From a153eb26260db6eb4dc1942e8816cefff6ae499f Mon Sep 17 00:00:00 2001 From: github-actions <41898282+github-actions[bot]@users.noreply.github.com> Date: Tue, 29 Nov 2022 18:45:20 +0000 Subject: [PATCH] Built site for AMR: 1.8.2.9054@6017f81 --- articles/AMR.html | 514 +++++++++--------- .../AMR_files/figure-html/disk_plots-1.png | Bin 38090 -> 39257 bytes .../figure-html/disk_plots_mo_ab-1.png | Bin 52875 -> 55217 bytes .../AMR_files/figure-html/mic_plots-1.png | Bin 28718 -> 27833 bytes .../AMR_files/figure-html/mic_plots-2.png | Bin 37435 -> 38507 bytes .../figure-html/mic_plots_mo_ab-1.png | Bin 38738 -> 37267 bytes .../figure-html/mic_plots_mo_ab-2.png | Bin 49533 -> 49948 bytes articles/AMR_files/figure-html/plot 1-1.png | Bin 43310 -> 42847 bytes articles/AMR_files/figure-html/plot 3-1.png | Bin 28398 -> 28454 bytes articles/AMR_files/figure-html/plot 4-1.png | Bin 78107 -> 78034 bytes articles/AMR_files/figure-html/plot 5-1.png | Bin 49896 -> 49877 bytes articles/MDR.html | 52 +- articles/SPSS.html | 2 +- articles/datasets.html | 2 +- pkgdown.yml | 2 +- reference/Rplot005.png | Bin 13167 -> 13172 bytes reference/Rplot006.png | Bin 12671 -> 12697 bytes reference/Rplot007.png | Bin 14225 -> 15662 bytes reference/Rplot008.png | Bin 20012 -> 17860 bytes reference/Rplot009.png | Bin 8970 -> 8473 bytes reference/age.html | 20 +- reference/as.rsi.html | 20 +- reference/get_episode.html | 143 +++-- reference/kurtosis.html | 4 +- reference/mean_amr_distance.html | 76 +-- reference/plot-1.png | Bin 26317 -> 26826 bytes reference/plot-2.png | Bin 27070 -> 26482 bytes reference/plot-3.png | Bin 28267 -> 28303 bytes reference/plot-4.png | Bin 38274 -> 38683 bytes reference/plot-5.png | Bin 38682 -> 38151 bytes reference/plot-6.png | Bin 37408 -> 36855 bytes reference/plot-7.png | Bin 39051 -> 41345 bytes reference/plot-8.png | Bin 58507 -> 54758 bytes reference/plot-9.png | Bin 27468 -> 26162 bytes reference/random.html | 32 +- reference/skewness.html | 2 +- search.json | 2 +- 37 files changed, 436 insertions(+), 435 deletions(-) diff --git a/articles/AMR.html b/articles/AMR.html index 053cd287..041d02a5 100644 --- a/articles/AMR.html +++ b/articles/AMR.html @@ -168,7 +168,7 @@

Dr. Matthijs Berends

-

28 November 2022

+

29 November 2022

Source: vignettes/AMR.Rmd
AMR.Rmd
@@ -180,7 +180,7 @@ Berends website update since they are based on randomly created values and the page was written in R Markdown. However, the methodology remains unchanged. This page was -generated on 28 November 2022.

+generated on 29 November 2022.

Introduction

@@ -236,21 +236,21 @@ make the structure of your data generally look like this:

-2022-11-28 +2022-11-29 abcd Escherichia coli S S -2022-11-28 +2022-11-29 abcd Escherichia coli S R -2022-11-28 +2022-11-29 efgh Escherichia coli R @@ -400,71 +400,71 @@ data set:

-2016-12-09 -B5 +2016-02-08 +L4 Hospital A -Klebsiella pneumoniae -I -S +Escherichia coli R +R +S S M -2013-12-22 -V7 +2011-06-04 +B4 Hospital B Escherichia coli +R +S +S +S +M + + +2010-12-27 +U10 +Hospital B +Klebsiella pneumoniae S S S S F + +2013-08-11 +H1 +Hospital C +Staphylococcus aureus +R +S +S +S +M + -2011-09-01 -J7 +2011-08-27 +M9 Hospital B Streptococcus pneumoniae +S +S +S +S +M + + +2015-04-24 +L8 +Hospital C +Streptococcus pneumoniae R S S S M - -2010-09-10 -N5 -Hospital A -Escherichia coli -S -S -S -S -M - - -2015-12-02 -E9 -Hospital B -Staphylococcus aureus -S -S -R -S -M - - -2012-01-20 -V9 -Hospital B -Staphylococcus aureus -S -R -S -S -F -

Now, let’s start the cleaning and the analysis!

@@ -499,16 +499,16 @@ Longest: 1

1 M -10,502 -52.51% -10,502 -52.51% +10,441 +52.21% +10,441 +52.21% 2 F -9,498 -47.49% +9,559 +47.80% 20,000 100.00% @@ -621,9 +621,9 @@ takes into account the antimicrobial susceptibility test results using # Basing inclusion on all antimicrobial results, using a points threshold of # 2 # Including isolates from ICU. -# => Found 10,638 'phenotype-based' first isolates (53.2% of total where a +# => Found 10,709 'phenotype-based' first isolates (53.5% of total where a # microbial ID was available)
-

So only 53.2% is suitable for resistance analysis! We can now filter +

So only 53.5% is suitable for resistance analysis! We can now filter on it with the filter() function, also from the dplyr package:

@@ -634,12 +634,13 @@ on it with the data_1st <- data %>%
   filter_first_isolate()
 # Including isolates from ICU.
-

So we end up with 10,638 isolates for analysis. Now our data looks +

So we end up with 10,709 isolates for analysis. Now our data looks like:

 head(data_1st)
- +
+@@ -655,6 +656,7 @@ like:

+ @@ -671,90 +673,96 @@ like:

- - - + + + + - - + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + - - + + + + + + + + + + + + + + + + + + - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -793,8 +801,8 @@ readable:

data_1st %>% freq(genus, species)

Frequency table

Class: character
-Length: 10,638
-Available: 10,638 (100%, NA: 0 = 0%)
+Length: 10,709
+Available: 10,709 (100%, NA: 0 = 0%)
Unique: 4

Shortest: 16
Longest: 24

@@ -819,33 +827,33 @@ Longest: 24

- - - - + + + + - - - - + + + + - - - - + + + + - - - + + + @@ -894,8 +902,38 @@ antibiotic class they are in:

- - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -909,54 +947,24 @@ antibiotic class they are in:

- - + + - - - - - - - - - - - - - - - - + - - - - - - - - - - - - - - - - - - + + + @@ -969,9 +977,9 @@ antibiotic class they are in:

- - - + + + @@ -1005,50 +1013,50 @@ different bug/drug combinations, you can use the - - - - + + + + - - - - + + + + - + - - + + - + - - + + - - + + - - - - + + + +
date patient_id hospital
2016-12-09B5Hospital A32010-12-27U10Hospital B B_KLBSL_PNMN R SR SMSF Gram-negative Klebsiella pneumoniae TRUE
2013-12-22V7Hospital BB_ESCHR_COLISSSSFGram-negativeEscherichiacoliTRUE
2011-09-01J7Hospital BB_STRPT_PNMNRRSRMGram-positiveStreptococcuspneumoniaeTRUE
2010-09-10N5Hospital AB_ESCHR_COLISSSSMGram-negativeEscherichiacoliTRUE
2015-12-02E9Hospital B42013-08-11H1Hospital C B_STPHY_AURSSS R SSS M Gram-positive Staphylococcus aureus TRUE
72013-10-25I3Hospital AB_ESCHR_COLIRSRSMGram-negativeEscherichiacoliTRUE
2012-01-20V9Hospital BB_STPHY_AURSR92011-08-23Y10Hospital AB_ESCHR_COLI R S SS FGram-negativeEscherichiacoliTRUE
112012-08-03U10Hospital AB_KLBSL_PNMNRSSSFGram-negativeKlebsiellapneumoniaeTRUE
122013-12-31L3Hospital AB_STPHY_AURSRSSSM Gram-positive Staphylococcus aureus
1 Escherichia coli4,64643.67%4,64643.67%4,63543.28%4,63543.28%
2 Staphylococcus aureus2,74325.78%7,38969.46%2,75725.74%7,39269.03%
3 Streptococcus pneumoniae2,06519.41%9,45488.87%2,11519.75%9,50788.78%
4 Klebsiella pneumoniae1,18411.13%10,6381,20211.22%10,709 100.00%
2011-09-01J72014-06-23T5Hospital BB_STRPT_PNMNSSSRFGram-positiveStreptococcuspneumoniaeTRUE
2016-09-29N9Hospital AB_ESCHR_COLISSSRFGram-negativeEscherichiacoliTRUE
2011-01-04E8 Hospital B B_STRPT_PNMN R TRUE
2014-11-04C72017-12-28Z5 Hospital C B_STRPT_PNMNRR SRMGram-positiveStreptococcuspneumoniaeTRUE
2010-05-22X1Hospital CB_ESCHR_COLIRIS S R FGram-negativeEscherichiacoliTRUE
2011-03-20A1Hospital CB_STRPT_PNMNRRSRM Gram-positive Streptococcus pneumoniae TRUE
2016-05-13K9Hospital A2010-08-11C6Hospital C B_STRPT_PNMN S S TRUE
2014-01-21Q10Hospital D2012-08-24Z9Hospital A B_STRPT_PNMN S S
E. coli AMX217114723284646220412123104635
E. coli AMC342915710604646338915010964635
E. coli CIP33543408 01292464612274635
E. coli GEN40834065 056346465704635
K. pneumoniae AMX 0 01184118412021202
K. pneumoniae AMC936422061184927502251202
@@ -1070,34 +1078,34 @@ different bug/drug combinations, you can use the E. coli GEN -4083 +4065 0 -563 -4646 +570 +4635 K. pneumoniae GEN -1073 +1095 0 -111 -1184 +107 +1202 S. aureus GEN -2435 +2408 0 -308 -2743 +349 +2757 S. pneumoniae GEN 0 0 -2065 -2065 +2115 +2115 @@ -1129,7 +1137,7 @@ I (proportion_SI(), equa own:

 data_1st %>% resistance(AMX)
-# [1] 0.5455913
+# [1] 0.5429078

Or can be used in conjunction with group_by() and summarise(), both from the dplyr package:

@@ -1144,19 +1152,19 @@ own:

Hospital A -0.5382918 +0.5461974 Hospital B -0.5347408 +0.5343758 Hospital C -0.5776965 +0.5487149 Hospital D -0.5509126 +0.5482517 @@ -1181,23 +1189,23 @@ all isolates available for every group (i.e. values S, I or R):

Hospital A -0.5382918 -3173 +0.5461974 +3182 Hospital B -0.5347408 -3742 +0.5343758 +3709 Hospital C -0.5776965 -1641 +0.5487149 +1673 Hospital D -0.5509126 -2082 +0.5482517 +2145 @@ -1222,27 +1230,27 @@ therapies very easily:

Escherichia -0.7718467 -0.8788205 -0.9750323 +0.7635383 +0.8770227 +0.9766990 Klebsiella -0.8260135 -0.9062500 -0.9873311 +0.8128120 +0.9109817 +0.9833611 Staphylococcus -0.7907401 -0.8877142 -0.9817718 +0.7972434 +0.8734131 +0.9818643 Streptococcus -0.5438257 +0.5399527 0.0000000 -0.5438257 +0.5399527 @@ -1270,23 +1278,23 @@ classes, use a antibiotic class selector such as Hospital A -53.8% -25.3% +54.6% +27.7% Hospital B -53.5% -25.1% +53.4% +26.4% Hospital C -57.8% -30.1% +54.9% +25.2% Hospital D -55.1% -26.3% +54.8% +26.7% @@ -1402,18 +1410,16 @@ classes) <mic> and <disk>:

mic_values <- random_mic(size = 100) mic_values # Class 'mic' -# [1] 8 0.01 0.025 32 0.01 16 32 >=256 0.125 -# [10] 128 0.5 0.125 128 0.005 4 2 0.01 0.0625 -# [19] 0.025 4 <=0.001 0.025 0.002 0.125 0.0625 0.0625 0.01 -# [28] 0.025 <=0.001 16 8 0.005 0.0625 2 2 0.002 -# [37] 0.0625 64 0.025 0.005 0.125 0.002 2 16 0.005 -# [46] 4 16 >=256 0.25 64 128 1 8 0.0625 -# [55] 4 0.002 32 0.0625 8 128 0.0625 64 0.0625 -# [64] 8 0.125 1 <=0.001 128 0.002 8 1 0.002 -# [73] 0.002 64 0.125 0.005 0.5 8 0.025 0.125 0.005 -# [82] 0.005 0.002 <=0.001 0.0625 2 0.125 2 0.25 64 -# [91] 0.25 4 <=0.001 0.125 0.005 0.5 4 0.0625 64 -# [100] 2
+# [1] 8 64 2 1 0.002 128 0.01 0.25 2 0.125 +# [11] 16 0.01 256 4 64 2 0.002 256 0.01 8 +# [21] 0.025 0.025 16 0.025 8 1 128 0.125 4 0.001 +# [31] 4 256 4 1 0.01 0.025 1 0.001 0.002 2 +# [41] 0.001 2 0.01 128 0.01 1 16 0.5 64 0.0625 +# [51] 8 0.005 16 32 128 4 0.01 32 0.025 0.005 +# [61] 32 0.01 0.125 256 32 16 8 0.025 4 1 +# [71] 16 16 0.125 0.002 16 32 0.5 0.0625 256 2 +# [81] 0.005 0.01 1 0.005 0.125 0.0625 0.001 0.025 4 0.01 +# [91] 2 1 0.025 256 0.0625 0.001 0.125 0.005 0.0625 0.001
 # base R:
 plot(mic_values)
@@ -1447,10 +1453,10 @@ plotting:

disk_values <- random_disk(size = 100, mo = "E. coli", ab = "cipro") disk_values # Class 'disk' -# [1] 31 26 24 18 17 18 27 18 28 19 17 23 30 18 22 25 28 27 19 21 27 31 27 20 31 -# [26] 20 18 24 17 17 30 18 24 25 29 29 17 25 18 18 17 31 20 29 30 18 24 29 23 27 -# [51] 17 19 29 17 29 24 22 17 19 19 28 25 25 25 31 30 30 23 28 29 27 20 18 31 28 -# [76] 24 30 22 27 20 20 28 23 31 25 19 30 20 19 19 21 28 27 19 31 21 28 30 17 18 +# [1] 31 26 18 31 23 20 17 17 28 29 27 20 23 19 19 24 23 29 20 17 24 26 31 21 20 +# [26] 26 19 20 18 31 18 17 31 19 26 20 19 27 20 22 17 25 24 29 19 24 28 25 20 22 +# [51] 30 23 18 28 29 22 18 23 30 18 18 22 24 29 26 23 31 31 21 20 31 21 26 23 25 +# [76] 23 26 25 29 22 26 18 23 29 26 31 25 17 30 23 21 28 31 26 30 29 29 25 28 27
 # base R:
 plot(disk_values, mo = "E. coli", ab = "cipro")
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