Create a visual table from a summariseClinicalRecord() output
Source:R/tableClinicalRecords.R
tableClinicalRecords.RdCreate a visual table from a summariseClinicalRecord() output
Usage
tableClinicalRecords(
result,
header = "cdm_name",
hide = omopgenerics::settingsColumns(result),
groupColumn = c("omop_table", omopgenerics::strataColumns(result)),
type = NULL,
style = NULL
)Arguments
- result
A summarised_result object (output of
summariseClinicalRecords()).- header
A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header.
- hide
Columns to drop from the output table.
- groupColumn
Columns to use as group labels, to see options use visOmopResults::tableColumns(result).
- type
Character string specifying the desired output table format. See
visOmopResults::tableType()for supported table types. Iftype = NULL, global options (set viavisOmopResults::setGlobalTableOptions()) will be used if available; otherwise, a default 'gt' table is created.- style
Defines the visual formatting of the table. This argument can be provided in one of the following ways:
Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See
visOmopResults::tableStyle()for available options.YAML file path: Provide the path to an existing .yml file defining a new style.
List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type.
If
style = NULL, the function will use global options (seevisOmopResults::setGlobalTableOptions()) or a _brand.yml file (if found); otherwise, the default style is applied.
Examples
# \donttest{
library(OmopSketch)
library(omock)
cdm <- mockCdmFromDataset(datasetName = "GiBleed", source = "duckdb")
#> ℹ Loading bundled GiBleed tables from package data.
#> ℹ Adding drug_strength table.
#> ℹ Creating local <cdm_reference> object.
#> ℹ Inserting <cdm_reference> into duckdb.
summarisedResult <- summariseClinicalRecords(
cdm = cdm,
omopTableName = c("condition_occurrence", "drug_exposure"),
recordsPerPerson = c("mean", "sd"),
inObservation = TRUE,
standardConcept = TRUE,
sourceVocabulary = TRUE,
domainId = TRUE,
typeConcept = TRUE
)
#> Warning: The `inObservation` argument of `summariseClinicalRecords()` is deprecated as
#> of OmopSketch 1.0.0.
#> ℹ Please use the `quality` argument instead.
#> Warning: The `standardConcept` argument of `summariseClinicalRecords()` is deprecated as
#> of OmopSketch 1.0.0.
#> ℹ Please use the `conceptSummary` argument instead.
#> Warning: The `sourceVocabulary` argument of `summariseClinicalRecords()` is deprecated
#> as of OmopSketch 1.0.0.
#> ℹ Please use the `conceptSummary` argument instead.
#> Warning: The `domainId` argument of `summariseClinicalRecords()` is deprecated as of
#> OmopSketch 1.0.0.
#> ℹ Please use the `conceptSummary` argument instead.
#> Warning: The `typeConcept` argument of `summariseClinicalRecords()` is deprecated as of
#> OmopSketch 1.0.0.
#> ℹ Please use the `conceptSummary` argument instead.
#> ℹ Adding variables of interest to condition_occurrence.
#> ℹ Summarising records per person in condition_occurrence.
#> ℹ The following estimates will be calculated:
#> • duration: mean, sd
#> → Start summary of data, at 2026-05-19 14:11:14.962447
#> ✔ Summary finished, at 2026-05-19 14:11:15.110618
#> ℹ Summarising subjects not in person table in condition_occurrence.
#> ℹ Summarising records in observation in condition_occurrence.
#> ℹ Summarising records with start before birth date in condition_occurrence.
#> ℹ Summarising records with end date before start date in condition_occurrence.
#> ℹ Summarising domains in condition_occurrence.
#> ℹ Summarising standard concepts in condition_occurrence.
#> ℹ Summarising source vocabularies in condition_occurrence.
#> ℹ Summarising concept types in condition_occurrence.
#> ℹ Summarising missing data in condition_occurrence.
#> ℹ Adding variables of interest to drug_exposure.
#> ℹ Summarising records per person in drug_exposure.
#> ℹ The following estimates will be calculated:
#> • duration: mean, sd
#> → Start summary of data, at 2026-05-19 14:11:19.078509
#> ✔ Summary finished, at 2026-05-19 14:11:19.232177
#> ℹ Summarising subjects not in person table in drug_exposure.
#> ℹ Summarising records in observation in drug_exposure.
#> ℹ Summarising records with start before birth date in drug_exposure.
#> ℹ Summarising records with end date before start date in drug_exposure.
#> ℹ Summarising domains in drug_exposure.
#> ℹ Summarising standard concepts in drug_exposure.
#> ℹ Summarising source vocabularies in drug_exposure.
#> ℹ Summarising concept types in drug_exposure.
#> ℹ Summarising concept class in drug_exposure.
#> ℹ Summarising missing data in drug_exposure.
summarisedResult |>
suppress(minCellCount = 5) |>
tableClinicalRecords()
Summary of condition_occurrence, drug_exposure tables
condition_occurrence
drug_exposure
cdmDisconnect(cdm = cdm)
# }