data-line-number="49"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># =&gt; changed 8,137 test results</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 115 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 4,732 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co"># - 1,228 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co"># - 330 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co"># - 1,732 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># =&gt; changed 8,249 test results</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 102 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 4,787 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co"># - 1,224 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co"># - 363 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co"># - 1,773 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-56" data-line-number="56"><span class="co"># -------------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-57" data-line-number="57"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-58" data-line-number="58"><span class="co"># Use eucast_rules(..., verbose = TRUE) (on your original data) to get a data.frame with all specified edits instead.</span></a></code></pre></div>
@ -499,7 +499,7 @@
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,667 first isolates (28.3% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,656 first isolates (28.3% of total)</span></a></code></pre></div>
<p>So only 28.3% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
@ -510,7 +510,7 @@
<div id="first-weighted-isolates" class="section level2">
<h2 class="hasAnchor">
<a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient E9, sorted on date:</p>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient D2, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -526,52 +526,52 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-07-16</td>
<td align="center">E9</td>
<td align="center">2010-02-23</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-07-22</td>
<td align="center">E9</td>
<td align="center">2010-03-20</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-08-26</td>
<td align="center">E9</td>
<td align="center">2010-04-13</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-10-17</td>
<td align="center">E9</td>
<td align="center">2010-07-22</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-10-25</td>
<td align="center">E9</td>
<td align="center">2010-07-22</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -581,10 +581,10 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-02-27</td>
<td align="center">E9</td>
<td align="center">2010-08-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -592,8 +592,8 @@
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-03-15</td>
<td align="center">E9</td>
<td align="center">2010-08-19</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -603,40 +603,40 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-03-19</td>
<td align="center">E9</td>
<td align="center">2010-09-02</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-06-20</td>
<td align="center">E9</td>
<td align="center">2010-09-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-12-03</td>
<td align="center">E9</td>
<td align="center">2010-09-18</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<p>Only 2 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
<p>Only 1 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
<p>If a column exists with a name like ‘key(…)ab’ the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output:</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">keyab =</span> <span class="kw"><a href="../reference/key_antibiotics.html">key_antibiotics</a></span>(.)) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -647,7 +647,7 @@
<a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb19-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I</span></a>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,044 first weighted isolates (75.2% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,026 first weighted isolates (75.1% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -664,131 +664,131 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-07-16</td>
<td align="center">E9</td>
<td align="center">2010-02-23</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-07-22</td>
<td align="center">E9</td>
<td align="center">2010-03-20</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-08-26</td>
<td align="center">E9</td>
<td align="center">2010-04-13</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-10-17</td>
<td align="center">E9</td>
<td align="center">2010-07-22</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-10-25</td>
<td align="center">E9</td>
<td align="center">2010-07-22</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-02-27</td>
<td align="center">E9</td>
<td align="center">2010-08-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-03-15</td>
<td align="center">E9</td>
<td align="center">2010-08-19</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-03-19</td>
<td align="center">E9</td>
<td align="center">2010-09-02</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-06-20</td>
<td align="center">E9</td>
<td align="center">2010-09-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-12-03</td>
<td align="center">E9</td>
<td align="center">2010-09-18</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 7 isolates are flagged. In total, 75.2% of all isolates are marked ‘first weighted’ - 46.9% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 1, now 9 isolates are flagged. In total, 75.1% of all isolates are marked ‘first weighted’ - 46.9% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,044 isolates for analysis.</p>
<p>So we end up with 15,026 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(first, keyab))</a></code></pre></div>
@ -796,7 +796,6 @@
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(data_1st)</a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th></th>
<th align="center">date</th>
<th align="center">patient_id</th>
<th align="center">hospital</th>
@ -813,63 +812,59 @@
</tr></thead>
<tbody>
<tr class="odd">
<td>3</td>
<td align="center">2016-12-08</td>
<td align="center">P9</td>
<td align="center">Hospital B</td>
<td align="center">2017-05-19</td>
<td align="center">J2</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>4</td>
<td align="center">2014-11-30</td>
<td align="center">V1</td>
<td align="center">Hospital B</td>
<td align="center">B_KLBSL_PNMN</td>
<td align="center">R</td>
<td align="center">2016-07-09</td>
<td align="center">K4</td>
<td align="center">Hospital A</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Klebsiella</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>5</td>
<td align="center">2017-09-12</td>
<td align="center">T5</td>
<td align="center">Hospital D</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">2014-05-10</td>
<td align="center">R6</td>
<td align="center">Hospital C</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>6</td>
<td align="center">2010-01-31</td>
<td align="center">W3</td>
<td align="center">Hospital A</td>
<td align="center">2011-06-29</td>
<td align="center">T4</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
@ -877,35 +872,33 @@
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>7</td>
<td align="center">2015-09-28</td>
<td align="center">K4</td>
<td align="center">Hospital B</td>
<td align="center">B_KLBSL_PNMN</td>
<td align="center">2012-02-11</td>
<td align="center">O10</td>
<td align="center">Hospital A</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">I</td>
<td align="center">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Klebsiella</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>8</td>
<td align="center">2011-08-30</td>
<td align="center">B6</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">2017-04-09</td>
<td align="center">D3</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
</tbody>
@ -927,7 +920,7 @@
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,044 (of which NA: 0 = 0%)<br>
Length: 15,026 (of which NA: 0 = 0%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -944,33 +937,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,493</td>
<td align="right">49.81%</td>
<td align="right">7,493</td>
<td align="right">49.81%</td>
<td align="right">7,425</td>
<td align="right">49.41%</td>
<td align="right">7,425</td>
<td align="right">49.41%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,718</td>
<td align="right">24.71%</td>
<td align="right">11,211</td>
<td align="right">74.52%</td>
<td align="right">3,806</td>
<td align="right">25.33%</td>
<td align="right">11,231</td>
<td align="right">74.74%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,293</td>
<td align="right">15.24%</td>
<td align="right">13,504</td>
<td align="right">89.76%</td>
<td align="right">2,311</td>
<td align="right">15.38%</td>
<td align="right">13,542</td>
<td align="right">90.12%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,540</td>
<td align="right">10.24%</td>
<td align="right">15,044</td>
<td align="right">1,484</td>
<td align="right">9.88%</td>
<td align="right">15,026</td>
<td align="right">100.00%</td>
</tr>
</tbody>
@ -982,7 +975,7 @@ Longest: 24</p>
<p>The functions <code><a href="../reference/proportion.html">resistance()</a></code> and <code><a href="../reference/proportion.html">susceptibility()</a></code> can be used to calculate antimicrobial resistance or susceptibility. For more specific analyses, the functions <code><a href="../reference/proportion.html">proportion_S()</a></code>, <code><a href="../reference/proportion.html">proportion_SI()</a></code>, <code><a href="../reference/proportion.html">proportion_I()</a></code>, <code><a href="../reference/proportion.html">proportion_IR()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code> can be used to determine the proportion of a specific antimicrobial outcome.</p>
<p>As per the EUCAST guideline of 2019, we calculate resistance as the proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a></code>, equal to <code><a href="../reference/proportion.html">resistance()</a></code>) and susceptibility as the proportion of S and I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equal to <code><a href="../reference/proportion.html">susceptibility()</a></code>). These functions can be used on their own:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/proportion.html">resistance</a></span>(AMX)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4660994</span></a></code></pre></div>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4631971</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -995,19 +988,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4644833</td>
<td align="center">0.4553786</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4626231</td>
<td align="center">0.4653638</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4616060</td>
<td align="center">0.4613043</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4776800</td>
<td align="center">0.4729412</td>
</tr>
</tbody>
</table>
@ -1025,23 +1018,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4644833</td>
<td align="center">4519</td>
<td align="center">0.4553786</td>
<td align="center">4583</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4626231</td>
<td align="center">5177</td>
<td align="center">0.4653638</td>
<td align="center">5168</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4616060</td>
<td align="center">2279</td>
<td align="center">0.4613043</td>
<td align="center">2300</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4776800</td>
<td align="center">3069</td>
<td align="center">0.4729412</td>
<td align="center">2975</td>
</tr>
</tbody>
</table>
@ -1061,27 +1054,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9253970</td>
<td align="center">0.8955025</td>
<td align="center">0.9929267</td>
<td align="center">0.9248485</td>
<td align="center">0.8921212</td>
<td align="center">0.9936700</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.9298701</td>
<td align="center">0.9038961</td>
<td align="center">0.9967532</td>
<td align="center">0.9238544</td>
<td align="center">0.8928571</td>
<td align="center">0.9946092</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9276493</td>
<td align="center">0.9133943</td>
<td align="center">0.9943518</td>
<td align="center">0.9224908</td>
<td align="center">0.9177614</td>
<td align="center">0.9923805</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6096816</td>
<td align="center">0.5962787</td>
<td align="center">0.0000000</td>
<td align="center">0.6096816</td>
<td align="center">0.5962787</td>
</tr>
</tbody>
</table>

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<h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">29 November 2019</h4>
<h4 class="date">11 December 2019</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div>

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<h1>How to determine multi-drug resistance (M