View source: R/extract_test_recent.R
extract_test_recent | R Documentation |
Query an RSQLite database and return a data frame containing the most recent test result that meets specified criteria.
extract_test_recent(
cohort,
varname = NULL,
codelist = NULL,
codelist_vector = NULL,
indexdt,
t = NULL,
t_varname = TRUE,
time_prev = 365.25 * 5,
time_post = 0,
lower_bound = -Inf,
upper_bound = Inf,
db_open = NULL,
db = NULL,
db_filepath = NULL,
out_save_disk = FALSE,
out_subdir = NULL,
out_filepath = NULL,
return_output = FALSE
)
cohort |
Cohort of individuals to extract the 'history of' variable for. |
varname |
Name of variable in the outputted data frame. |
codelist |
Name of codelist (stored on hard disk) to query the database with. |
codelist_vector |
Vector of codes to query the database with. This takes precedent over |
indexdt |
Name of variable in |
t |
Number of days after |
t_varname |
Whether to alter the variable name in the outputted data frame to reflect |
time_prev |
Number of days prior to index date to look for codes. |
time_post |
Number of days after index date to look for codes. |
lower_bound |
Lower bound for returned values. |
upper_bound |
Upper bound for returned values. |
db_open |
An open SQLite database connection created using RSQLite::dbConnect, to be queried. |
db |
Name of SQLITE database on hard disk (stored in "data/sql/"), to be queried. |
db_filepath |
Full filepath to SQLITE database on hard disk, to be queried. |
out_save_disk |
If |
out_subdir |
Sub-directory of "data/extraction/" to save outputted data frame into. |
out_filepath |
Full filepath and filename to save outputted data frame into. |
return_output |
If |
Specifying db
requires a specific underlying directory structure. The SQLite database must be stored in "data/sql/" relative to the working directory.
If the SQLite database is accessed through db
, the connection will be opened and then closed after the query is complete. The same is true if
the database is accessed through db_filepath
. A connection to the SQLite database can also be opened manually using RSQLite::dbConnect
, and then
using the object as input to parameter db_open
. After wards, the connection must be closed manually using RSQLite::dbDisconnect
. If db_open
is specified, this will take precedence over db
or db_filepath
.
If out_save_disk = TRUE
, the data frame will automatically be written to an .rds file in a subdirectory "data/extraction/" of the working directory.
This directory structure must be created in advance. out_subdir
can be used to specify subdirectories within "data/extraction/". These options will use a default naming convetion. This can be overwritten
using out_filepath
to manually specify the location on the hard disk to save. Alternatively, return the data frame into the R workspace using return_output = TRUE
and then save onto the hard disk manually.
Codelists can be specified in two ways. The first is to read the codelist into R as a character vector and then specify through the argument
codelist_vector
. Codelists stored on the hard disk can also be referred to from the codelist
argument, but require a specific underlying directory structure.
The codelist on the hard disk must be stored in a directory called "codelists/analysis/" relative to the working directory. The codelist must be a .csv file, and
contain a column "medcodeid", "prodcodeid" or "ICD10" depending on the input for argument tab
. The input to argument codelist
should just be a character string of
the name of the files (excluding the suffix '.csv'). The codelist_vector
option will take precedence over the codelist
argument if both are specified.
Currently only returns most recent test result. This will be updated to return more than one most recent test result if specified.
A data frame containing most recent test result that meets required criteria.
## Connect
aurum_extract <- connect_database(file.path(tempdir(), "temp.sqlite"))
## Create SQLite database using cprd_extract
cprd_extract(aurum_extract,
filepath = system.file("aurum_data", package = "rcprd"),
filetype = "observation", use_set = FALSE)
## Define cohort and add index date
pat<-extract_cohort(system.file("aurum_data", package = "rcprd"))
pat$indexdt <- as.Date("01/01/1955", format = "%d/%m/%Y")
## Extract most recent test value prior to index date
extract_test_data(pat,
codelist_vector = "187341000000114",
indexdt = "fup_start",
db_open = aurum_extract,
time_prev = Inf,
return_output = TRUE)
## clean up
RSQLite::dbDisconnect(aurum_extract)
unlink(file.path(tempdir(), "temp.sqlite"))
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