library(CDMConnector)
library(dplyr)
library(PatientProfiles)
# For this example we will use GiBleed data set
CDMConnector::downloadEunomiaData(datasetName = "GiBleed")
db <- DBI::dbConnect(duckdb::duckdb(), eunomiaDir())
cdm <- cdmFromCon(db, cdmSchema = "main", writeSchema = "main")
# cdm <- cdm |>
# generate_concept_cohort_set(concept_set = list("gi_bleed" = 192671),
# limit = "all",
# end = 30,
# name = "gi_bleed",
# overwrite = TRUE) |>
# generate_concept_cohort_set(concept_set = list("acetaminophen" = c(1125315,
# 1127078,
# 1127433,
# 40229134,
# 40231925,
# 40162522,
# 19133768)),
# limit = "all",
# # end = "event_end_date",
# name = "acetaminophen",
# overwrite = TRUE)9 Working with cohorts
9.1 Cohort intersections
PatientProfiles::addCohortIntersect()
9.2 Intersection between two cohorts
9.3 Set up
9.3.1 Flag
# cdm$gi_bleed <- cdm$gi_bleed |>
# addCohortIntersectFlag(targetCohortTable = "acetaminophen",
# window = list(c(-Inf, -1), c(0,0), c(1, Inf)))
#
# cdm$gi_bleed |>
# summarise(acetaminophen_prior = sum(acetaminophen_minf_to_m1),
# acetaminophen_index = sum(acetaminophen_0_to_0),
# acetaminophen_post = sum(acetaminophen_1_to_inf)) |>
# collect()9.3.2 Count
9.3.3 Date and times
9.4 Intersection between a cohort and tables with patient data
10 Further reading
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