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(v3.0.1.9088) add version number to intrinsic_resistant
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59
index.md
59
index.md
@@ -27,9 +27,12 @@
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<div style="display: flex; font-size: 0.8em;">
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<p style="text-align:left; width: 50%;">
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<small><a href="https://amr-for-r.org/">amr-for-r.org</a></small>
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</p>
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<p style="text-align:right; width: 50%;">
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<small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank">doi.org/10.18637/jss.v104.i03</a></small>
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</p>
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@@ -59,7 +62,7 @@ times](https://scholar.google.com/citations?view_op=view_citation&hl=en&citation
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in scientific research.
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After installing this package, R knows [**~97 000 distinct microbial
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species**](./reference/microorganisms.html) (updated mei 2026) and all
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species**](./reference/microorganisms.html) (updated May 2026) and all
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[**~620 antimicrobial and antiviral
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drugs**](./reference/antimicrobials.html) by name and code (including
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ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all
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@@ -170,13 +173,11 @@ example_isolates %>%
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#> ℹ Using column mo as input for `mo_fullname()`
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#> ℹ Using column mo as input for `mo_is_gram_negative()`
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#> ℹ Using column mo as input for `mo_is_intrinsic_resistant()`
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#> ℹ Determining intrinsic resistance based on 'EUCAST Expected
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#> Resistant Phenotypes' v1.2 (2023). This note will be shown
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#> once per session.
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#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
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#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
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#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
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#> (meropenem)
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#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant Phenotypes' v1.2 (2023).
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#> This note will be shown once per session.
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#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
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#> (kanamycin)
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#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
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#> # A tibble: 35 × 7
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#> bacteria GEN TOB AMK KAN IPM MEM
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#> <chr> <sir> <sir> <sir> <sir> <sir> <sir>
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@@ -226,8 +227,8 @@ wisca(example_isolates,
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```
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| Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
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|:------------------------|:-------------------------------------|:-------------------------------------|
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| 70% (64.8-75.1%) | 93.6% (92.1-95%) | 89.9% (86.9-92.3%) |
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|:---|:---|:---|
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| 70.2% (64.6-75.4%) | 93.6% (92.1-95%) | 89.9% (87-92.5%) |
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WISCA supports stratification by any clinical variable, so you can
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generate syndrome-specific or ward-specific coverage estimates:
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@@ -241,10 +242,10 @@ wisca(example_isolates,
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```
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| Syndromic Group | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
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|:----------------|:------------------------|:-------------------------------------|:-------------------------------------|
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| Clinical | 74.7% (69-80.3%) | 93.6% (92-95.2%) | 90.4% (86.8-93.1%) |
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| ICU | 56.9% (48.7-66%) | 86.8% (83.6-90%) | 82.8% (78.3-87.3%) |
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| Outpatient | 57.2% (46-68.2%) | 76.5% (70.3-82.2%) | 67.7% (57.3-77.2%) |
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|:---|:---|:---|:---|
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| Clinical | 74.7% (68.9-80.8%) | 93.7% (92.1-95.2%) | 90.5% (87-93.2%) |
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| ICU | 57% (48.2-65.7%) | 86.8% (83.4-89.8%) | 83% (78-87.6%) |
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| Outpatient | 57.2% (46.2-68.9%) | 76.6% (70.1-82.1%) | 67.7% (57.6-77.5%) |
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**For AMR surveillance**, traditional antibiograms remain the right tool
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for tracking resistance per species over time:
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@@ -253,14 +254,13 @@ for tracking resistance per species over time:
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antibiogram(example_isolates,
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mo_transform = "gramstain",
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antimicrobials = c("AMC", carbapenems(), "TZP"))
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#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
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#> (meropenem)
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#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
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```
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| Pathogen | Amoxicillin/clavulanic acid | Imipenem | Meropenem | Piperacillin/tazobactam |
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|:--------------|:----------------------------|:--------------------|:---------------------|:------------------------|
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| Gram-negative | 76% (73-79%,N=726) | 99% (98-100%,N=631) | 100% (99-100%,N=626) | 88% (85-91%,N=641) |
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| Gram-positive | 76% (74-79%,N=1138) | 81% (75-85%,N=257) | 77% (70-82%,N=203) | 86% (82-89%,N=345) |
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| Pathogen | Amoxicillin/clavulanic acid | Imipenem | Meropenem | Piperacillin/tazobactam |
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|:---|:---|:---|:---|:---|
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| Gram-negative | 76% (73-79%,N=726) | 99% (98-100%,N=631) | 100% (99-100%,N=626) | 88% (85-91%,N=641) |
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| Gram-positive | 76% (74-79%,N=1138) | 81% (75-85%,N=257) | 77% (70-82%,N=203) | 86% (82-89%,N=345) |
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Combination antibiograms show the additional coverage gained by adding a
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second agent, stratified by species:
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@@ -271,10 +271,10 @@ antibiogram(example_isolates,
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antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"))
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```
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| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
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|:--------------|:------------------------|:-------------------------------------|:-------------------------------------|
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| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) |
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| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) |
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| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
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|:---|:---|:---|:---|
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| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) |
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| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) |
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Like many other functions in this package, `antibiogram()` and `wisca()`
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come with support for 28 languages that are often detected automatically
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@@ -369,16 +369,15 @@ out <- example_isolates %>%
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# calculate AMR using resistance(), over all aminoglycosides and polymyxins:
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summarise(across(c(aminoglycosides(), polymyxins()),
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resistance))
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#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
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#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
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#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
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#> (kanamycin)
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#> ℹ For `polymyxins()` using column COL (colistin)
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#> Warning: There was 1 warning in `summarise()`.
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#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()),
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#> resistance)`.
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#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
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#> ℹ In group 3: `ward = "Outpatient"`.
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#> Caused by warning:
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#> ! Introducing NA: only 23 results available for KAN in group:
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#> ward = "Outpatient" (whilst `minimum = 30`).
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#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" (whilst `minimum =
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#> 30`).
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out
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#> # A tibble: 3 × 6
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#> ward GEN TOB AMK KAN COL
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