The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Let’s first create a cdm reference to the Eunomia synthetic data.
One base cohort we can create is based around patient demographics. Here for example we create a cohort where people enter on their 18th birthday and leave at age 65 or
cdm$working_age_cohort <- demographicsCohort(cdm = cdm,
ageRange = c(18, 65),
name = "working_age_cohort")
settings(cdm$working_age_cohort)
#> # A tibble: 1 × 3
#> cohort_definition_id cohort_name age_range
#> <dbl> <chr> <chr>
#> 1 1 demographics 18_65
cohortCount(cdm$working_age_cohort)
#> # A tibble: 1 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
#> 1 1 2694 2694
attrition(cdm$working_age_cohort)
#> # A tibble: 2 × 7
#> cohort_definition_id number_records number_subjects reason_id reason
#> <int> <int> <int> <int> <chr>
#> 1 1 2694 2694 1 Initial qualify…
#> 2 1 2694 2694 2 Age requirement…
#> # ℹ 2 more variables: excluded_records <int>, excluded_subjects <int>
cdm$working_age_cohort |>
addAge(indexDate = "cohort_start_date") |>
summarise(min_start_age = min(age),
median_start_age = median(age),
max_start_age = max(age))
#> # Source: SQL [1 x 3]
#> # Database: DuckDB v0.10.3-dev775 [eburn@Windows 10 x64:R 4.4.0/C:\Users\eburn\AppData\Local\Temp\RtmpgHH2qN\file5b383dc01d2e.duckdb]
#> min_start_age median_start_age max_start_age
#> <int> <dbl> <int>
#> 1 17 18 18
cdm$working_age_cohort |>
addAge(indexDate = "cohort_end_date") |>
summarise(min_start_age = min(age),
median_start_age = median(age),
max_start_age = max(age))
#> # Source: SQL [1 x 3]
#> # Database: DuckDB v0.10.3-dev775 [eburn@Windows 10 x64:R 4.4.0/C:\Users\eburn\AppData\Local\Temp\RtmpgHH2qN\file5b383dc01d2e.duckdb]
#> min_start_age median_start_age max_start_age
#> <int> <dbl> <int>
#> 1 31 57 65
drug_codes <- getDrugIngredientCodes(cdm,
name = c("diclofenac",
"acetaminophen"))
drug_codes
#>
#> - diclofenac (1 codes)
#> - acetaminophen (7 codes)
cdm$medications <- conceptCohort(cdm = cdm,
conceptSet = drug_codes,
name = "medications")
settings(cdm$medications)
#> # A tibble: 2 × 2
#> cohort_definition_id cohort_name
#> <int> <chr>
#> 1 1 diclofenac
#> 2 2 acetaminophen
cohortCount(cdm$medications)
#> # A tibble: 2 × 3
#> cohort_definition_id number_records number_subjects
#> <int> <int> <int>
#> 1 1 830 830
#> 2 2 13908 2679
TO DO
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.