Determine which isolates are multidrug-resistant organisms (MDRO) according to international and national guidelines.
mdro( x, guideline = "CMI2012", col_mo = NULL, info = interactive(), pct_required_classes = 0.5, combine_SI = TRUE, verbose = FALSE, ... ) brmo(x, guideline = "BRMO", ...) mrgn(x, guideline = "MRGN", ...) mdr_tb(x, guideline = "TB", ...) mdr_cmi2012(x, guideline = "CMI2012", ...) eucast_exceptional_phenotypes(x, guideline = "EUCAST", ...)
data with antibiotic columns, like e.g.
a specific guideline to follow. When left empty, the publication by Magiorakos et al. (2012, Clinical Microbiology and Infection) will be followed, please see Details.
a logical to indicate whether progress should be printed to the console
minimal required percentage of antimicrobial classes that must be available per isolate, rounded down. For example, with the default guideline, 17 antimicrobial classes must be available for S. aureus. Setting this
a logical to indicate whether all values of S and I must be merged into one, so resistance is only considered when isolates are R, not I. As this is the default behaviour of the
a logical to turn Verbose mode on and off (default is off). In Verbose mode, the function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.
column name of an antibiotic, please see section Antibiotics below
Please see Details for the list of publications used for this function.
CMI 2012 paper - function
factor with levels
Multi-drug-resistant (MDR) <
Extensively drug-resistant (XDR) <
TB guideline - function
mdro(..., guideline = "TB"):
factor with levels
German guideline - function
mdro(..., guideline = "MRGN"):
factor with levels
factor with levels
Positive, unconfirmed <
Positive. The value
"Positive, unconfirmed" means that, according to the guideline, it is not entirely sure if the isolate is multi-drug resistant and this should be confirmed with additional (e.g. molecular) tests
pct_required_classes argument, values above 1 will be divided by 100. This is to support both fractions (
3/4) and percentages (
Currently supported guidelines are (case-insensitive):
guideline = "CMI2012"
Magiorakos AP, Srinivasan A et al. "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance." Clinical Microbiology and Infection (2012) (link)
guideline = "EUCAST"
The European international guideline - EUCAST Expert Rules Version 3.1 "Intrinsic Resistance and Exceptional Phenotypes Tables" (link)
guideline = "TB"
The international guideline for multi-drug resistant tuberculosis - World Health Organization "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis" (link)
guideline = "MRGN"
The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6
guideline = "BRMO"
The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" (link)
Please suggest your own (country-specific) guidelines by letting us know: https://github.com/msberends/AMR/issues/new.
Note: Every test that involves the Enterobacteriaceae family, will internally be performed using its newly named order Enterobacterales, since the Enterobacteriaceae family has been taxonomically reclassified by Adeolu et al. in 2016. Before that, Enterobacteriaceae was the only family under the Enterobacteriales (with an i) order. All species under the old Enterobacteriaceae family are still under the new Enterobacterales (without an i) order, but divided into multiple families. The way tests are performed now by this
mdro() function makes sure that results from before 2016 and after 2016 are identical.
The lifecycle of this function is maturing. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome to suggest changes at our repository or write us an email (see section 'Contact Us').
To define antibiotics column names, leave as it is to determine it automatically with
guess_ab_col() or input a text (case-insensitive), or use
NULL to skip a column (e.g.
TIC = NULL to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.
AMK: amikacin (J01GB06), AMX: amoxicillin (J01CA04), AMC: amoxicillin/clavulanic acid (J01CR02), AMP: ampicillin (J01CA01), SAM: ampicillin/sulbactam (J01CR01), AZM: azithromycin (J01FA10), AZL: azlocillin (J01CA09), ATM: aztreonam (J01DF01), CAP: capreomycin (J04AB30), RID: cefaloridine (J01DB02), CZO: cefazolin (J01DB04), FEP: cefepime (J01DE01), CTX: cefotaxime (J01DD01), CTT: cefotetan (J01DC05), FOX: cefoxitin (J01DC01), CPT: ceftaroline (J01DI02), CAZ: ceftazidime (J01DD02), CRO: ceftriaxone (J01DD04), CXM: cefuroxime (J01DC02), CED: cephradine (J01DB09), CHL: chloramphenicol (J01BA01), CIP: ciprofloxacin (J01MA02), CLR: clarithromycin (J01FA09), CLI: clindamycin (J01FF01), COL: colistin (J01XB01), DAP: daptomycin (J01XX09), DOR: doripenem (J01DH04), DOX: doxycycline (J01AA02), ETP: ertapenem (J01DH03), ERY: erythromycin (J01FA01), ETH: ethambutol (J04AK02), FLC: flucloxacillin (J01CF05), FOS: fosfomycin (J01XX01), FUS: fusidic acid (J01XC01), GAT: gatifloxacin (J01MA16), GEN: gentamicin (J01GB03), GEH: gentamicin-high (no ATC code), IPM: imipenem (J01DH51), INH: isoniazid (J04AC01), KAN: kanamycin (J01GB04), LVX: levofloxacin (J01MA12), LIN: lincomycin (J01FF02), LNZ: linezolid (J01XX08), MEM: meropenem (J01DH02), MTR: metronidazole (J01XD01), MEZ: mezlocillin (J01CA10), MNO: minocycline (J01AA08), MFX: moxifloxacin (J01MA14), NAL: nalidixic acid (J01MB02), NEO: neomycin (J01GB05), NET: netilmicin (J01GB07), NIT: nitrofurantoin (J01XE01), NOR: norfloxacin (J01MA06), NOV: novobiocin (QJ01XX95), OFX: ofloxacin (J01MA01), OXA: oxacillin (J01CF04), PEN: penicillin G (J01CE01), PIP: piperacillin (J01CA12), TZP: piperacillin/tazobactam (J01CR05), PLB: polymyxin B (J01XB02), PRI: pristinamycin (J01FG01), PZA: pyrazinamide (J04AK01), QDA: quinupristin/dalfopristin (J01FG02), RIB: rifabutin (J04AB04), RIF: rifampicin (J04AB02), RFP: rifapentine (J04AB05), RXT: roxithromycin (J01FA06), SIS: sisomicin (J01GB08), STH: streptomycin-high (no ATC code), TEC: teicoplanin (J01XA02), TLV: telavancin (J01XA03), TCY: tetracycline (J01AA07), TIC: ticarcillin (J01CA13), TCC: ticarcillin/clavulanic acid (J01CR03), TGC: tigecycline (J01AA12), TOB: tobramycin (J01GB01), TMP: trimethoprim (J01EA01), SXT: trimethoprim/sulfamethoxazole (J01EE01), VAN: vancomycin (J01XA01).
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (http://www.eucast.org/newsiandr/).
R = Resistant
A microorganism is categorised as Resistant when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
S = Susceptible
A microorganism is categorised as Susceptible, standard dosing regimen, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
I = Increased exposure, but still susceptible
A microorganism is categorised as Susceptible, Increased exposure when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
This AMR package honours this new insight. Use
susceptibility() (equal to
proportion_SI()) to determine antimicrobial susceptibility and
count_susceptible() (equal to
count_SI()) to count susceptible isolates.
On our website https://msberends.github.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.