ab_from_text
Retrieve Antimicrobial Drug Names and Doses from Clinical Text
Description
Use this function on e.g. clinical texts from health care records. It returns a list with all antimicrobial drugs, doses and forms of administration found in the texts.
Usage
ab_from_text(
text,
type = c("drug", "dose", "administration"),
collapse = NULL,
translate_ab = FALSE,
thorough_search = NULL,
...
)Arguments
text |
text to analyse |
type |
type of property to search for, either |
collapse |
character to pass on to |
translate_ab |
if |
thorough_search |
logical to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to |
... |
arguments passed on to |
Details
This function is also internally used by as.ab(), although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the as.ab() function may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
Argument type
At default, the function will search for antimicrobial drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses as.ab() internally, it will correct for misspelling.
With type = "dose" (or similar, like "dosing", "doses"), all text elements will be searched for numeric values that are higher than 100 and do not resemble years. The output will be numeric. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see Examples.
With type = "administration" (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see Examples.
Argument collapse
Without using collapse, this function will return a list. This can be convenient to use e.g. inside a mutate()):df %>% mutate(abx = ab_from_text(clinical_text))
The returned AB codes can be transformed to official names, groups, etc. with all ab_* functions such as ab_name() and ab_group(), or by using the translate_ab argument.
With using collapse, this function will return a character:df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))
Value
Stable Lifecycle
The lifecycle of this function is stable. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
Read more on Our Website!
On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR data analysis, the complete documentation of all functions and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!
Examples
# mind the bad spelling of amoxicillin in this line,
# straight from a true health care record:
ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds")
ab_from_text("500 mg amoxi po and 400mg cipro iv")
ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "dose")
ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "admin")
ab_from_text("500 mg amoxi po and 400mg cipro iv", collapse = ", ")
# if you want to know which antibiotic groups were administered, do e.g.:
abx <- ab_from_text("500 mg amoxi po and 400mg cipro iv")
ab_group(abx[[1]])
if (require("dplyr")) {
tibble(clinical_text = c("given 400mg cipro and 500 mg amox",
"started on doxy iv today")) %>%
mutate(abx_codes = ab_from_text(clinical_text),
abx_doses = ab_from_text(clinical_text, type = "doses"),
abx_admin = ab_from_text(clinical_text, type = "admin"),
abx_coll = ab_from_text(clinical_text, collapse = "|"),
abx_coll_names = ab_from_text(clinical_text,
collapse = "|",
translate_ab = "name"),
abx_coll_doses = ab_from_text(clinical_text,
type = "doses",
collapse = "|"),
abx_coll_admin = ab_from_text(clinical_text,
type = "admin",
collapse = "|"))
}