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export first_isolate

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dr. M.S. (Matthijs) Berends
2018-02-26 12:15:52 +01:00
parent be51a95448
commit d36a391747
6 changed files with 14 additions and 13 deletions
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2
man/ablist.Rd
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@ -14,7 +14,7 @@
\item{\code{trivial}}{Trivial name in Dutch, like \code{"Amoxicilline/clavulaanzuur"}}
\item{\code{oral_ddd}}{Daily Defined Dose (DDD) according to the WHO, oral treatment}
\item{\code{oral_units}}{Units of \code{ddd_units}}
\item{\code{iv_ddd}}{Daily Defined Dose (DDD) according to the WHO, bij parenteral treatment}
\item{\code{iv_ddd}}{Daily Defined Dose (DDD) according to the WHO, parenteral treatment}
\item{\code{iv_units}}{Units of \code{iv_ddd}}
\item{\code{atc_group1}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
\item{\code{atc_group2}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}

2
man/bactlist.Rd
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@ -13,7 +13,7 @@
\item{\code{species}}{Species name of microorganism, like \code{"coli"}}
\item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
\item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
\item{\code{type}}{Type of microorganism, like \code{"Bacterie"} en \code{"Schimmel/gist"} (these are Dutch)}
\item{\code{type}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
\item{\code{gramstain}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
\item{\code{aerobic}}{Type aerobe/anaerobe of bacteria}
}}

12
man/key_antibiotics.Rd
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@ -4,12 +4,12 @@
\alias{key_antibiotics}
\title{Key antibiotics based on bacteria ID}
\usage{
key_antibiotics(tbl, col_bactcode = "bacteriecode", info = TRUE,
amcl = "amcl", amox = "amox", cfot = "cfot", cfta = "cfta",
cftr = "cftr", cfur = "cfur", cipr = "cipr", clar = "clar",
clin = "clin", clox = "clox", doxy = "doxy", gent = "gent",
line = "line", mero = "mero", peni = "peni", pita = "pita",
rifa = "rifa", teic = "teic", trsu = "trsu", vanc = "vanc")
key_antibiotics(tbl, col_bactcode = "bactid", info = TRUE, amcl = "amcl",
amox = "amox", cfot = "cfot", cfta = "cfta", cftr = "cftr",
cfur = "cfur", cipr = "cipr", clar = "clar", clin = "clin",
clox = "clox", doxy = "doxy", gent = "gent", line = "line",
mero = "mero", peni = "peni", pita = "pita", rifa = "rifa",
teic = "teic", trsu = "trsu", vanc = "vanc")
}
\arguments{
\item{tbl}{table with antibiotics coloms, like \code{amox} and \code{amcl}.}

7
man/rsi_predict.Rd
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@ -4,7 +4,7 @@
\alias{rsi_predict}
\title{Predict antimicrobial resistance}
\usage{
rsi_predict(tbl, col_ab, col_date = "ontvangstdatum",
rsi_predict(tbl, col_ab, col_date,
year_max = as.integer(format(as.Date(Sys.Date()), "\%Y")) + 15,
year_every = 1, model = "binomial", I_as_R = TRUE,
preserve_measurements = TRUE, info = TRUE)
@ -37,19 +37,20 @@ Create a prediction model to predict antimicrobial resistance for the next years
\examples{
\dontrun{
# use it directly:
rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], "amcl")
rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], col_ab = "amcl", coldate = "date")
# or with dplyr so you can actually read it:
library(dplyr)
tbl \%>\%
filter(first_isolate == TRUE,
genus == "Haemophilus") \%>\%
rsi_predict("amcl")
rsi_predict(col_ab = "amcl", coldate = "date")
tbl \%>\%
filter(first_isolate_weighted == TRUE,
genus == "Haemophilus") \%>\%
rsi_predict(col_ab = "amcl",
coldate = "date",
year_max = 2050,
year_every = 5)