Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by using evidence-based methods, as described in https://doi.org/10.18637/jss.v104.i03.
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antibiotics
data set and updated to the latest version (LOINC v2.76)as.mic("1.28e-2")
)AMR_locale
is setPublished by msberends over 1 year ago
clinical_breakpoints
data set for usage in as.sir()
. EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretationsdosage
data setclinical_breakpoints
data set now also contains epidemiological cut-off (ECOFF) values and CLSI animal breakpoints. These two new breakpoint types can be used for MIC/disk interpretation using as.sir(..., breakpoint_type = "ECOFF")
oras.sir(..., breakpoint_type = "animal")
, which is an important new addition for veterinary microbiology.microorganisms.groups
and are used in clinical breakpoint interpretation. For example, CLSI 2023 contains breakpoints for the RGM group (Rapidly Growing Mycobacterium, containing over 80 species) which is now supported by our package.microorganisms
data set
mo_oxygen_tolerance()
to retrieve the valuesmo_is_anaerobic()
to determine which genera/species are obligate anaerobic bacteriamo_info()
.xpt
) to our download page to use in SAS softwareas.mo()
by giving more weight to fungimo_rank()
now returns NA
for 'unknown' microorganisms (B_ANAER
, B_ANAER-NEG
, B_ANAER-POS
, B_GRAMN
, B_GRAMP
, F_FUNGUS
, F_YEAST
, and UNKNOWN
)as.sir()
sir_interpretation_history()
clinical_breakpoints
as.mo()
that led to coercion of NA
values when using custom microorganism codesicu_exclude
in first_isolates()
as.mo()
algorithm:
keep_synonyms
argument when using MO codes as inputminimum_matching_score
argumentmicroorganisms.codes
reference_df
in as.mo()
as.sir()
as.sir()