Introduction
@@ -236,21 +236,21 @@ make the structure of your data generally look like this:
-| 2023-01-19 |
+2023-01-20 |
abcd |
Escherichia coli |
S |
S |
-| 2023-01-19 |
+2023-01-20 |
abcd |
Escherichia coli |
S |
R |
-| 2023-01-19 |
+2023-01-20 |
efgh |
Escherichia coli |
R |
@@ -400,67 +400,67 @@ data set:
-| 2015-07-08 |
-V2 |
+2015-03-26 |
+C9 |
+Hospital A |
+Escherichia coli |
+R |
+S |
+S |
+S |
+M |
+
+
+| 2014-11-12 |
+W8 |
Hospital B |
Escherichia coli |
S |
S |
S |
+R |
+F |
+
+
+| 2015-01-11 |
+X10 |
+Hospital B |
+Streptococcus pneumoniae |
+S |
+S |
+R |
S |
F |
-| 2017-05-03 |
-F10 |
-Hospital B |
-Streptococcus pneumoniae |
-R |
-R |
-S |
-S |
-M |
-
-
-| 2016-01-28 |
-T4 |
+2017-10-04 |
+V8 |
Hospital D |
Escherichia coli |
S |
-R |
-R |
-S |
-F |
-
-
-| 2013-03-27 |
-Y3 |
-Hospital B |
-Escherichia coli |
-R |
S |
S |
S |
F |
-| 2017-11-01 |
-E5 |
-Hospital A |
+2017-05-25 |
+E8 |
+Hospital D |
Escherichia coli |
-R |
-R |
+S |
+S |
S |
S |
M |
-| 2016-05-08 |
-H6 |
-Hospital A |
+2013-12-07 |
+N3 |
+Hospital B |
Escherichia coli |
S |
-S |
+I |
S |
S |
M |
@@ -499,16 +499,16 @@ Longest: 1
| 1 |
M |
-10,473 |
-52.37% |
-10,473 |
-52.37% |
+10,275 |
+51.38% |
+10,275 |
+51.38% |
| 2 |
F |
-9,527 |
-47.64% |
+9,725 |
+48.63% |
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 10,513 'phenotype-based' first isolates (52.6% of total where a
+# => Found 10,664 'phenotype-based' first isolates (53.3% of total where a
# microbial ID was available)
-So only 52.6% is suitable for resistance analysis! We can now filter
+
So only 53.3% is suitable for resistance analysis! We can now filter
on it with the filter() function, also from the
dplyr package:
-So we end up with 10,513 isolates for analysis. Now our data looks
+
So we end up with 10,664 isolates for analysis. Now our data looks
like:
-
+
@@ -652,7 +652,7 @@ like:
-
+
-| 3 |
-2016-01-28 |
-T4 |
-Hospital D |
-B_ESCHR_COLI |
-R |
-R |
-R |
-S |
-F |
-Gram-negative |
-Escherichia |
-coli |
-TRUE |
-
-
-| 5 |
-2017-11-01 |
-E5 |
+1 |
+2015-03-26 |
+C9 |
Hospital A |
B_ESCHR_COLI |
R |
-R |
+S |
S |
S |
M |
@@ -704,48 +688,32 @@ like:
coli |
TRUE |
+
+| 7 |
+2017-08-12 |
+B4 |
+Hospital A |
+B_KLBSL_PNMN |
+R |
+S |
+R |
+S |
+M |
+Gram-negative |
+Klebsiella |
+pneumoniae |
+TRUE |
+
| 8 |
-2011-07-01 |
-K2 |
-Hospital D |
-B_ESCHR_COLI |
-I |
-S |
-R |
-R |
-M |
-Gram-negative |
-Escherichia |
-coli |
-TRUE |
-
-
-| 10 |
-2010-08-12 |
-I2 |
-Hospital A |
-B_ESCHR_COLI |
-S |
-S |
-S |
-S |
-M |
-Gram-negative |
-Escherichia |
-coli |
-TRUE |
-
-
-| 12 |
-2011-09-04 |
-E2 |
+2015-07-29 |
+K7 |
Hospital D |
B_STPHY_AURS |
+S |
+S |
+S |
R |
-S |
-S |
-S |
M |
Gram-positive |
Staphylococcus |
@@ -753,14 +721,30 @@ like:
TRUE |
-| 14 |
-2015-05-09 |
-F7 |
+10 |
+2010-02-06 |
+N9 |
+Hospital A |
+B_ESCHR_COLI |
+S |
+S |
+S |
+S |
+F |
+Gram-negative |
+Escherichia |
+coli |
+TRUE |
+
+
+| 12 |
+2017-12-15 |
+M8 |
Hospital B |
B_ESCHR_COLI |
-R |
S |
-R |
+S |
+S |
S |
M |
Gram-negative |
@@ -768,6 +752,22 @@ like:
coli |
TRUE |
+
+| 15 |
+2014-01-10 |
+V9 |
+Hospital B |
+B_STPHY_AURS |
+R |
+S |
+S |
+S |
+F |
+Gram-positive |
+Staphylococcus |
+aureus |
+TRUE |
+
Time for the analysis!
@@ -801,8 +801,8 @@ readable:
data_1st %>% freq(genus, species)
Frequency table
Class: character
-Length: 10,513
-Available: 10,513 (100%, NA: 0 = 0%)
+Length: 10,664
+Available: 10,664 (100%, NA: 0 = 0%)
Unique: 4
Shortest: 16
Longest: 24
@@ -827,33 +827,33 @@ Longest: 24
| 1 |
Escherichia coli |
-4,589 |
-43.65% |
-4,589 |
-43.65% |
+4,704 |
+44.11% |
+4,704 |
+44.11% |
| 2 |
Staphylococcus aureus |
-2,637 |
-25.08% |
-7,226 |
-68.73% |
+2,741 |
+25.70% |
+7,445 |
+69.81% |
| 3 |
Streptococcus pneumoniae |
-2,072 |
-19.71% |
-9,298 |
-88.44% |
+2,062 |
+19.34% |
+9,507 |
+89.15% |
| 4 |
Klebsiella pneumoniae |
-1,215 |
-11.56% |
-10,513 |
+1,157 |
+10.85% |
+10,664 |
100.00% |
@@ -874,14 +874,14 @@ antibiotic class they are in:
-
+
-
+
@@ -902,42 +902,42 @@ antibiotic class they are in:
-| 2011-07-01 |
-K2 |
+2015-07-29 |
+K7 |
+Hospital D |
+B_STPHY_AURS |
+S |
+S |
+S |
+R |
+M |
+Gram-positive |
+Staphylococcus |
+aureus |
+TRUE |
+
+
+| 2015-09-30 |
+X1 |
Hospital D |
B_ESCHR_COLI |
-I |
+R |
S |
R |
R |
-M |
+F |
Gram-negative |
Escherichia |
coli |
TRUE |
-
-| 2012-11-09 |
-I6 |
-Hospital A |
-B_STRPT_PNMN |
-R |
-R |
-S |
-R |
-M |
-Gram-positive |
-Streptococcus |
-pneumoniae |
-TRUE |
-
-| 2014-06-12 |
-T1 |
+2011-12-11 |
+T5 |
Hospital A |
B_STRPT_PNMN |
-S |
-S |
+R |
+R |
S |
R |
F |
@@ -947,9 +947,9 @@ antibiotic class they are in:
TRUE |
-| 2013-01-17 |
-D2 |
-Hospital A |
+2010-01-19 |
+K7 |
+Hospital C |
B_STRPT_PNMN |
R |
R |
@@ -962,13 +962,13 @@ antibiotic class they are in:
TRUE |
-| 2011-02-13 |
-F3 |
+2013-05-13 |
+F4 |
Hospital B |
B_STRPT_PNMN |
-R |
-R |
S |
+S |
+R |
R |
M |
Gram-positive |
@@ -977,18 +977,18 @@ antibiotic class they are in:
TRUE |
-| 2011-02-13 |
-N3 |
-Hospital B |
-B_STRPT_PNMN |
-R |
+2010-01-29 |
+W4 |
+Hospital D |
+B_ESCHR_COLI |
R |
S |
+S |
R |
-M |
-Gram-positive |
-Streptococcus |
-pneumoniae |
+F |
+Gram-negative |
+Escherichia |
+coli |
TRUE |
@@ -1013,50 +1013,50 @@ different bug/drug combinations, you can use the
| E. coli |
AMX |
-2119 |
-139 |
-2331 |
-4589 |
+2227 |
+162 |
+2315 |
+4704 |
| E. coli |
AMC |
-3341 |
-170 |
-1078 |
-4589 |
+3431 |
+174 |
+1099 |
+4704 |
| E. coli |
CIP |
-3333 |
+3397 |
0 |
-1256 |
-4589 |
+1307 |
+4704 |
| E. coli |
GEN |
-4053 |
+4106 |
0 |
-536 |
-4589 |
+598 |
+4704 |
| K. pneumoniae |
AMX |
0 |
0 |
-1215 |
-1215 |
+1157 |
+1157 |
| K. pneumoniae |
AMC |
-959 |
-49 |
-207 |
-1215 |
+922 |
+47 |
+188 |
+1157 |
@@ -1078,34 +1078,34 @@ different bug/drug combinations, you can use the
| E. coli |
GEN |
-4053 |
+4106 |
0 |
-536 |
-4589 |
+598 |
+4704 |
| K. pneumoniae |
GEN |
-1109 |
+1047 |
0 |
-106 |
-1215 |
+110 |
+1157 |
| S. aureus |
GEN |
-2328 |
+2407 |
0 |
-309 |
-2637 |
+334 |
+2741 |
| S. pneumoniae |
GEN |
0 |
0 |
-2072 |
-2072 |
+2062 |
+2062 |
@@ -1137,7 +1137,7 @@ I (
proportion_SI(), equa
own:
+
# [1] 0.5381658
@@ -1152,19 +1152,19 @@ own:
| Hospital A |
-0.5437933 |
+0.5460547 |
| Hospital B |
-0.5506739 |
+0.5252972 |
| Hospital C |
-0.5457454 |
+0.5231231 |
| Hospital D |
-0.5605034 |
+0.5592912 |
@@ -1189,23 +1189,23 @@ all isolates available for every group (i.e. values S, I or R):
| Hospital A |
-0.5437933 |
-3174 |
+0.5460547 |
+3181 |
| Hospital B |
-0.5506739 |
-3710 |
+0.5252972 |
+3617 |
| Hospital C |
-0.5457454 |
-1563 |
+0.5231231 |
+1665 |
| Hospital D |
-0.5605034 |
-2066 |
+0.5592912 |
+2201 |
@@ -1230,27 +1230,27 @@ therapies very easily:
| Escherichia |
-0.7650904 |
-0.8831990 |
-0.9797341 |
+0.7663690 |
+0.8728741 |
+0.9770408 |
| Klebsiella |
-0.8296296 |
-0.9127572 |
-0.9901235 |
+0.8375108 |
+0.9049265 |
+0.9870354 |
| Staphylococcus |
-0.8058400 |
-0.8828214 |
-0.9821767 |
+0.7986136 |
+0.8781467 |
+0.9788398 |
| Streptococcus |
-0.5342664 |
+0.5446169 |
0.0000000 |
-0.5342664 |
+0.5446169 |
@@ -1278,23 +1278,23 @@ classes, use a antibiotic class selector such as
| Hospital A |
-54.4% |
-25.0% |
+54.6% |
+26.2% |
| Hospital B |
-55.1% |
-25.9% |
+52.5% |
+25.7% |
| Hospital C |
-54.6% |
-27.3% |
+52.3% |
+24.7% |
| Hospital D |
-56.1% |
-28.0% |
+55.9% |
+27.4% |
@@ -1410,18 +1410,16 @@ classes) <mic> and <disk>:
mic_values <- random_mic(size = 100)
mic_values
# Class 'mic'
-# [1] 64 0.005 16 0.025 2 <=0.001 8 0.0625 0.01
-# [10] 1 0.005 32 0.25 16 4 4 0.002 0.01
-# [19] 0.01 16 <=0.001 0.5 <=0.001 0.005 2 1 64
-# [28] 0.0625 0.125 0.002 0.025 0.25 8 0.025 0.0625 0.5
-# [37] 0.002 256 0.25 1 0.025 64 256 0.125 8
-# [46] 0.01 0.025 32 0.025 0.0625 8 0.5 2 0.5
-# [55] 16 64 32 0.025 64 0.01 0.25 0.002 0.5
-# [64] 128 0.5 0.25 0.005 4 1 <=0.001 256 2
-# [73] 4 256 2 0.005 0.002 4 16 0.002 16
-# [82] 256 0.25 0.025 256 4 0.125 1 <=0.001 0.5
-# [91] 32 4 0.25 0.5 0.002 0.025 0.005 2 1
-# [100] 4