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@@ -3,9 +3,9 @@
- Provides an **all-in-one solution** for antimicrobial resistance (AMR)
data analysis in a One Health approach
- Peer-reviewed, used in over 175 countries, available in 28 languages
- Generates **antibiograms** - traditional, combined, syndromic, and
even WISCA
- Provides the **full microbiological taxonomy** of ~79 000 distinct
- Generates **antibiograms** - WISCA for empiric coverage estimates, or
traditional/syndromic for AMR surveillance
- Provides the **full microbiological taxonomy** of ~97 000 distinct
species and extensive info of ~620 antimicrobial drugs
- Applies **CLSI 2011-2026** and **EUCAST 2011-2026** clinical and
veterinary breakpoints, and ECOFFs, for MIC and disk zone
@@ -49,7 +49,7 @@ formed the basis of two PhD theses ([DOI
10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and
[DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)).
After installing this package, R knows [**~79 000 distinct microbial
After installing this package, R knows [**~97 000 distinct microbial
species**](https://amr-for-r.org/reference/microorganisms.md) (updated
June 2024) and all [**~620 antimicrobial and antiviral
drugs**](https://amr-for-r.org/reference/antimicrobials.md) by name and
@@ -117,26 +117,24 @@ 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
#> <chr> <sir> <sir> <sir> <sir> <sir> <sir>
#> 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
#> bacteria GEN TOB AMK KAN IPM MEM
#> <chr> <sir> <sir> <sir> <sir> <sir> <sir>
#> 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
#> # ℹ 25 more rows
```
@@ -167,10 +165,9 @@ output format automatically (such as markdown, LaTeX, HTML, etc.).
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 |
@@ -275,18 +272,16 @@ 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
#> <chr> <dbl> <chr> <dbl>
#> 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 <chr>
#> ward GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int
#> <chr> <dbl> <chr> <dbl> <chr>
#> 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
```
Or use [antimicrobial
@@ -304,16 +299,15 @@ 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
@@ -328,12 +322,11 @@ out
# transform the antibiotic columns to names:
out %>% set_ab_names()
#> # A tibble: 3 × 6
#> ward gentamicin tobramycin amikacin kanamycin
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 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 <dbl>
#> 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
```
``` r
@@ -544,6 +537,7 @@ to add your own custom microorganisms to this package.
[`mo_is_intrinsic_resistant()`](https://amr-for-r.org/reference/mo_property.md)
[`mo_oxygen_tolerance()`](https://amr-for-r.org/reference/mo_property.md)
[`mo_is_anaerobic()`](https://amr-for-r.org/reference/mo_property.md)
[`mo_morphology()`](https://amr-for-r.org/reference/mo_property.md)
[`mo_snomed()`](https://amr-for-r.org/reference/mo_property.md)
[`mo_ref()`](https://amr-for-r.org/reference/mo_property.md)
[`mo_authors()`](https://amr-for-r.org/reference/mo_property.md)
@@ -666,13 +660,15 @@ antibiotic classes
or determine multi-drug resistant microorganisms (MDRO,
[`mdro()`](https://amr-for-r.org/reference/mdro.md)).
- [`antibiogram()`](https://amr-for-r.org/reference/antibiogram.md)
[`wisca()`](https://amr-for-r.org/reference/antibiogram.md)
- [`wisca()`](https://amr-for-r.org/reference/antibiogram.md)
[`antibiogram()`](https://amr-for-r.org/reference/antibiogram.md)
[`retrieve_wisca_parameters()`](https://amr-for-r.org/reference/antibiogram.md)
[`plot(`*`<antibiogram>`*`)`](https://amr-for-r.org/reference/antibiogram.md)
[`autoplot(`*`<antibiogram>`*`)`](https://amr-for-r.org/reference/antibiogram.md)
[`wisca_plot()`](https://amr-for-r.org/reference/antibiogram.md)
[`knit_print(`*`<antibiogram>`*`)`](https://amr-for-r.org/reference/antibiogram.md)
: Generate Traditional, Combination, Syndromic, or WISCA Antibiograms
: Generate Antibiograms (WISCA, Traditional, Combination, or
Syndromic)
- [`resistance()`](https://amr-for-r.org/reference/proportion.md)
[`susceptibility()`](https://amr-for-r.org/reference/proportion.md)
@@ -880,7 +876,7 @@ our [How To’s](https://amr-for-r.org/articles/index.md) for more
information about how to work with functions in this package.
- [`microorganisms`](https://amr-for-r.org/reference/microorganisms.md)
: Data Set with 78 679 Taxonomic Records of Microorganisms
: Data Set with 96 982 Taxonomic Records of Microorganisms
- [`antimicrobials`](https://amr-for-r.org/reference/antimicrobials.md)
[`antibiotics`](https://amr-for-r.org/reference/antimicrobials.md)
[`antivirals`](https://amr-for-r.org/reference/antimicrobials.md) :
@@ -892,9 +888,9 @@ information about how to work with functions in this package.
- [`esbl_isolates`](https://amr-for-r.org/reference/esbl_isolates.md) :
Data Set with 500 ESBL Isolates
- [`microorganisms.codes`](https://amr-for-r.org/reference/microorganisms.codes.md)
: Data Set with 6 050 Common Microorganism Codes
: Data Set with 6 029 Common Microorganism Codes
- [`microorganisms.groups`](https://amr-for-r.org/reference/microorganisms.groups.md)
: Data Set with 534 Microorganisms In Species Groups
: Data Set with 530 Microorganisms In Species Groups
- [`intrinsic_resistant`](https://amr-for-r.org/reference/intrinsic_resistant.md)
: Data Set Denoting Bacterial Intrinsic Resistance
- [`dosage`](https://amr-for-r.org/reference/dosage.md) : Data Set with