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# `AMR` # `AMR`
### An [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR). ### An [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and work with antibiotic properties by using evidence-based methods.
[![logo_rug](man/figures/logo_rug.png)](https://www.rug.nl)[![logo_umcg](man/figures/logo_umcg.png)](https://www.umcg.nl) This R package was created for academic research by PhD students of the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl) and the Medical Microbiology & Infection Prevention (MMBI) department of the [University Medical Center Groningen (UMCG)](https://www.umcg.nl).
This R package was created for academic research by PhD students of the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl) and the Medical Microbiology & Infection Prevention (MMBI) department of the [University Medical Center Groningen (UMCG)](https://www.umcg.nl). See [Authors](#authors). :arrow_forward: Download it with `install.packages("AMR")` or see below for other possibilities.
## Authors
- [Berends MS](https://github.com/msberends)<sup>1,2</sup>, PhD Student
- [Luz CF](https://github.com/ceefluz)<sup>1</sup>, PhD Student
- [Hassing EEA](https://github.com/erwinhassing)<sup>2</sup>, Data Analyst (contributor)
<sup>1</sup> Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
<sup>2</sup> Certe Medical Diagnostics & Advice, Groningen, the Netherlands
<a href="https://www.rug.nl"><img src="man/figures/logo_rug.png" height="60px"></a>
<a href="https://www.umcg.nl"><img src="man/figures/logo_umcg.png" height="60px"></a>
<a href="https://www.certe.nl"><img src="man/figures/logo_certe.png" height="60px"></a>
<a href="http://www.eurhealth-1health.eu"><img src="man/figures/logo_eh1h.png" height="60px"></a>
<a href="http://www.eurhealth-1health.eu"><img src="man/figures/logo_interreg.png" height="60px"></a>
## Why this package? ## Why this package?
This R package contains functions to make **microbiological, epidemiological data analysis easier**. It allows the use of some new classes to work with MIC values and antimicrobial interpretations (i.e. values S, I and R). This R package contains functions to make **microbiological, epidemiological data analysis easier**. It allows the use of some new classes to work with MIC values and antimicrobial interpretations (i.e. values S, I and R).
With `AMR` you can also: With `AMR` you can also:
* Create frequency tables with the `freq` function
* Conduct AMR analysis with the `rsi` function, that can also be used with the `dplyr` package (e.g. in conjunction with `summarise`) to calculate the resistance percentages (and even co-resistance) of different antibiotic columns of a table * Conduct AMR analysis with the `rsi` function, that can also be used with the `dplyr` package (e.g. in conjunction with `summarise`) to calculate the resistance percentages (and even co-resistance) of different antibiotic columns of a table
* Predict antimicrobial resistance for the nextcoming years with the `rsi_predict` function * Predict antimicrobial resistance for the nextcoming years with the `rsi_predict` function
* Apply [EUCAST rules to isolates](http://www.eucast.org/expert_rules_and_intrinsic_resistance/) with the `EUCAST_rules` function * Apply [EUCAST rules to isolates](http://www.eucast.org/expert_rules_and_intrinsic_resistance/) with the `EUCAST_rules` function
* Identify first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute) with the `first_isolate` function * Identify first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute) with the `first_isolate` function
* Translate antibiotic codes from the lab (like `"AMOX"`) or the [WHO](https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no) (like `"J01CA04"`) to trivial names (like `"amoxicillin"`) with the `abname` function * Get antimicrobial ATC properties from the WHO Collaborating Centre for Drug Statistics Methodology ([WHOCC](https://www.whocc.no/atc_ddd_methodology/who_collaborating_centre/)), to be able to:
* Translate antibiotic codes (like *AMOX*), official names (like *amoxicillin*) and even trade names (like *Amoxil* or *Trimox*) to an [ATC code](https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no) (like *J01CA04*) and vice versa with the `abname` function
* Get the latest antibiotic properties like hierarchic groups and [defined daily dose](https://en.wikipedia.org/wiki/Defined_daily_dose) (DDD) with units and administration form from the WHOCC website with the `atc_property` function
* Create frequency tables with the `freq` function
With the `MDRO` function (abbreviation of Multi Drug Resistant Organisms), you can check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently guidelines for Germany and the Netherlands are supported. Please suggest addition of your own country here: [https://github.com/msberends/AMR/issues/new](https://github.com/msberends/AMR/issues/new?title=New%20guideline%20for%20MDRO&body=%3C--%20Please%20add%20your%20country%20code,%20guideline%20name,%20version%20and%20source%20below%20and%20remove%20this%20line--%3E). With the `MDRO` function (abbreviation of Multi Drug Resistant Organisms), you can check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently guidelines for Germany and the Netherlands are supported. Please suggest addition of your own country here: [https://github.com/msberends/AMR/issues/new](https://github.com/msberends/AMR/issues/new?title=New%20guideline%20for%20MDRO&body=%3C--%20Please%20add%20your%20country%20code,%20guideline%20name,%20version%20and%20source%20below%20and%20remove%20this%20line--%3E).
@ -277,19 +295,6 @@ antibiotics # A tibble: 420 x 18
microorganisms # A tibble: 2,453 x 12 microorganisms # A tibble: 2,453 x 12
``` ```
## Authors
- [Berends MS](https://github.com/msberends)<sup>1,2</sup>, PhD Student
- [Luz CF](https://github.com/ceefluz)<sup>1</sup>, PhD Student
- [Hassing EEA](https://github.com/erwinhassing)<sup>2</sup>, Data Analyst (contributor)
<sup>1</sup> Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
<sup>2</sup> Certe Medical Diagnostics & Advice, Groningen, the Netherlands
[![logo_umcg](man/figures/logo_umcg.png)](https://www.umcg.nl)[![logo_certe](man/figures/logo_certe.png)](https://www.certe.nl)[![logo_eh1h](man/figures/logo_eh1h.png)](http://www.eurhealth-1health.eu)[![logo_interreg](man/figures/logo_interreg.png)](http://www.eurhealth-1health.eu)
## Copyright ## Copyright
[![License](https://img.shields.io/github/license/msberends/AMR.svg?colorB=3679BC)](https://github.com/msberends/AMR/blob/master/LICENSE) [![License](https://img.shields.io/github/license/msberends/AMR.svg?colorB=3679BC)](https://github.com/msberends/AMR/blob/master/LICENSE)