@@ -167,7 +162,7 @@
How to conduct AMR data analysis
Dr. Matthijs Berends
- 21 August 2022
+ 25 August 2022
Source: vignettes/AMR.Rmd
AMR.Rmd
@@ -175,7 +170,7 @@
-Note: values on this page will change with every 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 21 August 2022.
+Note: values on this page will change with every 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 25 August 2022.
Introduction
@@ -206,21 +201,21 @@
-| 2022-08-21 |
+2022-08-25 |
abcd |
Escherichia coli |
S |
S |
-| 2022-08-21 |
+2022-08-25 |
abcd |
Escherichia coli |
S |
R |
-| 2022-08-21 |
+2022-08-25 |
efgh |
Escherichia coli |
R |
@@ -317,71 +312,71 @@
-| 2011-06-19 |
-N8 |
+2010-03-22 |
+I8 |
+Hospital A |
+Escherichia coli |
+S |
+S |
+S |
+S |
+M |
+
+
+| 2012-04-13 |
+G1 |
+Hospital B |
+Escherichia coli |
+R |
+S |
+R |
+R |
+M |
+
+
+| 2014-11-21 |
+D5 |
Hospital D |
-Escherichia coli |
-R |
-R |
-S |
-S |
-F |
-
-
-| 2013-07-08 |
-U10 |
-Hospital A |
-Escherichia coli |
-S |
-S |
-S |
-S |
-F |
-
-
-| 2015-07-14 |
-N3 |
-Hospital B |
-Escherichia coli |
-S |
-S |
-R |
-S |
-M |
-
-
-| 2014-07-29 |
-J1 |
-Hospital B |
-Streptococcus pneumoniae |
-S |
-S |
-S |
-S |
-M |
-
-
-| 2015-03-05 |
-A9 |
-Hospital C |
-Escherichia coli |
-S |
-I |
-S |
-S |
-M |
-
-
-| 2017-10-20 |
-P10 |
-Hospital A |
Staphylococcus aureus |
S |
S |
+S |
+S |
+M |
+
+
+| 2010-01-18 |
+T4 |
+Hospital C |
+Streptococcus pneumoniae |
R |
S |
+S |
+S |
F |
+
+| 2012-07-14 |
+M9 |
+Hospital C |
+Staphylococcus aureus |
+R |
+S |
+S |
+S |
+M |
+
+
+| 2010-02-17 |
+H3 |
+Hospital B |
+Escherichia coli |
+R |
+R |
+S |
+S |
+M |
+
Now, let’s start the cleaning and the analysis!
@@ -414,16 +409,16 @@ Longest: 1
| 1 |
M |
-10,328 |
-51.64% |
-10,328 |
-51.64% |
+10,334 |
+51.67% |
+10,334 |
+51.67% |
| 2 |
F |
-9,672 |
-48.36% |
+9,666 |
+48.33% |
20,000 |
100.00% |
@@ -477,9 +472,9 @@ Longest: 1
# ℹ Using column 'patient_id' as input for `col_patient_id`.
# Basing inclusion on all antimicrobial results, using a points threshold of
# 2
-
# => Found 10,619 'phenotype-based' first isolates (53.1% of total where a
+
# => Found 10,754 'phenotype-based' first isolates (53.8% of total where a
# microbial ID was available)
-So only 53.1% is suitable for resistance analysis! We can now filter on it with the filter() function, also from the dplyr package:
+So only 53.8% is suitable for resistance analysis! We can now filter on it with the filter() function, also from the dplyr package:
@@ -487,10 +482,10 @@ Longest: 1
-So we end up with 10,619 isolates for analysis. Now our data looks like:
+So we end up with 10,754 isolates for analysis. Now our data looks like:
-
+
@@ -503,7 +498,7 @@ Longest: 1
-
+
@@ -525,74 +520,26 @@ Longest: 1
-| 5 |
-2015-03-05 |
-A9 |
-Hospital C |
-B_ESCHR_COLI |
-S |
-S |
-S |
-S |
-M |
-Gram-negative |
-Escherichia |
-coli |
-TRUE |
-
-
-| 6 |
-2017-10-20 |
-P10 |
-Hospital A |
-B_STPHY_AURS |
-S |
-S |
-R |
-S |
-F |
-Gram-positive |
-Staphylococcus |
-aureus |
-TRUE |
-
-
-| 8 |
-2013-03-11 |
-S7 |
-Hospital C |
-B_ESCHR_COLI |
-R |
-S |
-R |
-S |
-F |
-Gram-negative |
-Escherichia |
-coli |
-TRUE |
-
-
-| 9 |
-2012-06-14 |
-I1 |
-Hospital C |
-B_ESCHR_COLI |
-S |
-S |
-S |
-S |
-M |
-Gram-negative |
-Escherichia |
-coli |
-TRUE |
-
-
-| 10 |
-2010-11-23 |
-V10 |
+2 |
+2012-04-13 |
+G1 |
Hospital B |
+B_ESCHR_COLI |
+R |
+S |
+R |
+R |
+M |
+Gram-negative |
+Escherichia |
+coli |
+TRUE |
+
+
+| 4 |
+2010-01-18 |
+T4 |
+Hospital C |
B_STRPT_PNMN |
R |
R |
@@ -604,17 +551,65 @@ Longest: 1
pneumoniae |
TRUE |
+
+| 6 |
+2010-02-17 |
+H3 |
+Hospital B |
+B_ESCHR_COLI |
+R |
+R |
+S |
+S |
+M |
+Gram-negative |
+Escherichia |
+coli |
+TRUE |
+
-| 13 |
-2012-03-06 |
-R5 |
+7 |
+2013-01-04 |
+C5 |
Hospital B |
B_ESCHR_COLI |
S |
S |
+R |
+S |
+M |
+Gram-negative |
+Escherichia |
+coli |
+TRUE |
+
+
+| 10 |
+2014-12-10 |
+G7 |
+Hospital D |
+B_ESCHR_COLI |
+R |
+R |
S |
S |
-F |
+M |
+Gram-negative |
+Escherichia |
+coli |
+TRUE |
+
+
+| 11 |
+2015-10-09 |
+B3 |
+Hospital A |
+B_ESCHR_COLI |
+I |
+S |
+R |
+S |
+M |
Gram-negative |
Escherichia |
coli |
@@ -641,8 +636,8 @@ Longest: 1
data_1st %>% freq(genus, species)
Frequency table
Class: character
-Length: 10,619
-Available: 10,619 (100.0%, NA: 0 = 0.0%)
+Length: 10,754
+Available: 10,754 (100.0%, NA: 0 = 0.0%)
Unique: 4
Shortest: 16
Longest: 24
@@ -659,33 +654,33 @@ Longest: 24
| 1 |
Escherichia coli |
-4,632 |
-43.62% |
-4,632 |
-43.62% |
+4,654 |
+43.28% |
+4,654 |
+43.28% |
| 2 |
Staphylococcus aureus |
-2,742 |
-25.82% |
-7,374 |
-69.44% |
+2,782 |
+25.87% |
+7,436 |
+69.15% |
| 3 |
Streptococcus pneumoniae |
-2,062 |
-19.42% |
-9,436 |
-88.86% |
+2,109 |
+19.61% |
+9,545 |
+88.76% |
| 4 |
Klebsiella pneumoniae |
-1,183 |
-11.14% |
-10,619 |
+1,209 |
+11.24% |
+10,754 |
100.00% |
@@ -704,14 +699,14 @@ Longest: 24
-
+
-
+
@@ -732,9 +727,24 @@ Longest: 24
-| 2010-11-23 |
-V10 |
+2012-04-13 |
+G1 |
Hospital B |
+B_ESCHR_COLI |
+R |
+S |
+R |
+R |
+M |
+Gram-negative |
+Escherichia |
+coli |
+TRUE |
+
+
+| 2010-01-18 |
+T4 |
+Hospital C |
B_STRPT_PNMN |
R |
R |
@@ -746,24 +756,24 @@ Longest: 24
pneumoniae |
TRUE |
-
-| 2011-11-01 |
-B1 |
+
+| 2014-06-06 |
+Y10 |
Hospital D |
B_STRPT_PNMN |
-S |
-S |
-S |
R |
-M |
+R |
+R |
+R |
+F |
Gram-positive |
Streptococcus |
pneumoniae |
TRUE |
-
-| 2017-01-30 |
-H5 |
+
+| 2011-12-29 |
+J7 |
Hospital C |
B_STRPT_PNMN |
S |
@@ -776,43 +786,28 @@ Longest: 24
pneumoniae |
TRUE |
-
-| 2015-12-11 |
-I5 |
-Hospital B |
-B_STRPT_PNMN |
-R |
+
+| 2010-05-28 |
+C3 |
+Hospital A |
+B_KLBSL_PNMN |
R |
S |
+S |
R |
M |
-Gram-positive |
-Streptococcus |
+Gram-negative |
+Klebsiella |
pneumoniae |
TRUE |
-
-| 2017-08-04 |
-O3 |
-Hospital B |
-B_STPHY_AURS |
-I |
-S |
-S |
-R |
-F |
-Gram-positive |
-Staphylococcus |
-aureus |
-TRUE |
-
-| 2014-10-06 |
-V8 |
-Hospital A |
+2012-12-04 |
+V6 |
+Hospital D |
B_STRPT_PNMN |
-S |
-S |
+R |
+R |
S |
R |
F |
@@ -842,50 +837,50 @@ Longest: 24
| E. coli |
AMX |
-2203 |
-123 |
-2306 |
-4632 |
+2225 |
+122 |
+2307 |
+4654 |
| E. coli |
AMC |
-3385 |
-145 |
-1102 |
-4632 |
+3423 |
+151 |
+1080 |
+4654 |
| E. coli |
CIP |
-3390 |
+3411 |
0 |
-1242 |
-4632 |
+1243 |
+4654 |
| E. coli |
GEN |
-4049 |
+4041 |
0 |
-583 |
-4632 |
+613 |
+4654 |
| K. pneumoniae |
AMX |
0 |
0 |
-1183 |
-1183 |
+1209 |
+1209 |
| K. pneumoniae |
AMC |
-929 |
+948 |
54 |
-200 |
-1183 |
+207 |
+1209 |
@@ -908,34 +903,34 @@ Longest: 24
| E. coli |
GEN |
-4049 |
+4041 |
0 |
-583 |
-4632 |
+613 |
+4654 |
| K. pneumoniae |
GEN |
-1078 |
+1069 |
0 |
-105 |
-1183 |
+140 |
+1209 |
| S. aureus |
GEN |
-2430 |
+2474 |
0 |
-312 |
-2742 |
+308 |
+2782 |
| S. pneumoniae |
GEN |
0 |
0 |
-2062 |
-2062 |
+2109 |
+2109 |
@@ -949,7 +944,7 @@ Longest: 24
As per the EUCAST guideline of 2019, we calculate resistance as the proportion of R (proportion_R(), equal to resistance()) and susceptibility as the proportion of S and I (proportion_SI(), equal to susceptibility()). These functions can be used on their own:
+# [1] 0.5432397
Or can be used in conjunction with group_by() and summarise(), both from the dplyr package:
data_1st %>%
@@ -963,19 +958,19 @@ Longest: 24
| Hospital A |
-0.5382868 |
+0.5458167 |
| Hospital B |
-0.5447543 |
+0.5334954 |
| Hospital C |
-0.5595602 |
+0.5404571 |
| Hospital D |
-0.5353630 |
+0.5580645 |
@@ -994,23 +989,23 @@ Longest: 24
| Hospital A |
-0.5382868 |
-3082 |
+0.5458167 |
+3263 |
| Hospital B |
-0.5447543 |
-3765 |
+0.5334954 |
+3702 |
| Hospital C |
-0.5595602 |
-1637 |
+0.5404571 |
+1619 |
| Hospital D |
-0.5353630 |
-2135 |
+0.5580645 |
+2170 |
@@ -1031,27 +1026,27 @@ Longest: 24
| Escherichia |
-0.7620898 |
-0.8741364 |
-0.9771157 |
+0.7679416 |
+0.8682853 |
+0.9735711 |
| Klebsiella |
-0.8309383 |
-0.9112426 |
-0.9805579 |
+0.8287841 |
+0.8842018 |
+0.9809760 |
| Staphylococcus |
-0.7884756 |
-0.8862144 |
-0.9817651 |
+0.7890007 |
+0.8892883 |
+0.9780733 |
| Streptococcus |
-0.5354025 |
+0.5372214 |
0.0000000 |
-0.5354025 |
+0.5372214 |
@@ -1076,23 +1071,23 @@ Longest: 24
| Hospital A |
-53.8% |
-26.2% |
+54.6% |
+26.9% |
| Hospital B |
-54.5% |
-27.0% |
+53.3% |
+25.9% |
| Hospital C |
-56.0% |
-27.9% |
+54.0% |
+25.6% |
| Hospital D |
-53.5% |
-26.1% |
+55.8% |
+27.5% |
@@ -1176,16 +1171,16 @@ Longest: 24
mic_values <- random_mic(size = 100)
mic_values
# Class <mic>
-# [1] 256 16 0.002 0.025 8 0.025 32 0.025 0.01 256
-# [11] 16 0.01 32 0.025 0.01 0.0625 2 0.25 128 0.005
-# [21] 0.01 16 0.125 0.25 0.01 0.001 8 0.025 8 1
-# [31] 0.025 0.25 0.0625 256 0.001 0.025 0.001 8 0.01 0.025
-# [41] 0.25 8 64 8 0.25 4 1 0.0625 0.0625 0.5
-# [51] 2 0.002 16 0.002 0.01 16 0.25 64 8 256
-# [61] 0.005 0.0625 1 64 64 0.5 128 0.002 32 0.002
-# [71] 128 128 0.5 0.002 0.25 0.5 0.125 1 16 64
-# [81] 128 32 0.025 128 16 32 32 32 0.002 0.125
-# [91] 0.5 0.0625 0.5 128 0.125 128 8 0.25 128 0.25
# base R:
plot(mic_values)
# base R:
plot(disk_values, mo = "E. coli", ab = "cipro")