@@ -243,21 +243,21 @@ make the structure of your data generally look like this:
-
2023-04-14
+
2023-04-15
abcd
Escherichia coli
S
S
-
2023-04-14
+
2023-04-15
abcd
Escherichia coli
S
R
-
2023-04-14
+
2023-04-15
efgh
Escherichia coli
R
@@ -962,110 +962,110 @@ antibiograms:
Cardial
-E. coli (453-453)
-
66
-
60
+E. coli (450-450)
+
64
+
56
57
-
66
+
62
Respiratory
-E. coli (387-387)
+E. coli (411-411)
64
58
-
61
-
61
+
59
+
63
Rheumatic
-E. coli (410-410)
-
62
+E. coli (389-389)
+
63
+
61
57
-
56
-
60
+
64
Cardial
-K. pneumoniae (113-113)
-
62
+K. pneumoniae (96-96)
+
67
48
-
59
-
58
+
60
+
64
Respiratory
-K. pneumoniae (112-112)
-
62
-
56
+K. pneumoniae (109-109)
61
56
+
60
+
63
Rheumatic
-K. pneumoniae (91-91)
-
66
+K. pneumoniae (111-111)
+
62
+
53
+
57
54
-
56
-
68
Cardial
-S. aureus (212-212)
+S. aureus (219-219)
63
53
-
56
61
+
57
Respiratory
-S. aureus (234-234)
-
66
-
56
+S. aureus (235-235)
61
-
66
+
58
+
52
+
63
Rheumatic
-S. aureus (215-215)
-
64
-
61
-
55
-
62
+S. aureus (207-207)
+
70
+
59
+
59
+
70
Cardial
-S. pneumoniae (140-140)
+S. pneumoniae (141-141)
+
67
60
-
54
-
64
-
61
+
60
+
72
Respiratory
-S. pneumoniae (139-139)
-
66
-
56
-
57
-
68
+S. pneumoniae (124-124)
+
62
+
52
+
60
+
60
Rheumatic
-S. pneumoniae (120-120)
-
66
-
57
-
58
-
68
+S. pneumoniae (134-134)
+
63
+
56
+
59
+
64
@@ -1090,45 +1090,45 @@ antibiograms:
Cardial
-
Gram-negative (566-566)
-
65
-
57
+
Gram-negative (546-546)
65
+
55
+
63
Respiratory
-
Gram-negative (499-499)
-
64
-
58
-
60
+
Gram-negative (520-520)
+
63
+
57
+
63
Rheumatic
-
Gram-negative (501-501)
-
62
-
56
+
Gram-negative (500-500)
+
63
+
59
62
Cardial
-
Gram-positive (352-352)
+
Gram-positive (360-360)
+
64
+
56
62
-
54
-
61
Respiratory
-
Gram-positive (373-373)
-
66
+
Gram-positive (359-359)
+
62
56
-
67
+
62
Rheumatic
-
Gram-positive (335-335)
-
64
-
60
-
64
+
Gram-positive (341-341)
+
67
+
58
+
67
@@ -1152,45 +1152,45 @@ antibiograms:
Cardial
-
Gram-negative (566-566)
+
Gram-negative (546-546)
65
76
-
78
+
74
Respiratory
-
Gram-negative (499-499)
-
64
-
77
-
72
+
Gram-negative (520-520)
+
63
+
76
+
75
Rheumatic
-
Gram-negative (501-501)
-
62
-
74
-
74
+
Gram-negative (500-500)
+
63
+
76
+
75
Cardial
-
Gram-positive (352-352)
-
62
+
Gram-positive (360-360)
+
64
+
80
75
-
73
Respiratory
-
Gram-positive (373-373)
-
66
-
80
-
77
+
Gram-positive (359-359)
+
62
+
74
+
72
Rheumatic
-
Gram-positive (335-335)
-
64
-
76
-
76
+
Gram-positive (341-341)
+
67
+
78
+
79
diff --git a/articles/AMR_files/figure-html/unnamed-chunk-13-1.png b/articles/AMR_files/figure-html/unnamed-chunk-13-1.png
index c53fb2d4..ee246823 100644
Binary files a/articles/AMR_files/figure-html/unnamed-chunk-13-1.png and b/articles/AMR_files/figure-html/unnamed-chunk-13-1.png differ
diff --git a/articles/EUCAST.html b/articles/EUCAST.html
index 69a33956..993fe09a 100644
--- a/articles/EUCAST.html
+++ b/articles/EUCAST.html
@@ -38,7 +38,7 @@
AMR (for R)
- 2.0.0.9005
+ 2.0.0.9006
diff --git a/articles/MDR.html b/articles/MDR.html
index 4c94d481..b59e65c9 100644
--- a/articles/MDR.html
+++ b/articles/MDR.html
@@ -38,7 +38,7 @@
AMR (for R)
- 2.0.0.9005
+ 2.0.0.9006
@@ -385,19 +385,19 @@ names or codes, this would have worked exactly the same way:
head(my_TB_data)#> rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin
-#> 1 I I I R S S
-#> 2 S R R R R S
-#> 3 I R S I I S
-#> 4 I S S S S R
-#> 5 S I R I R R
-#> 6 S I I I I R
+#> 1 R S I I I I
+#> 2 I R S S I R
+#> 3 S S R I I I
+#> 4 R S S R S S
+#> 5 S R I I R R
+#> 6 S I I R I S#> kanamycin
-#> 1 S
-#> 2 R
+#> 1 R
+#> 2 I#> 3 S
-#> 4 I
+#> 4 S#> 5 R
-#> 6 I
+#> 6 R
We can now add the interpretation of MDR-TB to our data set. You can
use:
A data set with 52 149 rows and 22 columns, containing the following
+
A data set with 52 151 rows and 22 columns, containing the following
column names: mo, fullname, status, kingdom,
phylum, class, order, family,
genus, species, subspecies, rank,
@@ -206,7 +206,7 @@ column names: mo, fullname, status, kingdomgbif_renamed_to, prevalence, and snomed.
This data set is in R available as microorganisms, after
you load the AMR package.
-
It was last updated on 14 April 2023 09:12:26 UTC. Find more info
+
It was last updated on 14 April 2023 21:14:34 UTC. Find more info
about the structure of this data set here.
Direct download links:
@@ -283,7 +283,7 @@ Set Name ‘Microoganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL:
A data set with 18 308 rows and 11 columns, containing the following
+
A data set with 17 918 rows and 11 columns, containing the following
column names: guideline, method, site, mo,
rank_index, ab, ref_tbl, disk_dose,
breakpoint_S, breakpoint_R, and uti.
This data set is in R available as clinical_breakpoints,
after you load the AMR package.
-
It was last updated on 21 January 2023 22:47:20 UTC. Find more info
+
It was last updated on 14 April 2023 21:14:34 UTC. Find more info
about the structure of this data set here.
Direct download links:
@@ -891,7 +891,7 @@ about the structure of this data set tab-separated
-text file (1.9 MB)
+text file (1.8 MB)
Download as Microsoft
Excel workbook (0.8 MB)
@@ -900,16 +900,16 @@ Excel workbook (0.8 MB)
Feather file (0.7 MB)