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(v2.1.1.9262) fix knit printing
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Package: AMR
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Version: 2.1.1.9261
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Version: 2.1.1.9262
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Date: 2025-04-29
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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2
NEWS.md
2
NEWS.md
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# AMR 2.1.1.9261
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# AMR 2.1.1.9262
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*(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://amr-for-r.org/#get-this-package).)*
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@ -657,7 +657,7 @@ if (files_changed()) {
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}
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# Update index.md and README.md -------------------------------------------
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if (files_changed("man/microorganisms.Rd") | files_changed("man/antimicrobials.Rd") | files_changed("man/clinical_breakpoints.Rd") | files_changed("man/antibiogram.Rd")) {
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if (files_changed("man/microorganisms.Rd") | files_changed("man/antimicrobials.Rd") | files_changed("man/clinical_breakpoints.Rd") | files_changed("man/antibiogram.Rd") | files_changed("R/antibiogram.R")) {
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usethis::ui_info("Rendering {usethis::ui_field('index.md')} and {usethis::ui_field('README.md')}")
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suppressWarnings(rmarkdown::render("index.Rmd", quiet = TRUE))
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suppressWarnings(rmarkdown::render("README.Rmd", quiet = TRUE))
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37
index.md
37
index.md
@ -155,10 +155,9 @@ 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 Resistant
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#> Phenotypes' v1.2 (2023). This note will be shown 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 Determining intrinsic resistance based on 'EUCAST Expected Resistant Phenotypes' v1.2 (2023). This note will be shown once per
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#> session.
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#> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' (tobramycin), 'AMK' (amikacin), and 'KAN' (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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@ -196,23 +195,23 @@ output format automatically (such as markdown, LaTeX, HTML, etc.).
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``` r
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antibiogram(example_isolates,
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antimicrobials = c(aminoglycosides(), carbapenems()))
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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' (kanamycin)
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#> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)
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#> ℹ 502 combinations had less than minimum = 30 results and were ignored
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```
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| Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
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|:---|:---|:---|:---|:---|:---|:---|
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| 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) |
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| E. coli | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | | 100% (99-100%,N=418) | 97% (96-99%,N=462) |
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| E. faecalis | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | | 0% (0-9%,N=39) |
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| K. pneumoniae | | 90% (79-96%,N=58) | 100% (93-100%,N=51) | | 100% (93-100%,N=53) | 90% (79-96%,N=58) |
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| P. aeruginosa | | 100% (88-100%,N=30) | | 0% (0-12%,N=30) | | 100% (88-100%,N=30) |
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| P. mirabilis | | 94% (80-99%,N=34) | 94% (79-99%,N=32) | | | 94% (80-99%,N=34) |
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| S. aureus | | 99% (97-100%,N=233) | | | | 98% (92-100%,N=86) |
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| S. epidermidis | 0% (0-8%,N=44) | 79% (71-85%,N=163) | | 0% (0-8%,N=44) | | 51% (40-61%,N=89) |
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| S. hominis | | 92% (84-97%,N=80) | | | | 85% (74-93%,N=62) |
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| S. pneumoniae | 0% (0-3%,N=117) | 0% (0-3%,N=117) | | 0% (0-3%,N=117) | | 0% (0-3%,N=117) |
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| *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) |
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| *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) |
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| *K. pneumoniae* | NA | 90% (79-96%,N=58) | 100% (93-100%,N=51) | NA | 100% (93-100%,N=53) | 90% (79-96%,N=58) |
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| *P. aeruginosa* | NA | 100% (88-100%,N=30) | NA | 0% (0-12%,N=30) | NA | 100% (88-100%,N=30) |
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| *P. mirabilis* | NA | 94% (80-99%,N=34) | 94% (79-99%,N=32) | NA | NA | 94% (80-99%,N=34) |
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| *S. aureus* | NA | 99% (97-100%,N=233) | NA | NA | NA | 98% (92-100%,N=86) |
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| *S. epidermidis* | 0% (0-8%,N=44) | 79% (71-85%,N=163) | NA | 0% (0-8%,N=44) | NA | 51% (40-61%,N=89) |
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| *S. hominis* | NA | 92% (84-97%,N=80) | NA | NA | NA | 85% (74-93%,N=62) |
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| *S. pneumoniae* | 0% (0-3%,N=117) | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) | NA | 0% (0-3%,N=117) |
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In combination antibiograms, it is clear that combined antimicrobials
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yield higher empiric coverage:
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@ -221,6 +220,7 @@ yield higher empiric coverage:
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antibiogram(example_isolates,
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antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
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mo_transform = "gramstain")
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#> ℹ 3 combinations had less than minimum = 30 results and were ignored
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```
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| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
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@ -238,6 +238,7 @@ antibiogram(example_isolates,
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mo_transform = "gramstain",
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ab_transform = "name",
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language = "uk") # Ukrainian
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#> ℹ 3 combinations had less than minimum = 30 results and were ignored
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```
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| Збудник | Гентаміцин | Тобраміцин | Ципрофлоксацин |
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@ -321,15 +322,13 @@ 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' (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()), 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: ward =
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#> "Outpatient" (minimum = 30).
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#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" (minimum = 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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