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italicise antibiogram

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dr. M.S. (Matthijs) Berends
2023-02-17 09:42:51 +01:00
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@ -85,18 +85,18 @@ antibiogram(example_isolates,
antibiotics = c(aminoglycosides(), carbapenems()))
```
|Pathogen (N min-max) | AMK| GEN| IPM| KAN| MEM| TOB|
|:----------------------|---:|---:|---:|---:|---:|---:|
|CoNS (43-309) | 0| 86| 52| 0| 52| 22|
|E. coli (0-462) | 100| 98| 100| NA| 100| 97|
|E. faecalis (0-39) | 0| 0| 100| 0| NA| 0|
|K. pneumoniae (0-58) | NA| 90| 100| NA| 100| 90|
|P. aeruginosa (17-30) | NA| 100| NA| 0| NA| 100|
|P. mirabilis (0-34) | NA| 94| 94| NA| NA| 94|
|S. aureus (2-233) | NA| 99| NA| NA| NA| 98|
|S. epidermidis (8-163) | 0| 79| NA| 0| NA| 51|
|S. hominis (3-80) | NA| 92| NA| NA| NA| 85|
|S. pneumoniae (11-117) | 0| 0| NA| 0| NA| 0|
|Pathogen (N min-max) | AMK| GEN| IPM| KAN| MEM| TOB|
|:------------------------|---:|---:|---:|---:|---:|---:|
|CoNS (43-309) | 0| 86| 52| 0| 52| 22|
|*E. coli* (0-462) | 100| 98| 100| | 100| 97|
|*E. faecalis* (0-39) | 0| 0| 100| 0| | 0|
|*K. pneumoniae* (0-58) | | 90| 100| | 100| 90|
|*P. aeruginosa* (17-30) | | 100| | 0| | 100|
|*P. mirabilis* (0-34) | | 94| 94| | | 94|
|*S. aureus* (2-233) | | 99| | | | 98|
|*S. epidermidis* (8-163) | 0| 79| | 0| | 51|
|*S. hominis* (3-80) | | 92| | | | 85|
|*S. pneumoniae* (11-117) | 0| 0| | 0| | 0|
In combination antibiograms, it is clear that combined antibiotics yield higher empiric coverage:
@ -111,7 +111,7 @@ antibiogram(example_isolates,
|Gram-negative (641-693) | 88| 99| 98|
|Gram-positive (345-1044) | 86| 98| 95|
Like many other functions in this package, `antibiograms()` comes with support for 20 languages that are often detected automatically based on system language:
Like many other functions in this package, `antibiogram()` comes with support for 20 languages that are often detected automatically based on system language:
```r
antibiogram(example_isolates,
@ -129,6 +129,8 @@ antibiogram(example_isolates,
#### Calculating resistance per group
For a manual approach, you can use the `resistance` or `susceptibility()` function:
```r
library(AMR)
library(dplyr)
@ -147,7 +149,7 @@ out
|:-----------|------:|------:|------:|------:|------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | NA | 0.889 |
| Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
```r
# transform the antibiotic columns to names:
@ -158,7 +160,7 @@ out %>% set_ab_names()
|:-----------|-----------:|-----------:|----------|----------:|----------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | NA | 0.889 |
| Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
```r
# transform the antibiotic column to ATC codes:
@ -169,7 +171,7 @@ out %>% set_ab_names(property = "atc")
|:-----------|-----------:|-----------:|----------|----------:|----------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | NA | 0.889 |
| Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
### What else can you do with this package?