From ae7aeef853657ea701e877d6ade3fb438c8ad87d Mon Sep 17 00:00:00 2001 From: cecicampanile Date: Fri, 20 Dec 2024 15:46:07 +0000 Subject: [PATCH 1/4] name changed to summariseConceptIdCounts --- NAMESPACE | 1 + R/summariseAllConceptCounts.R | 104 ++------------ R/summariseConceptIdCounts.R | 133 ++++++++++++++++++ man/summariseConceptIdCounts.Rd | 60 ++++++++ .../testthat/test-summariseAllConceptCounts.R | 62 ++++---- 5 files changed, 240 insertions(+), 120 deletions(-) create mode 100644 R/summariseConceptIdCounts.R create mode 100644 man/summariseConceptIdCounts.Rd diff --git a/NAMESPACE b/NAMESPACE index a3fa787..15fa8e5 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -12,6 +12,7 @@ export(settings) export(summariseAllConceptCounts) export(summariseClinicalRecords) export(summariseConceptCounts) +export(summariseConceptIdCounts) export(summariseConceptSetCounts) export(summariseInObservation) export(summariseMissingData) diff --git a/R/summariseAllConceptCounts.R b/R/summariseAllConceptCounts.R index bd3befc..3f79dd1 100644 --- a/R/summariseAllConceptCounts.R +++ b/R/summariseAllConceptCounts.R @@ -41,93 +41,19 @@ summariseAllConceptCounts <- function(cdm, ageGroup = NULL, sample = NULL, dateRange = NULL) { - # initial checks - cdm <- omopgenerics::validateCdmArgument(cdm) - checkCountBy(countBy) - omopgenerics::assertLogical(year, length = 1) - omopgenerics::assertLogical(sex, length = 1) - omopgenerics::assertChoice(omopTableName, choices = omopgenerics::omopTables(), unique = TRUE) - ageGroup <- omopgenerics::validateAgeGroupArgument(ageGroup) - dateRange <- validateStudyPeriod(cdm, dateRange) - omopgenerics::assertNumeric(sample, integerish = TRUE, min = 1, null = TRUE, length = 1) - - # settings for the created results - set <- createSettings(result_type = "summarise_all_concept_counts", study_period = dateRange) - - # get strata - strata <- omopgenerics::combineStrata(c(strataCols(sex = sex, ageGroup = ageGroup), "year"[year])) - concepts <- c("concept_id", "concept_name") - stratax <- c(list(concepts), purrr::map(strata, \(x) c(concepts, x))) - - # how to count - counts <- c("records", "person_id")[c("record", "person") %in% countBy] - - # summarise counts - resultTables <- purrr::map(omopTableName, \(table) { - # initial table - omopTable <- dplyr::ungroup(cdm[[table]]) - conceptId <- omopgenerics::omopColumns(table = table, field = "standard_concept") - if (is.na(conceptId)) { - cli::cli_warn(c("!" = "No standard concept identified for {table}.")) - return(NULL) - } - - prefix <- omopgenerics::tmpPrefix() - - # restrict study period - omopTable <- restrictStudyPeriod(omopTable, dateRange) - if (is.null(omopTable)) return(NULL) - - # sample table - omopTable <- omopTable |> - sampleOmopTable(sample = sample, name = omopgenerics::uniqueTableName(prefix)) - - result <- omopTable |> - # add concept names - dplyr::rename(concept_id = dplyr::all_of(conceptId)) |> - dplyr::left_join( - cdm$concept |> - dplyr::select("concept_id", "concept_name"), - by = "concept_id" - ) |> - # add demographics and year - addStratifications( - indexDate = omopgenerics::omopColumns(table = table, field = "start_date"), - sex = sex, - ageGroup = ageGroup, - interval = dplyr::if_else(year, "years", "overall"), - intervalName = "year", - name = omopgenerics::uniqueTableName(prefix) - ) |> - # summarise results - summariseCountsInternal(stratax, counts) |> - dplyr::mutate(omop_table = .env$table) - - omopgenerics::dropSourceTable(cdm = cdm, name = dplyr::starts_with(prefix)) - - return(result) - }) |> - purrr::compact() - - if (length(resultTables) == 0) { - return(omopgenerics::emptySummarisedResult(settings = set)) - } - - resultTables |> - dplyr::bind_rows() |> - dplyr::mutate( - result_id = 1L, - cdm_name = omopgenerics::cdmName(cdm) - ) |> - omopgenerics::uniteGroup(cols = "omop_table") |> - omopgenerics::uniteStrata(cols = unique(unlist(strata)) %||% character()) |> - omopgenerics::uniteAdditional() |> - dplyr::mutate( - estimate_value = as.character(.data$estimate_value), - estimate_type = "integer", - variable_level = as.character(.data$concept_id) - ) |> - dplyr::rename("variable_name" = "concept_name") |> - dplyr::select(!"concept_id") |> - omopgenerics::newSummarisedResult(settings = set) + lifecycle::deprecate_warn( + when = "0.2.0", + what = "summariseAllConceptCounts()", + with = "summariseConceptIdCounts()" + ) + summariseConceptIdCounts( + cdm = cdm, + omopTableName = omopTableName, + countBy = countBy, + year = year, + sex = sex, + ageGroup = ageGroup, + sample = sample, + dateRange = dateRange + ) } diff --git a/R/summariseConceptIdCounts.R b/R/summariseConceptIdCounts.R new file mode 100644 index 0000000..20af304 --- /dev/null +++ b/R/summariseConceptIdCounts.R @@ -0,0 +1,133 @@ + +#' Summarise concept use in patient-level data +#' +#' @param cdm A cdm object +#' @param omopTableName A character vector of the names of the tables to +#' summarise in the cdm object. +#' @param countBy Either "record" for record-level counts or "person" for +#' person-level counts +#' @param year TRUE or FALSE. If TRUE code use will be summarised by year. +#' @param sex TRUE or FALSE. If TRUE code use will be summarised by sex. +#' @param ageGroup A list of ageGroup vectors of length two. Code use will be +#' thus summarised by age groups. +#' @param sample An integer to sample the tables to only that number of records. +#' If NULL no sample is done. +#' @param dateRange A list containing the minimum and the maximum dates +#' defining the time range within which the analysis is performed. +#' +#' @return A summarised_result object with results overall and, if specified, by +#' strata. +#' +#' @export +#' +#' @examples +#' \donttest{ +#' library(OmopSketch) +#' library(CDMConnector) +#' library(duckdb) +#' +#' requireEunomia() +#' con <- dbConnect(duckdb(), eunomiaDir()) +#' cdm <- cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main") +#' +#' summariseConceptIdCounts(cdm, "condition_occurrence") +#' } +#' +summariseConceptIdCounts <- function(cdm, + omopTableName, + countBy = "record", + year = FALSE, + sex = FALSE, + ageGroup = NULL, + sample = NULL, + dateRange = NULL) { + # initial checks + cdm <- omopgenerics::validateCdmArgument(cdm) + checkCountBy(countBy) + omopgenerics::assertLogical(year, length = 1) + omopgenerics::assertLogical(sex, length = 1) + omopgenerics::assertChoice(omopTableName, choices = omopgenerics::omopTables(), unique = TRUE) + ageGroup <- omopgenerics::validateAgeGroupArgument(ageGroup) + dateRange <- validateStudyPeriod(cdm, dateRange) + omopgenerics::assertNumeric(sample, integerish = TRUE, min = 1, null = TRUE, length = 1) + + # settings for the created results + set <- createSettings(result_type = "summarise_all_concept_counts", study_period = dateRange) + + # get strata + strata <- omopgenerics::combineStrata(c(strataCols(sex = sex, ageGroup = ageGroup), "year"[year])) + concepts <- c("concept_id", "concept_name") + stratax <- c(list(concepts), purrr::map(strata, \(x) c(concepts, x))) + + # how to count + counts <- c("records", "person_id")[c("record", "person") %in% countBy] + + # summarise counts + resultTables <- purrr::map(omopTableName, \(table) { + # initial table + omopTable <- dplyr::ungroup(cdm[[table]]) + conceptId <- omopgenerics::omopColumns(table = table, field = "standard_concept") + if (is.na(conceptId)) { + cli::cli_warn(c("!" = "No standard concept identified for {table}.")) + return(NULL) + } + + prefix <- omopgenerics::tmpPrefix() + + # restrict study period + omopTable <- restrictStudyPeriod(omopTable, dateRange) + if (is.null(omopTable)) return(NULL) + + # sample table + omopTable <- omopTable |> + sampleOmopTable(sample = sample, name = omopgenerics::uniqueTableName(prefix)) + + result <- omopTable |> + # add concept names + dplyr::rename(concept_id = dplyr::all_of(conceptId)) |> + dplyr::left_join( + cdm$concept |> + dplyr::select("concept_id", "concept_name"), + by = "concept_id" + ) |> + # add demographics and year + addStratifications( + indexDate = omopgenerics::omopColumns(table = table, field = "start_date"), + sex = sex, + ageGroup = ageGroup, + interval = dplyr::if_else(year, "years", "overall"), + intervalName = "year", + name = omopgenerics::uniqueTableName(prefix) + ) |> + # summarise results + summariseCountsInternal(stratax, counts) |> + dplyr::mutate(omop_table = .env$table) + + omopgenerics::dropSourceTable(cdm = cdm, name = dplyr::starts_with(prefix)) + + return(result) + }) |> + purrr::compact() + + if (length(resultTables) == 0) { + return(omopgenerics::emptySummarisedResult(settings = set)) + } + + resultTables |> + dplyr::bind_rows() |> + dplyr::mutate( + result_id = 1L, + cdm_name = omopgenerics::cdmName(cdm) + ) |> + omopgenerics::uniteGroup(cols = "omop_table") |> + omopgenerics::uniteStrata(cols = unique(unlist(strata)) %||% character()) |> + omopgenerics::uniteAdditional() |> + dplyr::mutate( + estimate_value = as.character(.data$estimate_value), + estimate_type = "integer", + variable_level = as.character(.data$concept_id) + ) |> + dplyr::rename("variable_name" = "concept_name") |> + dplyr::select(!"concept_id") |> + omopgenerics::newSummarisedResult(settings = set) +} diff --git a/man/summariseConceptIdCounts.Rd b/man/summariseConceptIdCounts.Rd new file mode 100644 index 0000000..7ba5006 --- /dev/null +++ b/man/summariseConceptIdCounts.Rd @@ -0,0 +1,60 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/summariseConceptIdCounts.R +\name{summariseConceptIdCounts} +\alias{summariseConceptIdCounts} +\title{Summarise concept use in patient-level data} +\usage{ +summariseConceptIdCounts( + cdm, + omopTableName, + countBy = "record", + year = FALSE, + sex = FALSE, + ageGroup = NULL, + sample = NULL, + dateRange = NULL +) +} +\arguments{ +\item{cdm}{A cdm object} + +\item{omopTableName}{A character vector of the names of the tables to +summarise in the cdm object.} + +\item{countBy}{Either "record" for record-level counts or "person" for +person-level counts} + +\item{year}{TRUE or FALSE. If TRUE code use will be summarised by year.} + +\item{sex}{TRUE or FALSE. If TRUE code use will be summarised by sex.} + +\item{ageGroup}{A list of ageGroup vectors of length two. Code use will be +thus summarised by age groups.} + +\item{sample}{An integer to sample the tables to only that number of records. +If NULL no sample is done.} + +\item{dateRange}{A list containing the minimum and the maximum dates +defining the time range within which the analysis is performed.} +} +\value{ +A summarised_result object with results overall and, if specified, by +strata. +} +\description{ +Summarise concept use in patient-level data +} +\examples{ +\donttest{ +library(OmopSketch) +library(CDMConnector) +library(duckdb) + +requireEunomia() +con <- dbConnect(duckdb(), eunomiaDir()) +cdm <- cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main") + +summariseAllConceptCounts(cdm, "condition_occurrence") +} + +} diff --git a/tests/testthat/test-summariseAllConceptCounts.R b/tests/testthat/test-summariseAllConceptCounts.R index 2c40730..d52f14d 100644 --- a/tests/testthat/test-summariseAllConceptCounts.R +++ b/tests/testthat/test-summariseAllConceptCounts.R @@ -3,42 +3,42 @@ test_that("summariseAllConceptCount works", { cdm <- cdmEunomia() - expect_true(inherits(summariseAllConceptCounts(cdm, "drug_exposure"), "summarised_result")) - expect_warning(summariseAllConceptCounts(cdm, "observation_period")) - expect_no_error(x <- summariseAllConceptCounts(cdm, "visit_occurrence")) - expect_no_error(summariseAllConceptCounts(cdm, "condition_occurrence", countBy = c("record", "person"))) - expect_no_error(summariseAllConceptCounts(cdm, "drug_exposure")) - expect_no_error(summariseAllConceptCounts(cdm, "procedure_occurrence", countBy = "person")) - expect_warning(summariseAllConceptCounts(cdm, "device_exposure")) - expect_no_error(y <- summariseAllConceptCounts(cdm, "measurement")) - expect_no_error(summariseAllConceptCounts(cdm, "observation", year = TRUE)) - expect_warning(p<-summariseAllConceptCounts(cdm, "death")) + expect_true(inherits(summariseConceptIdCounts(cdm, "drug_exposure"), "summarised_result")) + expect_warning(summariseConceptIdCounts(cdm, "observation_period")) + expect_no_error(x <- summariseConceptIdCounts(cdm, "visit_occurrence")) + expect_no_error(summariseConceptIdCounts(cdm, "condition_occurrence", countBy = c("record", "person"))) + expect_no_error(summariseConceptIdCounts(cdm, "drug_exposure")) + expect_no_error(summariseConceptIdCounts(cdm, "procedure_occurrence", countBy = "person")) + expect_warning(summariseConceptIdCounts(cdm, "device_exposure")) + expect_no_error(y <- summariseConceptIdCounts(cdm, "measurement")) + expect_no_error(summariseConceptIdCounts(cdm, "observation", year = TRUE)) + expect_warning(p<-summariseConceptIdCounts(cdm, "death")) - expect_no_error(all <- summariseAllConceptCounts(cdm, c("visit_occurrence", "measurement"))) + expect_no_error(all <- summariseConceptIdCounts(cdm, c("visit_occurrence", "measurement"))) expect_equal(all |> sortTibble(), x |> dplyr::bind_rows(y) |> sortTibble()) expect_equal( - summariseAllConceptCounts(cdm, "procedure_occurrence", countBy = "record") |> + summariseConceptIdCounts(cdm, "procedure_occurrence", countBy = "record") |> sortTibble(), - summariseAllConceptCounts(cdm, "procedure_occurrence") |> + summariseConceptIdCounts(cdm, "procedure_occurrence") |> sortTibble() ) - expect_warning(summariseAllConceptCounts(cdm, "observation_period")) - expect_error(summariseAllConceptCounts(cdm, omopTableName = "")) - expect_error(summariseAllConceptCounts(cdm, omopTableName = "visit_occurrence", countBy = "dd")) + expect_warning(summariseConceptIdCounts(cdm, "observation_period")) + expect_error(summariseConceptIdCounts(cdm, omopTableName = "")) + expect_error(summariseConceptIdCounts(cdm, omopTableName = "visit_occurrence", countBy = "dd")) expect_equal(settings(y)$result_type, settings(p)$result_type) - expect_true(summariseAllConceptCounts(cdm, "procedure_occurrence", sex = TRUE, ageGroup = list(c(0, 50), c(51, Inf))) |> + expect_true(summariseConceptIdCounts(cdm, "procedure_occurrence", sex = TRUE, ageGroup = list(c(0, 50), c(51, Inf))) |> dplyr::distinct(.data$strata_level) |> dplyr::tally() |> dplyr::pull() == 9) - expect_true(summariseAllConceptCounts(cdm, "procedure_occurrence", ageGroup = list(c(0, 50))) |> + expect_true(summariseConceptIdCounts(cdm, "procedure_occurrence", ageGroup = list(c(0, 50))) |> dplyr::distinct(.data$strata_level) |> dplyr::tally() |> dplyr::pull() == 3) - s <- summariseAllConceptCounts(cdm, "procedure_occurrence") |> + s <- summariseConceptIdCounts(cdm, "procedure_occurrence") |> sortTibble() - z <- summariseAllConceptCounts(cdm, "procedure_occurrence", sex = TRUE, year = TRUE, ageGroup = list(c(0, 50), c(51, Inf))) |> + z <- summariseConceptIdCounts(cdm, "procedure_occurrence", sex = TRUE, year = TRUE, ageGroup = list(c(0, 50), c(51, Inf))) |> sortTibble() x <- z |> @@ -69,16 +69,16 @@ test_that("dateRange argument works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() - expect_no_error(summariseAllConceptCounts(cdm, "condition_occurrence", dateRange = as.Date(c("2012-01-01", "2018-01-01")))) - expect_message(x<-summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2012-01-01", "2025-01-01")))) + expect_no_error(summariseConceptIdCounts(cdm, "condition_occurrence", dateRange = as.Date(c("2012-01-01", "2018-01-01")))) + expect_message(x<-summariseConceptIdCounts(cdm, "drug_exposure", dateRange = as.Date(c("2012-01-01", "2025-01-01")))) observationRange <- cdm$observation_period |> dplyr::summarise(minobs = min(.data$observation_period_start_date, na.rm = TRUE), maxobs = max(.data$observation_period_end_date, na.rm = TRUE)) - expect_no_error(y<- summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2012-01-01", observationRange |>dplyr::pull("maxobs"))))) + expect_no_error(y<- summariseConceptIdCounts(cdm, "drug_exposure", dateRange = as.Date(c("2012-01-01", observationRange |>dplyr::pull("maxobs"))))) expect_equal(x |> sortTibble(), y |> sortTibble(), ignore_attr = TRUE) expect_false(settings(x)$study_period_end==settings(y)$study_period_end) - expect_error(summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2015-01-01", "2014-01-01")))) - expect_warning(y<-summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2020-01-01", "2021-01-01")))) + expect_error(summariseConceptIdCounts(cdm, "drug_exposure", dateRange = as.Date(c("2015-01-01", "2014-01-01")))) + expect_warning(y<-summariseConceptIdCounts(cdm, "drug_exposure", dateRange = as.Date(c("2020-01-01", "2021-01-01")))) expect_equal(y, omopgenerics::emptySummarisedResult(), ignore_attr = TRUE) expect_equal(settings(y)$result_type, settings(x)$result_type) expect_equal(colnames(settings(y)), colnames(settings(x))) @@ -89,12 +89,12 @@ test_that("sample argument works", { # Load mock database ---- cdm <- cdmEunomia() - expect_no_error(x<-summariseAllConceptCounts(cdm,"drug_exposure", sample = 50)) - expect_no_error(y<-summariseAllConceptCounts(cdm,"drug_exposure")) + expect_no_error(x<-summariseConceptIdCounts(cdm,"drug_exposure", sample = 50)) + expect_no_error(y<-summariseConceptIdCounts(cdm,"drug_exposure")) n <- cdm$drug_exposure |> dplyr::tally()|> dplyr::pull(n) - expect_no_error(z<-summariseAllConceptCounts(cdm,"drug_exposure",sample = n)) + expect_no_error(z<-summariseConceptIdCounts(cdm,"drug_exposure",sample = n)) expect_equal(y |> sortTibble(), z |> sortTibble()) PatientProfiles::mockDisconnect(cdm = cdm) }) @@ -105,12 +105,12 @@ test_that("tableAllConceptCounts() works", { cdm <- cdmEunomia() # Check that works ---- - expect_no_error(x <- tableAllConceptCounts(summariseAllConceptCounts(cdm, "condition_occurrence"))) + expect_no_error(x <- tableAllConceptCounts(summariseConceptIdCounts(cdm, "condition_occurrence"))) expect_true(inherits(x,"gt_tbl")) - expect_no_error(y <- tableAllConceptCounts(summariseAllConceptCounts(cdm, c("drug_exposure", + expect_no_error(y <- tableAllConceptCounts(summariseConceptIdCounts(cdm, c("drug_exposure", "measurement")))) expect_true(inherits(y,"gt_tbl")) - expect_warning(t <- summariseAllConceptCounts(cdm, "death")) + expect_warning(t <- summariseConceptIdCounts(cdm, "death")) expect_warning(inherits(tableAllConceptCounts(t),"gt_tbl")) PatientProfiles::mockDisconnect(cdm = cdm) From 93e387dcf660bbbd958fd01c907d69c542cdaccb Mon Sep 17 00:00:00 2001 From: cecicampanile Date: Fri, 20 Dec 2024 17:07:05 +0000 Subject: [PATCH 2/4] updated namespace and pkgdown --- NAMESPACE | 3 +- R/summariseAllConceptCounts.R | 59 ------------------ ...ConceptCounts.R => tableConceptIdCounts.R} | 4 +- _pkgdown.yml | 4 +- man/summariseAllConceptCounts.Rd | 60 ------------------- man/summariseConceptIdCounts.Rd | 2 +- man/tableAllConceptCounts.Rd | 19 ------ man/tableConceptIdCounts.Rd | 19 ++++++ ...unts.R => test-summariseConceptIdCounts.R} | 10 ++-- 9 files changed, 30 insertions(+), 150 deletions(-) delete mode 100644 R/summariseAllConceptCounts.R rename R/{tableAllConceptCounts.R => tableConceptIdCounts.R} (92%) delete mode 100644 man/summariseAllConceptCounts.Rd delete mode 100644 man/tableAllConceptCounts.Rd create mode 100644 man/tableConceptIdCounts.Rd rename tests/testthat/{test-summariseAllConceptCounts.R => test-summariseConceptIdCounts.R} (93%) diff --git a/NAMESPACE b/NAMESPACE index 15fa8e5..ec11e71 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -9,7 +9,6 @@ export(plotInObservation) export(plotObservationPeriod) export(plotRecordCount) export(settings) -export(summariseAllConceptCounts) export(summariseClinicalRecords) export(summariseConceptCounts) export(summariseConceptIdCounts) @@ -20,8 +19,8 @@ export(summariseObservationPeriod) export(summariseOmopSnapshot) export(summariseRecordCount) export(suppress) -export(tableAllConceptCounts) export(tableClinicalRecords) +export(tableConceptIdCounts) export(tableMissingData) export(tableObservationPeriod) export(tableOmopSnapshot) diff --git a/R/summariseAllConceptCounts.R b/R/summariseAllConceptCounts.R deleted file mode 100644 index 3f79dd1..0000000 --- a/R/summariseAllConceptCounts.R +++ /dev/null @@ -1,59 +0,0 @@ - -#' Summarise concept use in patient-level data -#' -#' @param cdm A cdm object -#' @param omopTableName A character vector of the names of the tables to -#' summarise in the cdm object. -#' @param countBy Either "record" for record-level counts or "person" for -#' person-level counts -#' @param year TRUE or FALSE. If TRUE code use will be summarised by year. -#' @param sex TRUE or FALSE. If TRUE code use will be summarised by sex. -#' @param ageGroup A list of ageGroup vectors of length two. Code use will be -#' thus summarised by age groups. -#' @param sample An integer to sample the tables to only that number of records. -#' If NULL no sample is done. -#' @param dateRange A list containing the minimum and the maximum dates -#' defining the time range within which the analysis is performed. -#' -#' @return A summarised_result object with results overall and, if specified, by -#' strata. -#' -#' @export -#' -#' @examples -#' \donttest{ -#' library(OmopSketch) -#' library(CDMConnector) -#' library(duckdb) -#' -#' requireEunomia() -#' con <- dbConnect(duckdb(), eunomiaDir()) -#' cdm <- cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main") -#' -#' summariseAllConceptCounts(cdm, "condition_occurrence") -#' } -#' -summariseAllConceptCounts <- function(cdm, - omopTableName, - countBy = "record", - year = FALSE, - sex = FALSE, - ageGroup = NULL, - sample = NULL, - dateRange = NULL) { - lifecycle::deprecate_warn( - when = "0.2.0", - what = "summariseAllConceptCounts()", - with = "summariseConceptIdCounts()" - ) - summariseConceptIdCounts( - cdm = cdm, - omopTableName = omopTableName, - countBy = countBy, - year = year, - sex = sex, - ageGroup = ageGroup, - sample = sample, - dateRange = dateRange - ) -} diff --git a/R/tableAllConceptCounts.R b/R/tableConceptIdCounts.R similarity index 92% rename from R/tableAllConceptCounts.R rename to R/tableConceptIdCounts.R index c5bbafe..d915cd7 100644 --- a/R/tableAllConceptCounts.R +++ b/R/tableConceptIdCounts.R @@ -1,11 +1,11 @@ -#' Create a visual table from a summariseAllConceptCounts() result. +#' Create a visual table from a summariseConceptIdCounts() result. #' @param result A summarised_result object. #' @param type Type of formatting output table, either "gt" or "flextable". #' @return A gt or flextable object with the summarised data. #' @export #' #' -tableAllConceptCounts <- function(result, +tableConceptIdCounts <- function(result, type = "gt") { # initial checks rlang::check_installed("visOmopResults") diff --git a/_pkgdown.yml b/_pkgdown.yml index cd91ef0..9f76d9a 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -30,8 +30,8 @@ reference: - contents: - summariseConceptSetCounts - plotConceptSetCounts - - summariseAllConceptCounts - - tableAllConceptCounts + - summariseConceptIdCounts + - tableConceptIdCounts - subtitle: Mock Database desc: Create a mock database to test the OmopSketch package - contents: diff --git a/man/summariseAllConceptCounts.Rd b/man/summariseAllConceptCounts.Rd deleted file mode 100644 index b10f437..0000000 --- a/man/summariseAllConceptCounts.Rd +++ /dev/null @@ -1,60 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/summariseAllConceptCounts.R -\name{summariseAllConceptCounts} -\alias{summariseAllConceptCounts} -\title{Summarise concept use in patient-level data} -\usage{ -summariseAllConceptCounts( - cdm, - omopTableName, - countBy = "record", - year = FALSE, - sex = FALSE, - ageGroup = NULL, - sample = NULL, - dateRange = NULL -) -} -\arguments{ -\item{cdm}{A cdm object} - -\item{omopTableName}{A character vector of the names of the tables to -summarise in the cdm object.} - -\item{countBy}{Either "record" for record-level counts or "person" for -person-level counts} - -\item{year}{TRUE or FALSE. If TRUE code use will be summarised by year.} - -\item{sex}{TRUE or FALSE. If TRUE code use will be summarised by sex.} - -\item{ageGroup}{A list of ageGroup vectors of length two. Code use will be -thus summarised by age groups.} - -\item{sample}{An integer to sample the tables to only that number of records. -If NULL no sample is done.} - -\item{dateRange}{A list containing the minimum and the maximum dates -defining the time range within which the analysis is performed.} -} -\value{ -A summarised_result object with results overall and, if specified, by -strata. -} -\description{ -Summarise concept use in patient-level data -} -\examples{ -\donttest{ -library(OmopSketch) -library(CDMConnector) -library(duckdb) - -requireEunomia() -con <- dbConnect(duckdb(), eunomiaDir()) -cdm <- cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main") - -summariseAllConceptCounts(cdm, "condition_occurrence") -} - -} diff --git a/man/summariseConceptIdCounts.Rd b/man/summariseConceptIdCounts.Rd index 7ba5006..6a7d52f 100644 --- a/man/summariseConceptIdCounts.Rd +++ b/man/summariseConceptIdCounts.Rd @@ -54,7 +54,7 @@ requireEunomia() con <- dbConnect(duckdb(), eunomiaDir()) cdm <- cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main") -summariseAllConceptCounts(cdm, "condition_occurrence") +summariseConceptIdCounts(cdm, "condition_occurrence") } } diff --git a/man/tableAllConceptCounts.Rd b/man/tableAllConceptCounts.Rd deleted file mode 100644 index a3ce818..0000000 --- a/man/tableAllConceptCounts.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/tableAllConceptCounts.R -\name{tableAllConceptCounts} -\alias{tableAllConceptCounts} -\title{Create a visual table from a summariseAllConceptCounts() result.} -\usage{ -tableAllConceptCounts(result, type = "gt") -} -\arguments{ -\item{result}{A summarised_result object.} - -\item{type}{Type of formatting output table, either "gt" or "flextable".} -} -\value{ -A gt or flextable object with the summarised data. -} -\description{ -Create a visual table from a summariseAllConceptCounts() result. -} diff --git a/man/tableConceptIdCounts.Rd b/man/tableConceptIdCounts.Rd new file mode 100644 index 0000000..e221a45 --- /dev/null +++ b/man/tableConceptIdCounts.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/tableConceptIdCounts.R +\name{tableConceptIdCounts} +\alias{tableConceptIdCounts} +\title{Create a visual table from a summariseConceptIdCounts() result.} +\usage{ +tableConceptIdCounts(result, type = "gt") +} +\arguments{ +\item{result}{A summarised_result object.} + +\item{type}{Type of formatting output table, either "gt" or "flextable".} +} +\value{ +A gt or flextable object with the summarised data. +} +\description{ +Create a visual table from a summariseConceptIdCounts() result. +} diff --git a/tests/testthat/test-summariseAllConceptCounts.R b/tests/testthat/test-summariseConceptIdCounts.R similarity index 93% rename from tests/testthat/test-summariseAllConceptCounts.R rename to tests/testthat/test-summariseConceptIdCounts.R index d52f14d..5bcbb3b 100644 --- a/tests/testthat/test-summariseAllConceptCounts.R +++ b/tests/testthat/test-summariseConceptIdCounts.R @@ -1,4 +1,4 @@ -test_that("summariseAllConceptCount works", { +test_that("summariseConceptIdCount works", { skip_on_cran() cdm <- cdmEunomia() @@ -99,19 +99,19 @@ test_that("sample argument works", { PatientProfiles::mockDisconnect(cdm = cdm) }) -test_that("tableAllConceptCounts() works", { +test_that("tableConceptIdCounts() works", { skip_on_cran() # Load mock database ---- cdm <- cdmEunomia() # Check that works ---- - expect_no_error(x <- tableAllConceptCounts(summariseConceptIdCounts(cdm, "condition_occurrence"))) + expect_no_error(x <- tableConceptIdCounts(summariseConceptIdCounts(cdm, "condition_occurrence"))) expect_true(inherits(x,"gt_tbl")) - expect_no_error(y <- tableAllConceptCounts(summariseConceptIdCounts(cdm, c("drug_exposure", + expect_no_error(y <- tableConceptIdCounts(summariseConceptIdCounts(cdm, c("drug_exposure", "measurement")))) expect_true(inherits(y,"gt_tbl")) expect_warning(t <- summariseConceptIdCounts(cdm, "death")) - expect_warning(inherits(tableAllConceptCounts(t),"gt_tbl")) + expect_warning(inherits(tableConceptIdCounts(t),"gt_tbl")) PatientProfiles::mockDisconnect(cdm = cdm) }) From f5d3b852a34f8075a3f0d203e3289cb27c11e655 Mon Sep 17 00:00:00 2001 From: cecicampanile Date: Fri, 20 Dec 2024 23:27:10 +0000 Subject: [PATCH 3/4] Delete test-summariseAllConceptCounts.R --- .../testthat/test-summariseAllConceptCounts.R | 142 ------------------ 1 file changed, 142 deletions(-) delete mode 100644 tests/testthat/test-summariseAllConceptCounts.R diff --git a/tests/testthat/test-summariseAllConceptCounts.R b/tests/testthat/test-summariseAllConceptCounts.R deleted file mode 100644 index fe1fc8b..0000000 --- a/tests/testthat/test-summariseAllConceptCounts.R +++ /dev/null @@ -1,142 +0,0 @@ -test_that("summariseAllConceptCount works", { - skip_on_cran() - - cdm <- cdmEunomia() - - expect_true(inherits(summariseAllConceptCounts(cdm, "drug_exposure"), "summarised_result")) - expect_warning(summariseAllConceptCounts(cdm, "observation_period")) - expect_no_error(x <- summariseAllConceptCounts(cdm, "visit_occurrence")) - expect_no_error(summariseAllConceptCounts(cdm, "condition_occurrence", countBy = c("record", "person"))) - expect_no_error(summariseAllConceptCounts(cdm, "drug_exposure")) - expect_no_error(summariseAllConceptCounts(cdm, "procedure_occurrence", countBy = "person")) - expect_warning(summariseAllConceptCounts(cdm, "device_exposure")) - expect_no_error(y <- summariseAllConceptCounts(cdm, "measurement")) - expect_no_error(summariseAllConceptCounts(cdm, "observation", year = TRUE)) - expect_warning(p<-summariseAllConceptCounts(cdm, "death")) - - expect_no_error(all <- summariseAllConceptCounts(cdm, c("visit_occurrence", "measurement"))) - expect_equal(all |> sortTibble(), x |> dplyr::bind_rows(y) |> sortTibble()) - expect_equal( - summariseAllConceptCounts(cdm, "procedure_occurrence", countBy = "record") |> - sortTibble(), - summariseAllConceptCounts(cdm, "procedure_occurrence") |> - sortTibble() - ) - expect_warning(summariseAllConceptCounts(cdm, "observation_period")) - expect_error(summariseAllConceptCounts(cdm, omopTableName = "")) - expect_error(summariseAllConceptCounts(cdm, omopTableName = "visit_occurrence", countBy = "dd")) - expect_equal(settings(y)$result_type, settings(p)$result_type) - expect_true(summariseAllConceptCounts(cdm, "procedure_occurrence", sex = TRUE, ageGroup = list(c(0, 50), c(51, Inf))) |> - dplyr::distinct(.data$strata_level) |> - dplyr::tally() |> - dplyr::pull() == 9) - - expect_true(summariseAllConceptCounts(cdm, "procedure_occurrence", ageGroup = list(c(0, 50))) |> - dplyr::distinct(.data$strata_level) |> - dplyr::tally() |> - dplyr::pull() == 3) - - s <- summariseAllConceptCounts(cdm, "procedure_occurrence") |> - sortTibble() - z <- summariseAllConceptCounts(cdm, "procedure_occurrence", sex = TRUE, year = TRUE, ageGroup = list(c(0, 50), c(51, Inf))) |> - sortTibble() - - x <- z |> - dplyr::filter(strata_level == "overall") |> - dplyr::select(variable_level, estimate_value) - s <- s |> - dplyr::select(variable_level, estimate_value) - expect_equal(x, s, ignore_attr = TRUE) - - x <- z |> - dplyr::filter(strata_name == "age_group") |> - dplyr::group_by(variable_level) |> - dplyr::summarise(estimate_value = sum(as.numeric(estimate_value), na.rm = TRUE), .groups = "drop") |> - dplyr::mutate(estimate_value = as.character(estimate_value)) - - p <- s |> - dplyr::select(variable_level, estimate_value) - - expect_true(all.equal( - as.data.frame(x) |> dplyr::arrange(variable_level), - as.data.frame(p) |> dplyr::arrange(variable_level), - check.attributes = FALSE - )) - -}) - -test_that("dateRange argument works", { - skip_on_cran() - # Load mock database ---- - cdm <- cdmEunomia() - expect_no_error(summariseAllConceptCounts(cdm, "condition_occurrence", dateRange = as.Date(c("2012-01-01", "2018-01-01")))) - expect_message(x<-summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2012-01-01", "2025-01-01")))) - observationRange <- cdm$observation_period |> - dplyr::summarise(minobs = min(.data$observation_period_start_date, na.rm = TRUE), - maxobs = max(.data$observation_period_end_date, na.rm = TRUE)) - expect_no_error(y<- summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2012-01-01", observationRange |>dplyr::pull("maxobs"))))) - expect_equal(x |> sortTibble(), y |> sortTibble(), ignore_attr = TRUE) - expect_false(settings(x)$study_period_end==settings(y)$study_period_end) - expect_error(summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2015-01-01", "2014-01-01")))) - expect_warning(y<-summariseAllConceptCounts(cdm, "drug_exposure", dateRange = as.Date(c("2020-01-01", "2021-01-01")))) - expect_equal(y, omopgenerics::emptySummarisedResult(), ignore_attr = TRUE) - expect_equal(settings(y)$result_type, settings(x)$result_type) - expect_equal(colnames(settings(y)), colnames(settings(x))) - PatientProfiles::mockDisconnect(cdm = cdm) -}) -test_that("sample argument works", { - skip_on_cran() - # Load mock database ---- - cdm <- cdmEunomia() - - expect_no_error(x<-summariseAllConceptCounts(cdm,"drug_exposure", sample = 50)) - expect_no_error(y<-summariseAllConceptCounts(cdm,"drug_exposure")) - n <- cdm$drug_exposure |> - dplyr::tally()|> - dplyr::pull(n) - expect_no_error(z<-summariseAllConceptCounts(cdm,"drug_exposure",sample = n)) - expect_equal(y |> sortTibble(), z |> sortTibble()) - PatientProfiles::mockDisconnect(cdm = cdm) -}) - -test_that("tableAllConceptCounts() works", { - skip_on_cran() - # Load mock database ---- - cdm <- cdmEunomia() - - # Check that works ---- - expect_no_error(x <- tableAllConceptCounts(summariseAllConceptCounts(cdm, "condition_occurrence"))) - expect_true(inherits(x,"gt_tbl")) - expect_no_error(y <- tableAllConceptCounts(summariseAllConceptCounts(cdm, c("drug_exposure", - "measurement")))) - expect_true(inherits(y,"gt_tbl")) - expect_warning(t <- summariseAllConceptCounts(cdm, "death")) - expect_warning(inherits(tableAllConceptCounts(t),"gt_tbl")) - - PatientProfiles::mockDisconnect(cdm = cdm) -}) -test_that("no tables created", { - skip_on_cran() - # Load mock database ---- - cdm <- cdmEunomia() - - startNames <- CDMConnector::listSourceTables(cdm) - - results <- summariseAllConceptCounts(cdm = cdm, - omopTableName = c("drug_exposure", "condition_occurrence"), - countBy = c("record", "person"), - year=TRUE, - sex = TRUE, - ageGroup = list(c(0,17), - c(18,65), - c(66, 100)), - dateRange = as.Date(c("2012-01-01", "2018-01-01")), - sample = 100) - - endNames <- CDMConnector::listSourceTables(cdm) - - expect_true(length(setdiff(endNames, startNames)) == 0) - - - PatientProfiles::mockDisconnect(cdm = cdm) -}) From 7fd8d6cf03a17309f884f4a755560fad0f55ab07 Mon Sep 17 00:00:00 2001 From: cecicampanile Date: Sat, 21 Dec 2024 15:39:07 +0000 Subject: [PATCH 4/4] some modifications lost in the process --- R/plotInObservation.R | 18 +- R/plotRecordCount.R | 22 + README.Rmd | 18 +- README.md | 615 +---------------------- man/figures/README-unnamed-chunk-3-1.png | Bin 100547 -> 102014 bytes man/figures/README-unnamed-chunk-4-1.png | Bin 202402 -> 238185 bytes man/figures/README-unnamed-chunk-5-1.png | Bin 8263 -> 63772 bytes man/figures/README-unnamed-chunk-6-1.png | Bin 6184 -> 46388 bytes man/figures/README-unnamed-chunk-7-1.png | Bin 111504 -> 84230 bytes man/figures/README-unnamed-chunk-8-1.png | Bin 5321 -> 21935 bytes man/figures/README-unnamed-chunk-9-1.png | Bin 5894 -> 28494 bytes 11 files changed, 66 insertions(+), 607 deletions(-) diff --git a/R/plotInObservation.R b/R/plotInObservation.R index 750297e..f79b930 100644 --- a/R/plotInObservation.R +++ b/R/plotInObservation.R @@ -59,8 +59,7 @@ plotInObservation <- function(result, # plot if(length(unique(result$additional_level)) > 1 ){ - result |> - dplyr::mutate(additional_level = as.character(gsub("-01$","",as.Date(gsub(" to.*","",.data$additional_level))))) |> + p <- result |> dplyr::filter(.data$estimate_name == "count") |> visOmopResults::scatterPlot( x = "time_interval", @@ -78,6 +77,21 @@ plotInObservation <- function(result, y = variable, x = "Date" ) + p$data <- p$data |> + dplyr::arrange(.data$time_interval) |> + dplyr::mutate( + show_label = seq_along(.data$time_interval) %% ceiling(nrow(p$data) / 20) == 0 + ) + + p <- p + + ggplot2::scale_x_discrete( + breaks = p$data$time_interval[p$data$show_label] + ) + + ggplot2::theme( + axis.text.x = ggplot2::element_text(angle = 90, hjust = 1, size = 8), + plot.margin = ggplot2::margin(t = 5, r = 5, b = 30, l = 5) + ) + p }else{ result |> dplyr::filter(.data$estimate_name == "count") |> diff --git a/R/plotRecordCount.R b/R/plotRecordCount.R index 818122c..6290f1e 100644 --- a/R/plotRecordCount.R +++ b/R/plotRecordCount.R @@ -59,6 +59,28 @@ plotRecordCount <- function(result, y = "Number records", x = "Date" ) + p$data <- p$data |> + dplyr::arrange(.data$time_interval) |> + dplyr::group_by(.data$omop_table) |> + dplyr::mutate( + show_label = if (dplyr::cur_group_id() == 1) { + seq_along(.data$time_interval) %% ceiling(dplyr::n() / 20) == 0 + } else { + FALSE + } + ) |> + dplyr::ungroup() + + # Modify the plot + p <- p + + ggplot2::scale_x_discrete( + breaks = p$data$time_interval[p$data$show_label], + labels = p$data$time_interval[p$data$show_label] + ) + + ggplot2::theme( + axis.text.x = ggplot2::element_text(angle = 90, hjust = 1, size = 8), + plot.margin = ggplot2::margin(t = 5, r = 5, b = 30, l = 5) + ) }else{ p <- result |> visOmopResults::barPlot(x = "variable_name", diff --git a/README.Rmd b/README.Rmd index f68aa45..d027df4 100644 --- a/README.Rmd +++ b/README.Rmd @@ -67,8 +67,8 @@ summariseClinicalRecords(cdm, c("condition_occurrence", "drug_exposure")) |> We can also explore trends in the clinical table records over time. ```{r} -summariseRecordCount(cdm, c("condition_occurrence", "drug_exposure")) |> - plotRecordCount(facet = "omop_table") +summariseRecordCount(cdm, c("condition_occurrence", "drug_exposure"), interval = "years") |> + plotRecordCount(facet = "omop_table", colour = "cdm_name") ``` ### Characterise the observation period After visualising the main characteristics of our clinical tables, we can explore the observation period details. OmopSketch provides several functions to have an overview the dataset study period. @@ -76,8 +76,8 @@ After visualising the main characteristics of our clinical tables, we can explor Using `summariseInObservation()` and `plotInObservation()`, we can gather information on the number of records per year. ```{r} -summariseInObservation(cdm$observation_period, output = "records") |> - plotInObservation() +summariseInObservation(cdm$observation_period, output = "records", interval = "years") |> + plotInObservation(colour = "cdm_name") ``` You can also visualise and explore the characteristics of the observation period per each individual in the database using `summariseObservationPeriod()`. ```{r} @@ -88,7 +88,7 @@ summariseObservationPeriod(cdm$observation_period) |> Or if visualisation is preferred, you can easily build a histogram to explore how many participants have more than one observation period. ```{r} summariseObservationPeriod(cdm$observation_period) |> - plotObservationPeriod() + plotObservationPeriod(colour = "observation_period_ordinal") ``` ### Characterise the concepts @@ -98,14 +98,8 @@ acetaminophen <- c(1125315, 1127433, 1127078) summariseConceptSetCounts(cdm, conceptSet = list("acetaminophen" = acetaminophen)) |> filter(variable_name == "Number records") |> - plotConceptSetCounts() + plotConceptSetCounts(colour = "codelist_name") ``` -### Characterise the population -Finally, OmopSketch can also help us to characterise the population at the start and end of the observation period. -```{r} -summarisePopulationCharacteristics(cdm) |> - tablePopulationCharacteristics(type = "flextable") -``` As seen, OmopSketch offers multiple functionalities to provide a general overview of a database. Additionally, it includes more tools and arguments that allow for deeper exploration, helping to assess the database's suitability for specific research studies. For further information, please refer to the vignettes. diff --git a/README.md b/README.md index e939a3f..5d407ea 100644 --- a/README.md +++ b/README.md @@ -69,7 +69,6 @@ version or the data release. ``` r summariseOmopSnapshot(cdm) |> tableOmopSnapshot(type = "flextable") -#> ! Results have not been suppressed. ``` @@ -84,35 +83,14 @@ visualise the main characteristics of specific clinical tables. ``` r summariseClinicalRecords(cdm, c("condition_occurrence", "drug_exposure")) |> tableClinicalRecords(type = "flextable") -#> ℹ Summarising table counts -#> ℹ The following estimates will be computed: -#> → Start summary of data, at 2024-09-25 12:14:06.676817 -#> -#> ✔ Summary finished, at 2024-09-25 12:14:06.815944 -#> ℹ Summarising records per person -#> ℹ The following estimates will be computed: -#> • records_per_person: mean, sd, median, q25, q75, min, max -#> ! Table is collected to memory as not all requested estimates are supported on -#> the database side -#> → Start summary of data, at 2024-09-25 12:14:07.908258 -#> -#> ✔ Summary finished, at 2024-09-25 12:14:07.955041 -#> ℹ Summarising in_observation, standard, domain_id, and type information -#> ℹ Summarising table counts -#> ℹ The following estimates will be computed: -#> → Start summary of data, at 2024-09-25 12:14:11.725276 -#> -#> ✔ Summary finished, at 2024-09-25 12:14:11.877293 -#> ℹ Summarising records per person -#> ℹ The following estimates will be computed: -#> • records_per_person: mean, sd, median, q25, q75, min, max -#> ! Table is collected to memory as not all requested estimates are supported on -#> the database side -#> → Start summary of data, at 2024-09-25 12:14:12.808874 -#> -#> ✔ Summary finished, at 2024-09-25 12:14:12.850686 -#> ℹ Summarising in_observation, standard, domain_id, and type information -#> ! Results have not been suppressed. +#> ℹ Adding variables of interest to condition_occurrence. +#> ℹ Summarising records per person in condition_occurrence. +#> ℹ Summarising condition_occurrence: `in_observation`, `standard_concept`, +#> `source_vocabulary`, `domain_id`, and `type_concept`. +#> ℹ Adding variables of interest to drug_exposure. +#> ℹ Summarising records per person in drug_exposure. +#> ℹ Summarising drug_exposure: `in_observation`, `standard_concept`, +#> `source_vocabulary`, `domain_id`, and `type_concept`. ``` @@ -120,26 +98,24 @@ summariseClinicalRecords(cdm, c("condition_occurrence", "drug_exposure")) |> We can also explore trends in the clinical table records over time. ``` r -summariseRecordCount(cdm, c("condition_occurrence", "drug_exposure")) |> - plotRecordCount(facet = "omop_table") -#> ! The following column type were changed: -#> • variable_level: from double to character +summariseRecordCount(cdm, c("condition_occurrence", "drug_exposure"), interval = "years") |> + plotRecordCount(facet = "omop_table", colour = "cdm_name") ``` \### Characterise the observation period After visualising the main characteristics of our clinical tables, we can explore the observation period details. OmopSketch provides several functions to have an -overview of the dataset study period. +overview the dataset study period. Using `summariseInObservation()` and `plotInObservation()`, we can gather information on the number of records per year. ``` r -summariseInObservation(cdm$observation_period, output = "records") |> - plotInObservation() -#> ! The following column type were changed: -#> • variable_level: from double to character +summariseInObservation(cdm$observation_period, output = "records", interval = "years") |> + plotInObservation(colour = "cdm_name") +#> `result_id` is not present in result. +#> `result_id` is not present in result. ``` You @@ -150,17 +126,16 @@ period per each individual in the database using ``` r summariseObservationPeriod(cdm$observation_period) |> tableObservationPeriod(type = "flextable") -#> ! Results have not been suppressed. ``` -Or if visualisation is prefered, you can easily build a histogram to +Or if visualisation is preferred, you can easily build a histogram to explore how many participants have more than one observation period. ``` r summariseObservationPeriod(cdm$observation_period) |> - plotObservationPeriod() + plotObservationPeriod(colour = "observation_period_ordinal") ``` @@ -174,561 +149,15 @@ concepts in the dataset. acetaminophen <- c(1125315, 1127433, 1127078) summariseConceptSetCounts(cdm, conceptSet = list("acetaminophen" = acetaminophen)) |> - filter(estimate_name == "record_count") |> - plotConceptCounts() -#> ℹ Getting use of codes from acetaminophen -#> ! The following column type were changed: -#> • variable_name: from integer to character + filter(variable_name == "Number records") |> + plotConceptSetCounts(colour = "codelist_name") +#> Warning: ! `codelist` contains numeric values, they are casted to integers. +#> ℹ Searching concepts from domain drug in drug_exposure. +#> ℹ Counting concepts ``` -### Characterise the population - -Finally, OmopSketch can also help us to characterise the population at -the start and end of the observation period. - -``` r -summarisePopulationCharacteristics(cdm) |> - tablePopulationCharacteristics(type = "flextable") -#> Warning: ! 1 casted column in og_015_1727262876 (cohort_set) as do not match expected -#> column type: -#> • `cohort_definition_id` from numeric to integer -#> Warning: ! 1 column in og_015_1727262876 do not match expected column type: -#> • `cohort_definition_id` is numeric but expected integer -#> ! cohort columns will be reordered to match the expected order: -#> cohort_definition_id, subject_id, cohort_start_date, and cohort_end_date. -#> ℹ Building new trimmed cohort -#> Warning: ! 1 column in tmp_011_og_017_1727262877 do not match expected column type: -#> • `cohort_definition_id` is numeric but expected integer -#> Creating initial cohort -#> ! cohort columns will be reordered to match the expected order: -#> cohort_definition_id, subject_id, cohort_start_date, and cohort_end_date. -#> ! cohort columns will be reordered to match the expected order: -#> cohort_definition_id, subject_id, cohort_start_date, and cohort_end_date. -#> ✔ Cohort trimmed -#> ℹ adding demographics columns -#> -#> ℹ summarising data -#> -#> ✔ summariseCharacteristics finished! -#> -#> ! The following column type were changed: -#> • variable_name: from integer to character -#> ! Results have not been suppressed. -``` - -
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Variable nameVariable levelEstimate name - Database name -
Synthea synthetic health database
Number records-N2,694
Number subjects-N2,694
Cohort start date-Median [Q25 - Q75]1961-03-18 [1950-07-13 - 1970-08-29]
Range1908-09-22 to 1986-11-03
Cohort end date-Median [Q25 - Q75]2018-12-14 [2018-08-02 - 2019-04-06]
Range1945-07-20 to 2019-07-03
Age at start-Median [Q25 - Q75]0 [0 - 0]
Mean (SD)0.00 (0.00)
Range0 to 0
Age at end-Median [Q25 - Q75]57 [47 - 67]
Range31 to 110
SexFemaleN%1,373 (50.97)
MaleN%1,321 (49.03)
Prior observation-Median [Q25 - Q75]0 [0 - 0]
Mean (SD)0.00 (0.00)
Range0 to 0
Future observation-Median [Q25 - Q75]20,870 [17,494 - 24,701]
Mean (SD)21,601.60 (5,460.69)
Range11,396 to 40,348
-
- As seen, OmopSketch offers multiple functionalities to provide a general overview of a database. 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