## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  eval = TRUE, message = FALSE, warning = FALSE,
  comment = "#>"
)

## -----------------------------------------------------------------------------
library(duckdb)
library(CDMConnector)
library(PatientProfiles)
library(CohortConstructor)
library(dplyr, warn.conflicts = FALSE)
library(clock)

## -----------------------------------------------------------------------------
requireEunomia(datasetName = "GiBleed")
con <- dbConnect(drv = duckdb(), dbdir = eunomiaDir())
cdm <- cdmFromCon(
  con = con, cdmSchema = "main", writeSchema = "main", writePrefix = "my_study_"
)

## -----------------------------------------------------------------------------
cdm$medications <- conceptCohort(cdm = cdm, 
                                 conceptSet = list("diclofenac" = 1124300L,
                                                   "acetaminophen" = 1127433L), 
                                 name = "medications")
cohortCount(cdm$medications)
settings(cdm$medications)

## -----------------------------------------------------------------------------
cdm$medications_female <- cdm$medications |>
  requireSex(sex = "Female", name = "medications_female") |>
  renameCohort(
    cohortId = c("acetaminophen", "diclofenac"), 
    newCohortName = c("acetaminophen_female", "diclofenac_female")
  )
cdm$medications_male <- cdm$medications |>
  requireSex(sex = "Male", name = "medications_male") |>
  renameCohort(
    cohortId = c("acetaminophen", "diclofenac"), 
    newCohortName = c("acetaminophen_male", "diclofenac_male")
  )
cdm <- bind(cdm$medications_female, cdm$medications_male, name = "medications_sex")
cohortCount(cdm$medications_sex)
settings(cdm$medications_sex)

## -----------------------------------------------------------------------------
cdm$medications <- cdm$medications |>
  addSex()
cdm$medications

## -----------------------------------------------------------------------------
cdm$medications_sex_2 <- cdm$medications |>
  stratifyCohorts(strata = "sex", name = "medications_sex_2")
cohortCount(cdm$medications_sex_2)
settings(cdm$medications_sex_2)

## ----warning=FALSE------------------------------------------------------------
cdm$stratified <- cdm$medications |>
  addAge(ageGroup = list("child" = c(0,17), "18_to_65" = c(18,64), "65_and_over" = c(65, Inf))) |>
  addSex() |>
  mutate(year = get_year(cohort_start_date)) |>
  stratifyCohorts(strata = list(c("sex", "age_group"), "year"), name = "stratified")

cohortCount(cdm$stratified)
settings(cdm$stratified)

## ----echo=FALSE---------------------------------------------------------------
library(ggplot2)
x <- tibble(
  time = as.Date(c("2010-05-01", "2012-06-12", "2010-05-01", "2010-12-31", "2011-01-01", "2011-12-31", "2012-01-01", "2012-06-12")),
  y = c(rep(1, 2), rep(0.8, 2), rep(0.78, 2), rep(0.76, 2)),
  colour = c(rep("1", 2), rep("2", 6)),
  group = c(1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L)
)
ggplot(data = x, mapping = aes(x = time, y = y, colour = colour, group = group)) +
  geom_line() +
  geom_point() +
  scale_y_continuous(limits = c(0.56, 1.2), breaks = NULL, labels = NULL) +
  theme_bw() +
  theme(
    axis.title.y = element_blank(),
    axis.text.y = element_blank(),
    axis.ticks.y = element_blank(),
    legend.position = "none"
  )

## -----------------------------------------------------------------------------
cdm$medications_year <- cdm$medications |>
  yearCohorts(years = c(1990:1993), name = "medications_year")
settings(cdm$medications_year)
cohortCount(cdm$medications_year)

## -----------------------------------------------------------------------------
cdm$medications |> 
  filter(subject_id == 4383)

## -----------------------------------------------------------------------------
cdm$medications_year |>
  dplyr::filter(subject_id == 4383)

## -----------------------------------------------------------------------------
cdmDisconnect(cdm)