v3.3.2

Author: edward-burn

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: CodelistGenerator
 Title: Identify Relevant Clinical Codes and Evaluate Their Use
-Version: 3.3.1
+Version: 3.3.2
 Authors@R: c(
     person("Edward", "Burn", email = "edward.burn@ndorms.ox.ac.uk", 
     role = c("aut", "cre"),
@@ -25,28 +25,29 @@ Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.3.2
 Depends:
-    R (>= 3.5.0)
+    R (>= 4.1)
 Imports:
     checkmate (>= 2.0.0),
     DBI (>= 1.1.0),
     dplyr (>= 1.1.0),
-    omopgenerics (>= 0.4.0),
+    omopgenerics (>= 0.4.1),
     rlang (>= 1.0.0),
     glue (>= 1.5.0),
     stringr (>= 1.4.0),
+    stringi (>= 1.8.1),
     tidyselect (>= 1.2.0),
     tidyr (>= 1.2.0),
     cli (>= 3.1.0),
     purrr,
     lubridate,
-    PatientProfiles (>= 1.1.0),
+    PatientProfiles (>= 1.2.3),
     vctrs,
-    visOmopResults (>= 0.5.0),
     RJSONIO
 Suggests: 
     covr,
     duckdb,
-    CDMConnector (>= 1.3.0),
+    CDMConnector (>= 1.7.0),
+    visOmopResults (>= 1.0.0),
     knitr,
     rmarkdown,
     testthat (>= 3.0.0),

R/getMappings.R

@@ -18,7 +18,7 @@
 #' Show mappings from non-standard vocabularies to standard
 #'
 #' @param candidateCodelist Dataframe
-#' @param cdm cdm_reference via CDMConnector::cdm_from_con()
+#' @param cdm cdm_reference via CDMConnector::cdmFromCon()
 #' @param nonStandardVocabularies Character vector
 #'
 #' @return tibble

R/runSearch.R

@@ -391,6 +391,7 @@ tidyWords <- function(words) {
   Encoding(words) <- "latin1"
 
   # some generic formatting
+  workingWords <- stringi::stri_trans_nfkc(words)
   workingWords <- trimws(words)
   workingWords <- stringr::str_replace_all(workingWords, "-", " ")
   workingWords <- stringr::str_replace_all(workingWords, "[[:punct:]]", "")

R/summariseAchillesCodeUse.R

@@ -1,7 +1,7 @@
 #' Summarise code use from achilles counts
 #'
 #' @param x Codelist
-#' @param cdm cdm_reference via CDMConnector::cdm_from_con()
+#' @param cdm cdm_reference via CDMConnector::cdmFromCon()
 #' @param countBy Either "record" for record-level counts or "person" for
 #' person-level counts
 #'
@@ -113,8 +113,8 @@ summariseAchillesCodeUse <- function(x,
         estimate_type = "integer",
         estimate_value = as.character(.data$n)
       ) |>
-      visOmopResults::uniteAdditional(cols = c("standard_concept", "vocabulary_id")) |>
-      visOmopResults::uniteStrata(cols = c("domain_id")) |>
+      omopgenerics::uniteAdditional(cols = c("standard_concept", "vocabulary_id")) |>
+      omopgenerics::uniteStrata(cols = c("domain_id")) |>
       dplyr::select(dplyr::any_of(omopgenerics::resultColumns("summarised_result")))
 
     codeUse <- codeUse |>

R/summariseCodeUse.R

@@ -17,7 +17,7 @@
 #' Summarise code use in patient-level data
 #'
 #' @param x List of concept IDs
-#' @param cdm cdm_reference via CDMConnector::cdm_from_con()
+#' @param cdm cdm_reference via CDMConnector::cdmFromCon()
 #' @param countBy Either "record" for record-level counts or "person" for
 #' person-level counts
 #' @param byConcept TRUE or FALSE. If TRUE code use will be summarised by
@@ -32,10 +32,10 @@
 #' @examples
 #' \dontrun{
 #' con <- DBI::dbConnect(duckdb::duckdb(),
-#'                       dbdir = CDMConnector::eunomia_dir())
-#' cdm <- CDMConnector::cdm_from_con(con,
-#'                                   cdm_schem = "main",
-#'                                   write_schema = "main")
+#'                       dbdir = CDMConnector::eunomiaDir())
+#' cdm <- CDMConnector::cdmFromCon(con,
+#'                                 cdmSchema = "main",
+#'                                 writeSchema = "main")
 #'acetiminophen <- c(1125315,  1127433, 40229134,
 #'40231925, 40162522, 19133768,  1127078)
 #'poliovirus_vaccine <- c(40213160)
@@ -101,7 +101,7 @@ summariseCodeUse <- function(x,
 #' Summarise code use among a cohort in the cdm reference
 #'
 #' @param x Vector of concept IDs
-#' @param cdm cdm_reference via CDMConnector::cdm_from_con()
+#' @param cdm cdm_reference via CDMConnector::cdmFromCon()
 #' @param cohortTable A cohort table from the cdm reference.
 #' @param cohortId A vector of cohort IDs to include
 #' @param timing When to assess the code use relative cohort dates. This can
@@ -121,10 +121,10 @@ summariseCodeUse <- function(x,
 #' @examples
 #' \dontrun{
 #' con <- DBI::dbConnect(duckdb::duckdb(),
-#'                       dbdir = CDMConnector::eunomia_dir())
-#' cdm <- CDMConnector::cdm_from_con(con,
-#'                                   cdm_schem = "main",
-#'                                   write_schema = "main")
+#'                       dbdir = CDMConnector::eunomiaDir())
+#' cdm <- CDMConnector::cdmFromCon(con,
+#'                                   cdmSchema = "main",
+#'                                   writeSchema = "main")
 #' cdm <- CDMConnector::generateConceptCohortSet(cdm = cdm,
 #' conceptSet = list(a = 260139,
 #'                   b = 1127433),
@@ -203,7 +203,7 @@ summariseCohortCodeUse <- function(x,
         )
       )
   } else {
-    codeUse <- omopgenerics::emptySummarisedResult()
+    cohortCodeUse <- omopgenerics::emptySummarisedResult()
   }
 
   return(cohortCodeUse)
@@ -321,8 +321,8 @@ getCodeUse <- function(x,
         "variable_name" = dplyr::if_else(is.na(.data$standard_concept_name), "overall", .data$standard_concept_name),
         "variable_level" = as.character(.data$standard_concept_id)
       ) |>
-      visOmopResults::uniteGroup(cols = c("cohort_name", "codelist_name")) |>
-      visOmopResults::uniteAdditional(
+      omopgenerics::uniteGroup(cols = c("cohort_name", "codelist_name")) |>
+      omopgenerics::uniteAdditional(
         cols = c("source_concept_name", "source_concept_id",
                  "source_concept_value", "domain_id"),
         ignore = "overall"
@@ -334,7 +334,7 @@ getCodeUse <- function(x,
       )
 
   } else {
-    codeCounts <- dplyr::tibble()
+    codeCounts <- omopgenerics::emptySummarisedResult()
     cli::cli_inform(c(
       "i" = "No records found in the cdm for the concepts provided."
     ))
@@ -715,7 +715,7 @@ getGroupedRecordCount <- function(records,
       dplyr::mutate(estimate_value = as.character(.data$estimate_value)) |>
       dplyr::collect()
     )  |>
-    visOmopResults::uniteStrata(cols = groupBy) |>
+    omopgenerics::uniteStrata(cols = groupBy) |>
     dplyr::mutate(estimate_name = "record_count")
 
   return(groupedCounts)
@@ -749,7 +749,7 @@ getGroupedPersonCount <- function(records,
       dplyr::tally(name = "estimate_value") |>
       dplyr::mutate(estimate_value = as.character(.data$estimate_value)) |>
       dplyr::collect()) |>
-    visOmopResults::uniteStrata(cols = groupBy) |>
+    omopgenerics::uniteStrata(cols = groupBy) |>
     dplyr::mutate(estimate_name = "person_count")
 
   return(groupedCounts)

R/tableAchillesCodeUse.R

@@ -43,6 +43,8 @@ tableAchillesCodeUse <- function(result,
                                  hide = character(),
                                  .options = list()) {
 
+  rlang::check_installed("visOmopResults", version = "1.0.0")
+
   # checks
   if(nrow(result) == 0){
     cli::cli_warn("`result` object is empty")
@@ -122,6 +124,8 @@ tableOrphanCodes <- function(result,
                              hide = character(),
                              .options = list()) {
 
+  rlang::check_installed("visOmopResults", version = "1.0.0")
+
   if(nrow(result) == 0){
     cli::cli_warn("`result` object is empty")
     return(emptyResultTable(type = type))

R/tableCodeUse.R

@@ -31,10 +31,10 @@
 #' @examples
 #' \dontrun{
 #' con <- DBI::dbConnect(duckdb::duckdb(),
-#'                       dbdir = CDMConnector::eunomia_dir())
-#' cdm <- CDMConnector::cdm_from_con(con,
-#'                                   cdm_schem = "main",
-#'                                   write_schema = "main")
+#'                       dbdir = CDMConnector::eunomiaDir())
+#' cdm <- CDMConnector::cdmFromCon(con,
+#'                                 cdmSchema = "main",
+#'                                 writeSchema = "main")
 #'acetiminophen <- c(1125315,  1127433, 40229134,
 #'40231925, 40162522, 19133768,  1127078)
 #'poliovirus_vaccine <- c(40213160)
@@ -53,6 +53,8 @@ tableCodeUse <- function(result,
                          hide = character(),
                          .options = list()) {
 
+  rlang::check_installed("visOmopResults", version = "1.0.0")
+
   # checks
   if(nrow(result) == 0){
     cli::cli_warn("`result` object is empty")
@@ -116,10 +118,10 @@ tableCodeUse <- function(result,
 #' @examples
 #' \dontrun{
 #' con <- DBI::dbConnect(duckdb::duckdb(),
-#'                       dbdir = CDMConnector::eunomia_dir())
-#' cdm <- CDMConnector::cdm_from_con(con,
-#'                                   cdm_schem = "main",
-#'                                   write_schema = "main")
+#'                       dbdir = CDMConnector::eunomiaDir())
+#' cdm <- CDMConnector::cdmFromCon(con,
+#'                                   cdmSchema = "main",
+#'                                   writeSchema = "main")
 #' cdm <- CDMConnector::generateConceptCohortSet(cdm = cdm,
 #' conceptSet = list(a = 260139,
 #'                   b = 1127433),
@@ -145,6 +147,8 @@ tableCohortCodeUse <- function(result,
                                hide = character(),
                                .options = list()) {
 
+  rlang::check_installed("visOmopResults", version = "1.0.0")
+
   # checks
   if(nrow(result) == 0){
     cli::cli_warn("`result` object is empty")
@@ -191,9 +195,9 @@ internalTableCodeUse <- function(result,
   .options <- optionsCodeUse(.options)
 
   if (timing) {
-    settingsColumns <- "timing"
+    settingsColumn <- "timing"
   } else {
-    settingsColumns <- character()
+    settingsColumn <- character()
   }
 
   x <- result |>
@@ -211,7 +215,7 @@ internalTableCodeUse <- function(result,
     header = header,
     groupColumn = groupColumn,
     type = type,
-    settingsColumns = settingsColumns,
+    settingsColumn = settingsColumn,
     rename = c(
       "Domain ID" = "domain_id", "Database name" = "cdm_name",
       "Standard concept ID" = "standard_concept_id",

R/tableUnmappedCodes.R

@@ -34,6 +34,9 @@ tableUnmappedCodes <- function(result,
                                groupColumn = character(),
                                hide = character(),
                                .options = list()) {
+
+  rlang::check_installed("visOmopResults", version = "1.0.0")
+
   # checks
   if(nrow(result) == 0){
     cli::cli_warn("`result` object is empty")

README.Rmd

@@ -44,8 +44,11 @@ library(CodelistGenerator)
 
 For this example we'll use the Eunomia dataset (which only contains a subset of the OMOP CDM vocabularies)
 ```{r}
-db <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomia_dir())
-cdm <- cdm_from_con(db, cdm_schema = "main", write_schema = c(prefix = "cg_", schema = "main"))
+db <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
+cdm <- cdmFromCon(db, 
+                  cdmSchema = "main", 
+                  writeSchema = "main", 
+                  writePrefix = "cg_")
 ```
 
 ## Exploring the OMOP CDM Vocabulary tables

README.md

@@ -39,8 +39,11 @@ For this example we’ll use the Eunomia dataset (which only contains a
 subset of the OMOP CDM vocabularies)
 
 ``` r
-db <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomia_dir())
-cdm <- cdm_from_con(db, cdm_schema = "main", write_schema = c(prefix = "cg_", schema = "main"))
+db <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
+cdm <- cdmFromCon(db, 
+                  cdmSchema = "main", 
+                  writeSchema = "main", 
+                  writePrefix = "cg_")
 ```
 
 ## Exploring the OMOP CDM Vocabulary tables
@@ -186,16 +189,16 @@ summariseCodeUse(list("asthma" = asthma_codes1$concept_id),
 #> Rows: 6
 #> Columns: 13
 #> $ result_id        <int> 1, 1, 1, 1, 1, 1
-#> $ cdm_name         <chr> "Synthea synthetic health database", "Synthea synthet…
+#> $ cdm_name         <chr> "An OMOP CDM database", "An OMOP CDM database", "An O…
 #> $ group_name       <chr> "codelist_name", "codelist_name", "codelist_name", "c…
 #> $ group_level      <chr> "asthma", "asthma", "asthma", "asthma", "asthma", "as…
 #> $ strata_name      <chr> "overall", "overall", "overall", "overall", "overall"…
 #> $ strata_level     <chr> "overall", "overall", "overall", "overall", "overall"…
-#> $ variable_name    <chr> "overall", "Childhood asthma", "Asthma", "overall", "…
-#> $ variable_level   <chr> NA, "4051466", "317009", NA, "317009", "4051466"
+#> $ variable_name    <chr> "overall", "Asthma", "Childhood asthma", "overall", "…
+#> $ variable_level   <chr> NA, "317009", "4051466", NA, "4051466", "317009"
 #> $ estimate_name    <chr> "record_count", "record_count", "record_count", "pers…
 #> $ estimate_type    <chr> "integer", "integer", "integer", "integer", "integer"…
-#> $ estimate_value   <chr> "101", "96", "5", "101", "5", "96"
-#> $ additional_name  <chr> "overall", "source_concept_name &&& source_concept_id…
-#> $ additional_level <chr> "overall", "Childhood asthma &&& 4051466 &&& conditio…
+#> $ estimate_value   <chr> "101", "5", "96", "101", "96", "5"
+#> $ additional_name  <chr> "source_concept_name &&& source_concept_id &&& source…
+#> $ additional_level <chr> "NA &&& NA &&& NA &&& NA", "Asthma &&& 317009 &&& 195…
 ```