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@edward-burn
edward-burn committed Jan 16, 2025
1 parent de26632 commit 5ebcc57
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4 changes: 2 additions & 2 deletions README.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -54,8 +54,8 @@ library(CohortCharacteristics)

```{r, message=TRUE, warning=FALSE}
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
cdm
```

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43 changes: 27 additions & 16 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -50,14 +50,19 @@ library(CohortCharacteristics)

``` r
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
#> Support for 'prefix' in writeSchema is deprecated and will be removed in a future release. Please use the `writePrefix` argument in `cdmFromCon()` instead.
#> Note: method with signature 'DBIConnection#Id' chosen for function 'dbExistsTable',
#> target signature 'duckdb_connection#Id'.
#> "duckdb_connection#ANY" would also be valid
#>
#> ! cdm name not specified and could not be inferred from the cdm source table
#>
#> This message is displayed once per session.
cdm
#>
#> ── # OMOP CDM reference (duckdb) of Synthea synthetic health database ──────────
#> ── # OMOP CDM reference (duckdb) of An OMOP CDM database ───────────────────────
#> • omop tables: person, observation_period, visit_occurrence, visit_detail,
#> condition_occurrence, drug_exposure, procedure_occurrence, device_exposure,
#> measurement, observation, death, note, note_nlp, specimen, fact_relationship,
Expand All @@ -79,6 +84,7 @@ synthetic data with a subset of the full vocabularies).

``` r
library(CodelistGenerator)
#> Warning: package 'CodelistGenerator' was built under R version 4.4.2

hip_fx_codes <- getCandidateCodes(cdm, "hip fracture")
#> Limiting to domains of interest
Expand All @@ -87,15 +93,15 @@ hip_fx_codes <- getCandidateCodes(cdm, "hip fracture")
#> Search completed. Finishing up.
#> ✔ 1 candidate concept identified
#>
#> Time taken: 0 minutes and 0 seconds
#> Time taken: 0 minutes and 1 seconds
forearm_fx_codes <- getCandidateCodes(cdm, "forearm fracture")
#> Limiting to domains of interest
#> Getting concepts to include
#> Adding descendants
#> Search completed. Finishing up.
#> ✔ 1 candidate concept identified
#>
#> Time taken: 0 minutes and 0 seconds
#> Time taken: 0 minutes and 1 seconds

fx_codes <- newCodelist(list("hip_fracture" = hip_fx_codes$concept_id,
"forearm_fracture"= forearm_fx_codes$concept_id))
Expand Down Expand Up @@ -142,21 +148,26 @@ settings(cdm$fractures) |> glimpse()
#> $ cdm_version <chr> "5.3", "5.3"
#> $ vocabulary_version <chr> "v5.0 18-JAN-19", "v5.0 18-JAN-19"
cohort_count(cdm$fractures) |> glimpse()
#> Warning: `cohort_count()` was deprecated in CDMConnector 1.7.0.
#> ℹ Please use `cohortCount()` instead.
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
#> generated.
#> Rows: 2
#> Columns: 3
#> $ cohort_definition_id <int> 1, 2
#> $ number_records <int> 569, 138
#> $ number_subjects <int> 510, 132
attrition(cdm$fractures) |> glimpse()
#> Rows: 4
#> Rows: 10
#> Columns: 7
#> $ cohort_definition_id <int> 1, 1, 2, 2
#> $ number_records <int> 569, 569, 138, 138
#> $ number_subjects <int> 510, 510, 132, 132
#> $ reason_id <int> 1, 2, 1, 2
#> $ reason <chr> "Initial qualifying events", "Pad cohort start da…
#> $ excluded_records <int> 0, 0, 0, 0
#> $ excluded_subjects <int> 0, 0, 0, 0
#> $ cohort_definition_id <int> 1, 1, 1, 1, 1, 2, 2, 2, 2, 2
#> $ number_records <int> 569, 569, 569, 569, 569, 138, 138, 138, 138, 138
#> $ number_subjects <int> 510, 510, 510, 510, 510, 132, 132, 132, 132, 132
#> $ reason_id <int> 1, 2, 3, 4, 5, 1, 2, 3, 4, 5
#> $ reason <chr> "Initial qualifying events", "Record start <= rec…
#> $ excluded_records <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
#> $ excluded_subjects <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
```

### Create an overall fracture cohort
Expand Down Expand Up @@ -248,7 +259,7 @@ attrition(cdm$fractures) |>
#> $ cohort_definition_id <int> 1, 2, 3
#> $ number_records <int> 64, 22, 86
#> $ number_subjects <int> 62, 22, 83
#> $ reason_id <int> 5, 5, 4
#> $ reason_id <int> 8, 8, 4
#> $ reason <chr> "Age requirement: 40 to 65", "Age requirement: 40…
#> $ excluded_records <int> 88, 40, 128
#> $ excluded_subjects <int> 81, 38, 113
Expand All @@ -261,7 +272,7 @@ attrition(cdm$fractures) |>
#> $ cohort_definition_id <int> 1, 2, 3
#> $ number_records <int> 37, 12, 49
#> $ number_subjects <int> 36, 12, 48
#> $ reason_id <int> 6, 6, 5
#> $ reason_id <int> 9, 9, 5
#> $ reason <chr> "Sex requirement: Female", "Sex requirement: Fema…
#> $ excluded_records <int> 27, 10, 37
#> $ excluded_subjects <int> 26, 10, 35
Expand Down Expand Up @@ -294,7 +305,7 @@ attrition(cdm$fractures) |>
#> $ cohort_definition_id <int> 1, 2, 3
#> $ number_records <int> 30, 10, 40
#> $ number_subjects <int> 30, 10, 40
#> $ reason_id <int> 9, 9, 8
#> $ reason_id <int> 12, 12, 8
#> $ reason <chr> "Not in cohort gibleed between -Inf & 0 days rela…
#> $ excluded_records <int> 7, 2, 9
#> $ excluded_subjects <int> 6, 2, 8
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8 changes: 4 additions & 4 deletions vignettes/a07_filter_cohorts.Rmd
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Expand Up @@ -67,8 +67,8 @@ It is also possible to only sample one cohort within cohort table, however the r

```{r include = FALSE, warning = FALSE}
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
cdm$medications <- conceptCohort(cdm = cdm,
conceptSet = list("diclofenac" = 1124300,
"acetaminophen" = 1127433),
Expand All @@ -87,8 +87,8 @@ If you want to filter the cohort table to only include individuals and records f

```{r include = FALSE, warning = FALSE}
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
cdm$medications <- conceptCohort(cdm = cdm,
conceptSet = list("diclofenac" = 1124300,
"acetaminophen" = 1127433),
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4 changes: 2 additions & 2 deletions vignettes/a08_split_cohorts.Rmd
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Expand Up @@ -63,8 +63,8 @@ We can also split cohorts for specified years using the function `yearCohorts()`

```{r, include=FALSE, warning=FALSE}
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
cdm$medications <- conceptCohort(cdm = cdm,
conceptSet = list("diclofenac" = 1124300,
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12 changes: 6 additions & 6 deletions vignettes/a09_combine_cohorts.Rmd
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Expand Up @@ -41,8 +41,8 @@ For this example we'll use the Eunomia synthetic data from the CDMConnector pack

```{r}
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
```

Let's start by creating two drug cohorts, one for users of diclofenac and another for users of acetaminophen.
Expand Down Expand Up @@ -104,8 +104,8 @@ We have now created a new cohort which includes individuals in either the diclof

```{r, include=FALSE, warning=FALSE}
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
cdm$medications <- conceptCohort(cdm = cdm,
conceptSet = list("diclofenac" = 1124300,
"acetaminophen" = 1127433),
Expand All @@ -127,8 +127,8 @@ You can also choose the number of days between two subsequent cohort entries to

```{r, include=FALSE, warning=FALSE}
con <- DBI::dbConnect(duckdb::duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(con, cdm_schema = "main",
write_schema = c(prefix = "my_study_", schema = "main"))
cdm <- cdmFromCon(con, cdmSchema = "main",
writeSchema = c(prefix = "my_study_", schema = "main"))
cdm$medications <- conceptCohort(cdm = cdm,
conceptSet = list("diclofenac" = 1124300,
"acetaminophen" = 1127433),
Expand Down

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