From the shell:
# CRAN check from parent directory R CMD check AMR
Naming conventions in R/:
R/
aa_*.R
zz_deprecated.R
zzz.R
.onLoad
.onAttach
Key source files:
The package defines five S3 classes with full print/format/plot/vctrs support:
<mo>
as.mo()
<ab>
as.ab()
<av>
as.av()
<sir>
as.sir()
<mic>
as.mic()
<disk>
as.disk()
Pre-compiled in data/ (do not edit directly; regenerate via data-raw/ scripts):
data/
data-raw/
microorganisms.rda
antimicrobials.rda
antivirals.rda
clinical_breakpoints.rda
intrinsic_resistant.rda
example_isolates.rda
WHONET.rda
We can write this as:
Coverage=∑i(Incidencei×Susceptibilityi)\text{Coverage} = \sum_i (\text{Incidence}_i \times \text{Susceptibility}_i)
For example, suppose:
Then:
Coverage=(0.6×0.9)+(0.4×0.7)=0.82\text{Coverage} = (0.6 \times 0.9) + (0.4 \times 0.7) = 0.82
But in real data, incidence and susceptibility are estimated from samples, so they carry uncertainty. WISCA models this probabilistically, using conjugate Bayesian @@ -180,16 +180,16 @@ distributions.
Then the posterior incidence is:
p∼Dirichlet(α1+n1,…,αK+nK)p \sim \text{Dirichlet}(\alpha_1 + n_1, \ldots, \alpha_K + n_K)
To simulate from this, we use:
xi∼Gamma(αi+ni,1),pi=xi∑j=1Kxjx_i \sim \text{Gamma}(\alpha_i + n_i,\ 1), \quad p_i = \frac{x_i}{\sum_{j=1}^{K} x_j}
Each pathogen–regimen pair has a prior and data:
Then the posterior is:
θ∼Beta(α0+S,β0+N−S)\theta \sim \text{Beta}(\alpha_0 + S,\ \beta_0 + N - S)
vignettes/datasets.Rmd
datasets.Rmd
With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (mo_is_gram_negative() and mo_is_intrinsic_resistant()) and a column selection on two antibiotic groups (aminoglycosides() and carbapenems()), the reference data about all microorganisms and all antimicrobials in the AMR package make sure you get what you meant.
mo_is_gram_negative()
mo_is_intrinsic_resistant()
aminoglycosides()
carbapenems()
AMR
antibiogram(example_isolates, antimicrobials = c(aminoglycosides(), carbapenems())) -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) -#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
Or use antimicrobial selectors to select a series of antibiotic columns:
library(AMR) @@ -425,15 +430,16 @@ # calculate AMR using resistance(), over all aminoglycosides and polymyxins: summarise(across(c(aminoglycosides(), polymyxins()), resistance)) -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) +#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB +#> (tobramycin), AMK (amikacin), and KAN (kanamycin) #> ℹ For `polymyxins()` using column COL (colistin) #> Warning: There was 1 warning in `summarise()`. -#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`. +#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), +#> resistance)`. #> ℹ In group 3: `ward = "Outpatient"`. #> Caused by warning: -#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" -#> (whilst `minimum = 30`). +#> ! Introducing NA: only 23 results available for KAN in group: +#> ward = "Outpatient" (whilst `minimum = 30`). out #> # A tibble: 3 × 6 #> ward GEN TOB AMK KAN COL @@ -445,11 +451,12 @@ # transform the antibiotic columns to names: out %>% set_ab_names() #> # A tibble: 3 × 6 -#> ward gentamicin tobramycin amikacin kanamycin colistin -#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 Clinical 0.229 0.315 0.626 1 0.780 -#> 2 ICU 0.290 0.400 0.662 1 0.857 -#> 3 Outpatient 0.2 0.368 0.605 NA 0.889
# transform the antibiotic columns to names: out %>% set_ab_names() #> # A tibble: 3 × 6 -#> ward gentamicin tobramycin amikacin kanamycin colistin -#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 Clinical 0.229 0.315 0.626 1 0.780 -#> 2 ICU 0.290 0.400 0.662 1 0.857 -#> 3 Outpatient 0.2 0.368 0.605 NA 0.889
# transform the antibiotic column to ATC codes: out %>% set_ab_names(property = "atc") diff --git a/index.md b/index.md index e57b8a9bc..bd0c1276f 100644 --- a/index.md +++ b/index.md @@ -100,6 +100,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html), which work in base R, `dplyr` and `data.table`. ``` r + # AMR works great with dplyr, but it's not required or neccesary library(AMR) library(dplyr, warn.conflicts = FALSE) @@ -116,24 +117,26 @@ example_isolates %>% #> ℹ Using column mo as input for `mo_fullname()` #> ℹ Using column mo as input for `mo_is_gram_negative()` #> ℹ Using column mo as input for `mo_is_intrinsic_resistant()` -#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant -#> Phenotypes' v1.2 (2023). This note will be shown once per session. -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) -#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem) +#> ℹ Determining intrinsic resistance based on 'EUCAST Expected +#> Resistant Phenotypes' v1.2 (2023). This note will be shown +#> once per session. +#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB +#> (tobramycin), AMK (amikacin), and KAN (kanamycin) +#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM +#> (meropenem) #> # A tibble: 35 × 7 -#> bacteria GEN TOB AMK KAN IPM MEM -#> -#> 1 Pseudomonas aeruginosa I S NA R S NA -#> 2 Pseudomonas aeruginosa I S NA R S NA -#> 3 Pseudomonas aeruginosa I S NA R S NA -#> 4 Pseudomonas aeruginosa S S S R NA S -#> 5 Pseudomonas aeruginosa S S S R S S -#> 6 Pseudomonas aeruginosa S S S R S S -#> 7 Stenotrophomonas maltophilia R R R R R R -#> 8 Pseudomonas aeruginosa S S S R NA S -#> 9 Pseudomonas aeruginosa S S S R NA S -#> 10 Pseudomonas aeruginosa S S S R S S +#> bacteria GEN TOB AMK KAN IPM MEM +#> +#> 1 Pseudomonas aer… I S NA R S NA +#> 2 Pseudomonas aer… I S NA R S NA +#> 3 Pseudomonas aer… I S NA R S NA +#> 4 Pseudomonas aer… S S S R NA S +#> 5 Pseudomonas aer… S S S R S S +#> 6 Pseudomonas aer… S S S R S S +#> 7 Stenotrophomona… R R R R R R +#> 8 Pseudomonas aer… S S S R NA S +#> 9 Pseudomonas aer… S S S R NA S +#> 10 Pseudomonas aer… S S S R S S #> # ℹ 25 more rows ``` @@ -161,39 +164,42 @@ If used inside [R Markdown](https://rmarkdown.rstudio.com) or output format automatically (such as markdown, LaTeX, HTML, etc.). ``` r + antibiogram(example_isolates, antimicrobials = c(aminoglycosides(), carbapenems())) -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) -#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem) +#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB +#> (tobramycin), AMK (amikacin), and KAN (kanamycin) +#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM +#> (meropenem) ``` -| Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin | -|:-----------------|:---------------------|:--------------------|:---------------------|:----------------|:---------------------|:--------------------| -| CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) | -| *E. coli* | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | NA | 100% (99-100%,N=418) | 97% (96-99%,N=462) | -| *E. faecalis* | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | NA | 0% (0-9%,N=39) | -| *K. pneumoniae* | NA | 90% (79-96%,N=58) | 100% (93-100%,N=51) | NA | 100% (93-100%,N=53) | 90% (79-96%,N=58) | -| *P. aeruginosa* | NA | 100% (88-100%,N=30) | NA | 0% (0-12%,N=30) | NA | 100% (88-100%,N=30) | -| *P. mirabilis* | NA | 94% (80-99%,N=34) | 94% (79-99%,N=32) | NA | NA | 94% (80-99%,N=34) | -| *S. aureus* | NA | 99% (97-100%,N=233) | NA | NA | NA | 98% (92-100%,N=86) | -| *S. epidermidis* | 0% (0-8%,N=44) | 79% (71-85%,N=163) | NA | 0% (0-8%,N=44) | NA | 51% (40-61%,N=89) | -| *S. hominis* | NA | 92% (84-97%,N=80) | NA | NA | NA | 85% (74-93%,N=62) | -| *S. pneumoniae* | 0% (0-3%,N=117) | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | +| Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin | +|:---|:---|:---|:---|:---|:---|:---| +| CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) | +| *E. coli* | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | NA | 100% (99-100%,N=418) | 97% (96-99%,N=462) | +| *E. faecalis* | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | NA | 0% (0-9%,N=39) | +| *K. pneumoniae* | NA | 90% (79-96%,N=58) | 100% (93-100%,N=51) | NA | 100% (93-100%,N=53) | 90% (79-96%,N=58) | +| *P. aeruginosa* | NA | 100% (88-100%,N=30) | NA | 0% (0-12%,N=30) | NA | 100% (88-100%,N=30) | +| *P. mirabilis* | NA | 94% (80-99%,N=34) | 94% (79-99%,N=32) | NA | NA | 94% (80-99%,N=34) | +| *S. aureus* | NA | 99% (97-100%,N=233) | NA | NA | NA | 98% (92-100%,N=86) | +| *S. epidermidis* | 0% (0-8%,N=44) | 79% (71-85%,N=163) | NA | 0% (0-8%,N=44) | NA | 51% (40-61%,N=89) | +| *S. hominis* | NA | 92% (84-97%,N=80) | NA | NA | NA | 85% (74-93%,N=62) | +| *S. pneumoniae* | 0% (0-3%,N=117) | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | In combination antibiograms, it is clear that combined antimicrobials yield higher empiric coverage: ``` r + antibiogram(example_isolates, antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"), mo_transform = "gramstain") ``` -| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin | -|:--------------|:------------------------|:-------------------------------------|:-------------------------------------| -| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) | -| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) | +| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin | +|:---|:---|:---|:---| +| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) | +| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) | Like many other functions in this package, [`antibiogram()`](https://amr-for-r.org/reference/antibiogram.md) comes @@ -201,6 +207,7 @@ with support for 28 languages that are often detected automatically based on system language: ``` r + antibiogram(example_isolates, antimicrobials = c("cipro", "tobra", "genta"), # any arbitrary name or code will work mo_transform = "gramstain", @@ -221,6 +228,7 @@ with new scale functions, to allow plotting of log2-distributed MIC values and SIR values. ``` r + library(ggplot2) library(AMR) @@ -258,6 +266,7 @@ For a manual approach, you can use the `resistance` or function: ``` r + example_isolates %>% # group by ward: group_by(ward) %>% @@ -266,16 +275,18 @@ example_isolates %>% summarise(across(c(GEN, TOB), list(total_R = resistance, conf_int = function(x) sir_confidence_interval(x, collapse = "-")))) -#> ℹ `resistance()` assumes the EUCAST guideline and thus considers the 'I' -#> category susceptible. Set the `guideline` argument or the `AMR_guideline` -#> option to either "CLSI" or "EUCAST", see `?AMR-options`. +#> ℹ `resistance()` assumes the EUCAST guideline and thus +#> considers the 'I' category susceptible. Set the `guideline` +#> argument or the `AMR_guideline` option to either "CLSI" or +#> "EUCAST", see `?AMR-options`. #> ℹ This message will be shown once per session. #> # A tibble: 3 × 5 -#> ward GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int -#> -#> 1 Clinical 0.229 0.205-0.254 0.315 0.284-0.347 -#> 2 ICU 0.290 0.253-0.33 0.400 0.353-0.449 -#> 3 Outpatient 0.2 0.131-0.285 0.368 0.254-0.493 +#> ward GEN_total_R GEN_conf_int TOB_total_R +#> +#> 1 Clinical 0.229 0.205-0.254 0.315 +#> 2 ICU 0.290 0.253-0.33 0.400 +#> 3 Outpatient 0.2 0.131-0.285 0.368 +#> # ℹ 1 more variable: TOB_conf_int ``` Or use [antimicrobial @@ -283,6 +294,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html) to select a series of antibiotic columns: ``` r + library(AMR) library(dplyr) @@ -292,15 +304,16 @@ out <- example_isolates %>% # calculate AMR using resistance(), over all aminoglycosides and polymyxins: summarise(across(c(aminoglycosides(), polymyxins()), resistance)) -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) +#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB +#> (tobramycin), AMK (amikacin), and KAN (kanamycin) #> ℹ For `polymyxins()` using column COL (colistin) #> Warning: There was 1 warning in `summarise()`. -#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`. +#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), +#> resistance)`. #> ℹ In group 3: `ward = "Outpatient"`. #> Caused by warning: -#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" -#> (whilst `minimum = 30`). +#> ! Introducing NA: only 23 results available for KAN in group: +#> ward = "Outpatient" (whilst `minimum = 30`). out #> # A tibble: 3 × 6 #> ward GEN TOB AMK KAN COL @@ -311,17 +324,20 @@ out ``` ``` r + # transform the antibiotic columns to names: out %>% set_ab_names() #> # A tibble: 3 × 6 -#> ward gentamicin tobramycin amikacin kanamycin colistin -#> -#> 1 Clinical 0.229 0.315 0.626 1 0.780 -#> 2 ICU 0.290 0.400 0.662 1 0.857 -#> 3 Outpatient 0.2 0.368 0.605 NA 0.889 +#> ward gentamicin tobramycin amikacin kanamycin +#> +#> 1 Clinical 0.229 0.315 0.626 1 +#> 2 ICU 0.290 0.400 0.662 1 +#> 3 Outpatient 0.2 0.368 0.605 NA +#> # ℹ 1 more variable: colistin ``` ``` r + # transform the antibiotic column to ATC codes: out %>% set_ab_names(property = "atc") #> # A tibble: 3 × 6 @@ -393,6 +409,7 @@ This package is available [here on the official R network R from CRAN by using the command: ``` r + install.packages("AMR") ``` @@ -417,6 +434,7 @@ here](https://github.com/msberends/AMR/wiki/Developer-Guideline). To install the latest and unpublished beta version: ``` r + install.packages("AMR", repos = "beta.amr-for-r.org") # if this does not work, try to install directly from GitHub using the 'remotes' package: diff --git a/llms.txt b/llms.txt index 2c7a590b7..2d147432c 100644 --- a/llms.txt +++ b/llms.txt @@ -100,6 +100,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html), which work in base R, `dplyr` and `data.table`. ``` r + # AMR works great with dplyr, but it's not required or neccesary library(AMR) library(dplyr, warn.conflicts = FALSE) @@ -116,24 +117,26 @@ example_isolates %>% #> ℹ Using column mo as input for `mo_fullname()` #> ℹ Using column mo as input for `mo_is_gram_negative()` #> ℹ Using column mo as input for `mo_is_intrinsic_resistant()` -#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant -#> Phenotypes' v1.2 (2023). This note will be shown once per session. -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) -#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem) +#> ℹ Determining intrinsic resistance based on 'EUCAST Expected +#> Resistant Phenotypes' v1.2 (2023). This note will be shown +#> once per session. +#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB +#> (tobramycin), AMK (amikacin), and KAN (kanamycin) +#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM +#> (meropenem) #> # A tibble: 35 × 7 -#> bacteria GEN TOB AMK KAN IPM MEM -#> -#> 1 Pseudomonas aeruginosa I S NA R S NA -#> 2 Pseudomonas aeruginosa I S NA R S NA -#> 3 Pseudomonas aeruginosa I S NA R S NA -#> 4 Pseudomonas aeruginosa S S S R NA S -#> 5 Pseudomonas aeruginosa S S S R S S -#> 6 Pseudomonas aeruginosa S S S R S S -#> 7 Stenotrophomonas maltophilia R R R R R R -#> 8 Pseudomonas aeruginosa S S S R NA S -#> 9 Pseudomonas aeruginosa S S S R NA S -#> 10 Pseudomonas aeruginosa S S S R S S +#> bacteria GEN TOB AMK KAN IPM MEM +#> +#> 1 Pseudomonas aer… I S NA R S NA +#> 2 Pseudomonas aer… I S NA R S NA +#> 3 Pseudomonas aer… I S NA R S NA +#> 4 Pseudomonas aer… S S S R NA S +#> 5 Pseudomonas aer… S S S R S S +#> 6 Pseudomonas aer… S S S R S S +#> 7 Stenotrophomona… R R R R R R +#> 8 Pseudomonas aer… S S S R NA S +#> 9 Pseudomonas aer… S S S R NA S +#> 10 Pseudomonas aer… S S S R S S #> # ℹ 25 more rows ``` @@ -161,39 +164,42 @@ If used inside [R Markdown](https://rmarkdown.rstudio.com) or output format automatically (such as markdown, LaTeX, HTML, etc.). ``` r + antibiogram(example_isolates, antimicrobials = c(aminoglycosides(), carbapenems())) -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) -#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem) +#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB +#> (tobramycin), AMK (amikacin), and KAN (kanamycin) +#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM +#> (meropenem) ``` -| Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin | -|:-----------------|:---------------------|:--------------------|:---------------------|:----------------|:---------------------|:--------------------| -| CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) | -| *E. coli* | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | NA | 100% (99-100%,N=418) | 97% (96-99%,N=462) | -| *E. faecalis* | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | NA | 0% (0-9%,N=39) | -| *K. pneumoniae* | NA | 90% (79-96%,N=58) | 100% (93-100%,N=51) | NA | 100% (93-100%,N=53) | 90% (79-96%,N=58) | -| *P. aeruginosa* | NA | 100% (88-100%,N=30) | NA | 0% (0-12%,N=30) | NA | 100% (88-100%,N=30) | -| *P. mirabilis* | NA | 94% (80-99%,N=34) | 94% (79-99%,N=32) | NA | NA | 94% (80-99%,N=34) | -| *S. aureus* | NA | 99% (97-100%,N=233) | NA | NA | NA | 98% (92-100%,N=86) | -| *S. epidermidis* | 0% (0-8%,N=44) | 79% (71-85%,N=163) | NA | 0% (0-8%,N=44) | NA | 51% (40-61%,N=89) | -| *S. hominis* | NA | 92% (84-97%,N=80) | NA | NA | NA | 85% (74-93%,N=62) | -| *S. pneumoniae* | 0% (0-3%,N=117) | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | +| Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin | +|:---|:---|:---|:---|:---|:---|:---| +| CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) | +| *E. coli* | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | NA | 100% (99-100%,N=418) | 97% (96-99%,N=462) | +| *E. faecalis* | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | NA | 0% (0-9%,N=39) | +| *K. pneumoniae* | NA | 90% (79-96%,N=58) | 100% (93-100%,N=51) | NA | 100% (93-100%,N=53) | 90% (79-96%,N=58) | +| *P. aeruginosa* | NA | 100% (88-100%,N=30) | NA | 0% (0-12%,N=30) | NA | 100% (88-100%,N=30) | +| *P. mirabilis* | NA | 94% (80-99%,N=34) | 94% (79-99%,N=32) | NA | NA | 94% (80-99%,N=34) | +| *S. aureus* | NA | 99% (97-100%,N=233) | NA | NA | NA | 98% (92-100%,N=86) | +| *S. epidermidis* | 0% (0-8%,N=44) | 79% (71-85%,N=163) | NA | 0% (0-8%,N=44) | NA | 51% (40-61%,N=89) | +| *S. hominis* | NA | 92% (84-97%,N=80) | NA | NA | NA | 85% (74-93%,N=62) | +| *S. pneumoniae* | 0% (0-3%,N=117) | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | In combination antibiograms, it is clear that combined antimicrobials yield higher empiric coverage: ``` r + antibiogram(example_isolates, antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"), mo_transform = "gramstain") ``` -| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin | -|:--------------|:------------------------|:-------------------------------------|:-------------------------------------| -| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) | -| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) | +| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin | +|:---|:---|:---|:---| +| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) | +| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) | Like many other functions in this package, [`antibiogram()`](https://amr-for-r.org/reference/antibiogram.md) comes @@ -201,6 +207,7 @@ with support for 28 languages that are often detected automatically based on system language: ``` r + antibiogram(example_isolates, antimicrobials = c("cipro", "tobra", "genta"), # any arbitrary name or code will work mo_transform = "gramstain", @@ -221,6 +228,7 @@ with new scale functions, to allow plotting of log2-distributed MIC values and SIR values. ``` r + library(ggplot2) library(AMR) @@ -258,6 +266,7 @@ For a manual approach, you can use the `resistance` or function: ``` r + example_isolates %>% # group by ward: group_by(ward) %>% @@ -266,16 +275,18 @@ example_isolates %>% summarise(across(c(GEN, TOB), list(total_R = resistance, conf_int = function(x) sir_confidence_interval(x, collapse = "-")))) -#> ℹ `resistance()` assumes the EUCAST guideline and thus considers the 'I' -#> category susceptible. Set the `guideline` argument or the `AMR_guideline` -#> option to either "CLSI" or "EUCAST", see `?AMR-options`. +#> ℹ `resistance()` assumes the EUCAST guideline and thus +#> considers the 'I' category susceptible. Set the `guideline` +#> argument or the `AMR_guideline` option to either "CLSI" or +#> "EUCAST", see `?AMR-options`. #> ℹ This message will be shown once per session. #> # A tibble: 3 × 5 -#> ward GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int -#> -#> 1 Clinical 0.229 0.205-0.254 0.315 0.284-0.347 -#> 2 ICU 0.290 0.253-0.33 0.400 0.353-0.449 -#> 3 Outpatient 0.2 0.131-0.285 0.368 0.254-0.493 +#> ward GEN_total_R GEN_conf_int TOB_total_R +#> +#> 1 Clinical 0.229 0.205-0.254 0.315 +#> 2 ICU 0.290 0.253-0.33 0.400 +#> 3 Outpatient 0.2 0.131-0.285 0.368 +#> # ℹ 1 more variable: TOB_conf_int ``` Or use [antimicrobial @@ -283,6 +294,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html) to select a series of antibiotic columns: ``` r + library(AMR) library(dplyr) @@ -292,15 +304,16 @@ out <- example_isolates %>% # calculate AMR using resistance(), over all aminoglycosides and polymyxins: summarise(across(c(aminoglycosides(), polymyxins()), resistance)) -#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK -#> (amikacin), and KAN (kanamycin) +#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB +#> (tobramycin), AMK (amikacin), and KAN (kanamycin) #> ℹ For `polymyxins()` using column COL (colistin) #> Warning: There was 1 warning in `summarise()`. -#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`. +#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), +#> resistance)`. #> ℹ In group 3: `ward = "Outpatient"`. #> Caused by warning: -#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" -#> (whilst `minimum = 30`). +#> ! Introducing NA: only 23 results available for KAN in group: +#> ward = "Outpatient" (whilst `minimum = 30`). out #> # A tibble: 3 × 6 #> ward GEN TOB AMK KAN COL @@ -311,17 +324,20 @@ out ``` ``` r + # transform the antibiotic columns to names: out %>% set_ab_names() #> # A tibble: 3 × 6 -#> ward gentamicin tobramycin amikacin kanamycin colistin -#> -#> 1 Clinical 0.229 0.315 0.626 1 0.780 -#> 2 ICU 0.290 0.400 0.662 1 0.857 -#> 3 Outpatient 0.2 0.368 0.605 NA 0.889 +#> ward gentamicin tobramycin amikacin kanamycin +#> +#> 1 Clinical 0.229 0.315 0.626 1 +#> 2 ICU 0.290 0.400 0.662 1 +#> 3 Outpatient 0.2 0.368 0.605 NA +#> # ℹ 1 more variable: colistin ``` ``` r + # transform the antibiotic column to ATC codes: out %>% set_ab_names(property = "atc") #> # A tibble: 3 × 6 @@ -393,6 +409,7 @@ This package is available [here on the official R network R from CRAN by using the command: ``` r + install.packages("AMR") ``` @@ -417,6 +434,7 @@ here](https://github.com/msberends/AMR/wiki/Developer-Guideline). To install the latest and unpublished beta version: ``` r + install.packages("AMR", repos = "beta.amr-for-r.org") # if this does not work, try to install directly from GitHub using the 'remotes' package: diff --git a/news/index.html b/news/index.html index 91be66e82..3c3006bb3 100644 --- a/news/index.html +++ b/news/index.html @@ -7,7 +7,7 @@ AMR (for R) - 3.0.1.9052 + 3.0.1.9053 @@ -49,11 +49,17 @@
This will become release v3.1.0, intended for launch end of May.
clinical_breakpoints
recipes
future
parallel = TRUE
future::plan()
future::plan(future::multisession)
step_mic_log2()
step_sir_numeric()
tidyselect
NA
NA_ab_
NA_mo_
NA_character_
NA_integer_
"1"
"1e-3"
e
ETH
MTH
PHE
PHN
STH
THA
THI1
antibiogram()
patient
ward
info = FALSE
&&
||
nrow(breakpoints) == 0
info
reference_data
> breakpoint_R
< breakpoint_R
host = NA
cli
ab_group()