library(dplyr)
library(readr)
library(tidyr)
library(janitor)
# WHONET version of 16th Feb 2024
whonet_breakpoints <- read_tsv("WHONET/Resources/Breakpoints.txt", na = c("", "NA", "-"),
show_col_types = FALSE, guess_max = Inf) %>%
filter(GUIDELINES %in% c("CLSI", "EUCAST"))
dim(whonet_breakpoints)[1] 31397 21whonet_breakpoints |>
filter(BREAKPOINT_TYPE != "Human")# A tibble: 5,287 × 21
GUIDELINES YEAR TEST_METHOD POTENCY ORGANISM_CODE ORGANISM_CODE_TYPE
<chr> <dbl> <chr> <chr> <chr> <chr>
1 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
2 CLSI 2019 MIC <NA> EBC FAMILY_CODE
3 CLSI 2019 DISK 10μg EBC FAMILY_CODE
4 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
5 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
6 CLSI 2019 MIC <NA> EBC FAMILY_CODE
7 CLSI 2019 DISK 10μg EBC FAMILY_CODE
8 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
9 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
10 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
# ℹ 5,277 more rows
# ℹ 15 more variables: BREAKPOINT_TYPE <chr>, HOST <chr>,
# SITE_OF_INFECTION <chr>, REFERENCE_TABLE <chr>, REFERENCE_SEQUENCE <dbl>,
# WHONET_ABX_CODE <chr>, WHONET_TEST <chr>, R <dbl>, I <chr>, SDD <lgl>,
# S <dbl>, ECV_ECOFF <dbl>, DATE_ENTERED <date>, DATE_MODIFIED <date>,
# COMMENTS <lgl>whonet_breakpoints |>
filter(BREAKPOINT_TYPE != "Human") |>
count(BREAKPOINT_TYPE)# A tibble: 2 × 2
BREAKPOINT_TYPE n
<chr> <int>
1 Animal 1683
2 ECOFF 3604whonet_breakpoints |>
filter(BREAKPOINT_TYPE == "Animal")# A tibble: 1,683 × 21
GUIDELINES YEAR TEST_METHOD POTENCY ORGANISM_CODE ORGANISM_CODE_TYPE
<chr> <dbl> <chr> <chr> <chr> <chr>
1 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
2 CLSI 2019 MIC <NA> EBC FAMILY_CODE
3 CLSI 2019 DISK 10μg EBC FAMILY_CODE
4 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
5 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
6 CLSI 2019 MIC <NA> EBC FAMILY_CODE
7 CLSI 2019 DISK 10μg EBC FAMILY_CODE
8 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
9 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
10 CLSI 2019 MIC <NA> eco WHONET_ORG_CODE
# ℹ 1,673 more rows
# ℹ 15 more variables: BREAKPOINT_TYPE <chr>, HOST <chr>,
# SITE_OF_INFECTION <chr>, REFERENCE_TABLE <chr>, REFERENCE_SEQUENCE <dbl>,
# WHONET_ABX_CODE <chr>, WHONET_TEST <chr>, R <dbl>, I <chr>, SDD <lgl>,
# S <dbl>, ECV_ECOFF <dbl>, DATE_ENTERED <date>, DATE_MODIFIED <date>,
# COMMENTS <lgl>whonet_breakpoints |>
filter(BREAKPOINT_TYPE == "Animal") |>
count(YEAR, HOST, REFERENCE_TABLE = gsub("VET[0-9]+ ", "", REFERENCE_TABLE)) |>
pivot_wider(names_from = YEAR, values_from = n, values_fill = list(n = 0)) |>
arrange(HOST, REFERENCE_TABLE) |>
adorn_totals(name = "TOTAL") HOST REFERENCE_TABLE 2019 2020 2021 2022 2023
Aquatic Table 12 4 4 4 4 4
Cats Table 2A 12 12 14 14 15
Cats Table 2B 2 2 2 2 2
Cats Table 2C 14 14 14 14 14
Cats Table 2D 10 10 10 10 3
Cats Table 2E 0 0 0 0 10
Cats Table 2H 6 6 6 6 6
Cattle Florfenicol rationale 0 0 3 0 0
Cattle Histophilus somni 0 0 0 1 1
Cattle Mannheimia haemolytica 0 0 0 1 1
Cattle Pasteurella multocida 0 0 0 1 1
Cattle Table 2A 3 3 5 5 1
Cattle Table 2C 6 6 6 6 0
Cattle Table 2C-1 0 0 2 2 2
Cattle Table 2D 18 18 18 18 0
Cattle Table 2E 0 0 10 8 2
Cattle Table 2G 21 21 21 21 21
Cattle Table 2H 19 19 19 19 21
Cattle Table 2J 17 17 17 17 19
Cattle Table 2K 0 0 0 0 6
Cattle Table 2L 0 0 0 0 12
Cattle Table 2M 0 0 0 0 28
Dogs Table 2A 35 35 39 39 41
Dogs Table 2B 4 4 8 8 8
Dogs Table 2C 34 34 34 34 34
Dogs Table 2D 19 19 19 19 4
Dogs Table 2E 0 0 0 0 19
Dogs Table 2H 3 3 3 3 3
Horses Table 2A 4 4 5 5 5
Horses Table 2B 3 3 3 3 3
Horses Table 2C 4 4 3 3 3
Horses Table 2C-1 0 0 2 2 2
Horses Table 2D 11 11 11 11 5
Horses Table 2E 0 0 0 0 6
Horses Table 2I 2 2 2 2 2
Horses (adults) Table 2A 3 3 3 3 3
Horses (adults) Table 2B 1 1 1 1 1
Horses (adults) Table 2C 1 1 1 1 1
Horses (adults) Table 2D 2 2 2 2 1
Horses (adults) Table 2E 0 0 0 0 1
Horses (foals) Table 2A 1 1 1 1 1
Horses (foals) Table 2B 1 1 1 1 1
Horses (foals) Table 2C 1 1 1 1 1
Horses (foals) Table 2D 2 2 2 2 1
Horses (foals) Table 2E 0 0 0 0 1
Poultry Table 2A 2 2 2 2 2
Swine Table 2A 4 4 4 4 4
Swine Table 2D 8 8 8 8 0
Swine Table 2E 0 0 0 0 8
Swine Table 2F 7 7 7 7 7
Swine Table 2H 15 15 15 15 17
Swine Table 2I 15 15 15 15 17
TOTAL - 314 314 343 341 371whonet_breakpoints |>
filter(HOST == "Cats", YEAR >= 2021) |>
select(GUIDELINES, YEAR, TEST_METHOD, ORGANISM_CODE, R, S) |>
mutate(MO_NAME = AMR::mo_shortname(ORGANISM_CODE), .before = R) |>
as.data.frame() GUIDELINES YEAR TEST_METHOD ORGANISM_CODE MO_NAME R S
1 CLSI 2021 DISK EBC Enterobacterales 16.0 23.000
2 CLSI 2021 MIC EBC Enterobacterales 4.0 0.500
3 CLSI 2021 DISK EBC Enterobacterales 14.0 20.000
4 CLSI 2021 MIC EBC Enterobacterales 4.0 1.000
5 CLSI 2021 DISK EBC Enterobacterales 17.0 23.000
6 CLSI 2021 MIC EBC Enterobacterales 8.0 1.000
7 CLSI 2021 DISK eco E. coli NA 18.000
8 CLSI 2021 MIC eco E. coli 1.0 0.250
9 CLSI 2021 MIC eco E. coli NA 8.000
10 CLSI 2021 MIC eco E. coli 1.0 0.250
11 CLSI 2021 DISK eco E. coli 20.0 24.000
12 CLSI 2021 MIC eco E. coli 8.0 2.000
13 CLSI 2021 DISK eco E. coli 19.0 24.000
14 CLSI 2021 MIC eco E. coli 2.0 0.250
15 CLSI 2021 DISK pae P. aeruginosa 16.0 23.000
16 CLSI 2021 MIC pae P. aeruginosa 4.0 0.500
17 CLSI 2021 MIC pam P. multocida 1.0 0.250
18 CLSI 2021 MIC pam P. multocida 1.0 0.250
19 CLSI 2021 DISK pam P. multocida 20.0 24.000
20 CLSI 2021 MIC pam P. multocida 0.5 0.125
21 CLSI 2021 DISK pam P. multocida NA 24.000
22 CLSI 2021 MIC pam P. multocida NA 0.250
23 CLSI 2021 DISK psd S. pseudintermedius 19.0 24.000
24 CLSI 2021 MIC psd S. pseudintermedius 2.0 0.250
25 CLSI 2021 DISK sau S. aureus 19.0 24.000
26 CLSI 2021 MIC sau S. aureus 2.0 0.250
27 CLSI 2021 DISK sfe S. felis 19.0 24.000
28 CLSI 2021 MIC sfe S. felis 2.0 0.250
29 CLSI 2021 MIC STA Staphylococcus 1.0 0.250
30 CLSI 2021 MIC STA Staphylococcus 1.0 0.250
31 CLSI 2021 DISK STA Staphylococcus 16.0 23.000
32 CLSI 2021 MIC STA Staphylococcus 4.0 0.500
33 CLSI 2021 DISK STA Staphylococcus 14.0 20.000
34 CLSI 2021 MIC STA Staphylococcus 4.0 1.000
35 CLSI 2021 DISK STA Staphylococcus 17.0 23.000
36 CLSI 2021 MIC STA Staphylococcus 8.0 1.000
37 CLSI 2021 MIC STR Streptococcus 1.0 0.250
38 CLSI 2021 MIC STR Streptococcus 1.0 0.250
39 CLSI 2021 DISK STR Streptococcus 16.0 23.000
40 CLSI 2021 MIC STR Streptococcus 4.0 0.500
41 CLSI 2021 DISK STR Streptococcus 14.0 20.000
42 CLSI 2021 MIC STR Streptococcus 4.0 1.000
43 CLSI 2021 DISK STR Streptococcus 17.0 23.000
44 CLSI 2021 MIC STR Streptococcus 8.0 1.000
45 CLSI 2021 DISK tcn S. canis NA 24.000
46 CLSI 2021 MIC tcn S. canis NA 0.250
47 CLSI 2022 MIC eco E. coli 1.0 0.250
48 CLSI 2022 MIC eco E. coli 8.0 2.000
49 CLSI 2022 DISK eco E. coli 20.0 24.000
50 CLSI 2022 MIC eco E. coli 1.0 0.250
51 CLSI 2022 DISK EBC Enterobacterales 16.0 23.000
52 CLSI 2022 MIC EBC Enterobacterales 4.0 0.500
53 CLSI 2022 DISK EBC Enterobacterales 14.0 20.000
54 CLSI 2022 MIC EBC Enterobacterales 4.0 1.000
55 CLSI 2022 DISK EBC Enterobacterales 17.0 23.000
56 CLSI 2022 MIC EBC Enterobacterales 8.0 1.000
57 CLSI 2022 DISK eco E. coli 19.0 24.000
58 CLSI 2022 MIC eco E. coli 2.0 0.250
59 CLSI 2022 DISK pae P. aeruginosa 16.0 23.000
60 CLSI 2022 MIC pae P. aeruginosa 4.0 0.500
61 CLSI 2022 MIC STA Staphylococcus 1.0 0.250
62 CLSI 2022 MIC STA Staphylococcus 1.0 0.250
63 CLSI 2022 DISK STA Staphylococcus 16.0 23.000
64 CLSI 2022 MIC STA Staphylococcus 4.0 0.500
65 CLSI 2022 DISK STA Staphylococcus 14.0 20.000
66 CLSI 2022 MIC STA Staphylococcus 4.0 1.000
67 CLSI 2022 DISK STA Staphylococcus 17.0 23.000
68 CLSI 2022 MIC STA Staphylococcus 8.0 1.000
69 CLSI 2022 DISK psd S. pseudintermedius 19.0 24.000
70 CLSI 2022 DISK sau S. aureus 19.0 24.000
71 CLSI 2022 DISK sfe S. felis 19.0 24.000
72 CLSI 2022 MIC psd S. pseudintermedius 2.0 0.250
73 CLSI 2022 MIC sau S. aureus 2.0 0.250
74 CLSI 2022 MIC sfe S. felis 2.0 0.250
75 CLSI 2022 MIC STR Streptococcus 1.0 0.250
76 CLSI 2022 MIC STR Streptococcus 1.0 0.250
77 CLSI 2022 DISK STR Streptococcus 16.0 23.000
78 CLSI 2022 MIC STR Streptococcus 4.0 0.500
79 CLSI 2022 DISK STR Streptococcus 14.0 20.000
80 CLSI 2022 MIC STR Streptococcus 4.0 1.000
81 CLSI 2022 DISK STR Streptococcus 17.0 23.000
82 CLSI 2022 MIC STR Streptococcus 8.0 1.000
83 CLSI 2022 DISK tcn S. canis NA 24.000
84 CLSI 2022 MIC tcn S. canis NA 0.250
85 CLSI 2022 MIC pam P. multocida 1.0 0.250
86 CLSI 2022 MIC pam P. multocida 1.0 0.250
87 CLSI 2022 DISK pam P. multocida 20.0 24.000
88 CLSI 2022 MIC pam P. multocida 0.5 0.125
89 CLSI 2022 DISK pam P. multocida NA 24.000
90 CLSI 2022 MIC pam P. multocida NA 0.250
91 CLSI 2022 MIC eco E. coli NA 8.000
92 CLSI 2022 DISK eco E. coli NA 18.000
93 CLSI 2023 MIC eco E. coli 1.0 0.250
94 CLSI 2023 MIC eco E. coli 8.0 2.000
95 CLSI 2023 DISK eco E. coli 20.0 24.000
96 CLSI 2023 MIC eco E. coli 1.0 0.250
97 CLSI 2023 DISK EBC Enterobacterales 16.0 23.000
98 CLSI 2023 MIC EBC Enterobacterales 4.0 0.500
99 CLSI 2023 DISK EBC Enterobacterales 14.0 20.000
100 CLSI 2023 MIC EBC Enterobacterales 4.0 1.000
101 CLSI 2023 DISK EBC Enterobacterales 17.0 23.000
102 CLSI 2023 MIC EBC Enterobacterales 8.0 1.000
103 CLSI 2023 DISK eco E. coli 19.0 24.000
104 CLSI 2023 MIC eco E. coli 2.0 0.250
105 CLSI 2023 DISK pae P. aeruginosa 16.0 23.000
106 CLSI 2023 MIC pae P. aeruginosa 4.0 0.500
107 CLSI 2023 MIC STA Staphylococcus 1.0 0.250
108 CLSI 2023 MIC STA Staphylococcus 1.0 0.250
109 CLSI 2023 DISK STA Staphylococcus 16.0 23.000
110 CLSI 2023 MIC STA Staphylococcus 4.0 0.500
111 CLSI 2023 DISK STA Staphylococcus 14.0 20.000
112 CLSI 2023 MIC STA Staphylococcus 4.0 1.000
113 CLSI 2023 DISK STA Staphylococcus 17.0 23.000
114 CLSI 2023 MIC STA Staphylococcus 8.0 1.000
115 CLSI 2023 DISK psd S. pseudintermedius 19.0 24.000
116 CLSI 2023 DISK sau S. aureus 19.0 24.000
117 CLSI 2023 DISK sfe S. felis 19.0 24.000
118 CLSI 2023 MIC psd S. pseudintermedius 2.0 0.250
119 CLSI 2023 MIC sau S. aureus 2.0 0.250
120 CLSI 2023 MIC sfe S. felis 2.0 0.250
121 CLSI 2023 MIC STR Streptococcus 1.0 0.250
122 CLSI 2023 MIC STR Streptococcus 1.0 0.250
123 CLSI 2023 DISK STR Streptococcus 16.0 23.000
124 CLSI 2023 MIC STR Streptococcus 4.0 0.500
125 CLSI 2023 DISK STR Streptococcus 14.0 20.000
126 CLSI 2023 MIC STR Streptococcus 4.0 1.000
127 CLSI 2023 DISK STR Streptococcus 17.0 23.000
128 CLSI 2023 MIC STR Streptococcus 8.0 1.000
129 CLSI 2023 DISK tcn S. canis NA 24.000
130 CLSI 2023 MIC tcn S. canis NA 0.250
131 CLSI 2023 MIC pam P. multocida 1.0 0.250
132 CLSI 2023 MIC pam P. multocida 1.0 0.250
133 CLSI 2023 DISK pam P. multocida 20.0 24.000
134 CLSI 2023 MIC pam P. multocida 0.5 0.125
135 CLSI 2023 DISK pam P. multocida NA 24.000
136 CLSI 2023 MIC pam P. multocida NA 0.250
137 CLSI 2023 MIC eco E. coli NA 8.000
138 CLSI 2023 DISK eco E. coli NA 18.000
139 CLSI 2023 DISK eco E. coli 8.0 17.000
140 CLSI 2023 MIC EBC Enterobacterales 16.0 8.000
141 CLSI 2023 DISK EBC Enterobacterales 16.0 17.000
142 CLSI 2023 MIC EBC Enterobacterales 16.0 8.000whonet_breakpoints |>
filter(HOST == "Cats", YEAR == 2023) |>
mutate(MO = AMR::mo_shortname(ORGANISM_CODE),
AB = AMR::ab_name(WHONET_ABX_CODE),
SITE_OF_INFECTION = substr(SITE_OF_INFECTION, 1, 25)) |>
arrange(MO, AB) |>
select(MO, AB, SITE_OF_INFECTION) |>
as.data.frame() MO AB SITE_OF_INFECTION
1 E. coli Amoxicillin/clavulanic acid Skin, soft tissue
2 E. coli Amoxicillin/clavulanic acid Uncomplicated urinary tra
3 E. coli Amoxicillin/clavulanic acid Uncomplicated urinary tra
4 E. coli Ampicillin Skin, soft tissue, uncomp
5 E. coli Ampicillin Uncomplicated urinary tra
6 E. coli Cefovecin Uncomplicated urinary tra
7 E. coli Cefovecin Uncomplicated urinary tra
8 E. coli Pradofloxacin Skin, respiratory
9 E. coli Pradofloxacin Skin, respiratory
10 Enterobacterales Amoxicillin/clavulanic acid Uncomplicated urinary tra
11 Enterobacterales Ampicillin Uncomplicated urinary tra
12 Enterobacterales Ampicillin Uncomplicated urinary tra
13 Enterobacterales Enrofloxacin Skin, soft tissue
14 Enterobacterales Enrofloxacin Skin, soft tissue
15 Enterobacterales Marbofloxacin Skin, soft tissue
16 Enterobacterales Marbofloxacin Skin, soft tissue
17 Enterobacterales Orbifloxacin Skin, soft tissue
18 Enterobacterales Orbifloxacin Skin, soft tissue
19 P. aeruginosa Enrofloxacin Skin, soft tissue
20 P. aeruginosa Enrofloxacin Skin, soft tissue
21 P. multocida Amoxicillin/clavulanic acid Skin, soft tissue, uncomp
22 P. multocida Ampicillin Skin, soft tissue, uncomp
23 P. multocida Cefovecin Skin, soft tissue
24 P. multocida Cefovecin Skin, soft tissue
25 P. multocida Pradofloxacin Skin, respiratory
26 P. multocida Pradofloxacin Skin, respiratory
27 S. aureus Pradofloxacin Skin, respiratory
28 S. aureus Pradofloxacin Skin, respiratory
29 S. canis Pradofloxacin Skin, respiratory
30 S. canis Pradofloxacin Skin, respiratory
31 S. felis Pradofloxacin Skin, respiratory
32 S. felis Pradofloxacin Skin, respiratory
33 S. pseudintermedius Pradofloxacin Skin, respiratory
34 S. pseudintermedius Pradofloxacin Skin, respiratory
35 Staphylococcus Amoxicillin/clavulanic acid Skin, soft tissue, uncomp
36 Staphylococcus Ampicillin Skin, soft tissue, uncomp
37 Staphylococcus Enrofloxacin Skin, soft tissue
38 Staphylococcus Enrofloxacin Skin, soft tissue
39 Staphylococcus Marbofloxacin Skin, soft tissue
40 Staphylococcus Marbofloxacin Skin, soft tissue
41 Staphylococcus Orbifloxacin Skin, soft tissue
42 Staphylococcus Orbifloxacin Skin, soft tissue
43 Streptococcus Amoxicillin/clavulanic acid Skin, soft tissue, uncomp
44 Streptococcus Ampicillin Skin, soft tissue, uncomp
45 Streptococcus Enrofloxacin Skin, soft tissue
46 Streptococcus Enrofloxacin Skin, soft tissue
47 Streptococcus Marbofloxacin Skin, soft tissue
48 Streptococcus Marbofloxacin Skin, soft tissue
49 Streptococcus Orbifloxacin Skin, soft tissue
50 Streptococcus Orbifloxacin Skin, soft tissue