inst/doc/findings_domain.R

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

library(sdtm.oak)
library(admiraldev)
library(rlang)
library(dplyr, warn.conflicts = FALSE)

## ----eval=TRUE----------------------------------------------------------------
vs_raw <- read.csv(system.file("raw_data/vitals_raw_data.csv",
  package = "sdtm.oak"
))

## ----eval=TRUE, echo=FALSE----------------------------------------------------
sdtm.oak:::dataset_oak_vignette(
  vs_raw,
  display_vars = exprs(
    PATNUM, FORML, ASMNTDN, TMPTC, VTLD, VTLTM, SUBPOS, SYS_BP, DIA_BP,
    PULSE, RESPRT, TEMP, TEMPLOC, OXY_SAT, LAT, LOC
  )
)

## ----eval=TRUE----------------------------------------------------------------
vs_raw <- vs_raw %>%
  generate_oak_id_vars(
    pat_var = "PATNUM",
    raw_src = "vitals"
  )

## ----eval=TRUE, echo=FALSE----------------------------------------------------
sdtm.oak:::dataset_oak_vignette(
  vs_raw,
  display_vars = exprs(
    oak_id, raw_source, patient_number, PATNUM, FORML, SYS_BP, DIA_BP
  )
)

## ----eval=TRUE, echo=FALSE----------------------------------------------------
dm <- read.csv(system.file("raw_data/dm.csv",
  package = "sdtm.oak"
))

## ----eval=TRUE----------------------------------------------------------------
study_ct <- read.csv(system.file("raw_data/sdtm_ct.csv",
  package = "sdtm.oak"
))

## ----eval=TRUE, echo=FALSE----------------------------------------------------
sdtm.oak:::dataset_oak_vignette(
  study_ct,
  display_vars = exprs(
    codelist_code, term_code, term_value, collected_value, term_preferred_term,
    term_synonyms
  )
)

## ----eval=TRUE----------------------------------------------------------------
# Map topic variable SYSBP and its qualifiers.
vs_sysbp <-
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "SYS_BP",
    tgt_var = "VSTESTCD",
    tgt_val = "SYSBP",
    ct_spec = study_ct,
    ct_clst = "C66741"
  ) %>%
  # Filter for records where VSTESTCD is not empty.
  # Only these records need qualifier mappings.
  dplyr::filter(!is.na(.data$VSTESTCD))

## ----eval=TRUE, echo=FALSE----------------------------------------------------
sdtm.oak:::dataset_oak_vignette(
  vs_sysbp,
  display_vars = exprs(
    oak_id, raw_source, patient_number, VSTESTCD
  )
)

## ----eval=TRUE----------------------------------------------------------------
# Map topic variable SYSBP and its qualifiers.
vs_sysbp <- vs_sysbp %>%
  # Map VSTEST using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "SYS_BP",
    tgt_var = "VSTEST",
    tgt_val = "Systolic Blood Pressure",
    ct_spec = study_ct,
    ct_clst = "C67153",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRES using assign_no_ct algorithm
  assign_no_ct(
    raw_dat = vs_raw,
    raw_var = "SYS_BP",
    tgt_var = "VSORRES",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRESU using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "SYS_BP",
    tgt_var = "VSORRESU",
    tgt_val = "mmHg",
    ct_spec = study_ct,
    ct_clst = "C66770",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSPOS using assign_ct algorithm
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "SUBPOS",
    tgt_var = "VSPOS",
    ct_spec = study_ct,
    ct_clst = "C71148",
    id_vars = oak_id_vars()
  )

## ----eval=TRUE, echo=FALSE----------------------------------------------------
sdtm.oak:::dataset_oak_vignette(
  vs_sysbp,
  display_vars = exprs(
    oak_id, raw_source, patient_number, VSTESTCD, VSTEST, VSORRES, VSORRESU, VSPOS
  )
)

## ----eval=TRUE----------------------------------------------------------------
# Map topic variable DIABP and its qualifiers.
vs_diabp <-
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "DIA_BP",
    tgt_var = "VSTESTCD",
    tgt_val = "DIABP",
    ct_spec = study_ct,
    ct_clst = "C66741"
  ) %>%
  dplyr::filter(!is.na(.data$VSTESTCD)) %>%
  # Map VSTEST using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "DIA_BP",
    tgt_var = "VSTEST",
    tgt_val = "Diastolic Blood Pressure",
    ct_spec = study_ct,
    ct_clst = "C67153",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRES using assign_no_ct algorithm
  assign_no_ct(
    raw_dat = vs_raw,
    raw_var = "DIA_BP",
    tgt_var = "VSORRES",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRESU using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "DIA_BP",
    tgt_var = "VSORRESU",
    tgt_val = "mmHg",
    ct_spec = study_ct,
    ct_clst = "C66770",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSPOS using assign_ct algorithm
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "SUBPOS",
    tgt_var = "VSPOS",
    ct_spec = study_ct,
    ct_clst = "C71148",
    id_vars = oak_id_vars()
  )

# Map topic variable PULSE and its qualifiers.
vs_pulse <-
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "PULSE",
    tgt_var = "VSTESTCD",
    tgt_val = "PULSE",
    ct_spec = study_ct,
    ct_clst = "C66741"
  ) %>%
  dplyr::filter(!is.na(.data$VSTESTCD)) %>%
  # Map VSTEST using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "PULSE",
    tgt_var = "VSTEST",
    tgt_val = "Pulse Rate",
    ct_spec = study_ct,
    ct_clst = "C67153",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRES using assign_no_ct algorithm
  assign_no_ct(
    raw_dat = vs_raw,
    raw_var = "PULSE",
    tgt_var = "VSORRES",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRESU using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "PULSE",
    tgt_var = "VSORRESU",
    tgt_val = "beats/min",
    ct_spec = study_ct,
    ct_clst = "C66770",
    id_vars = oak_id_vars()
  )

# Map topic variable RESP from the raw variable RESPRT and its qualifiers.
vs_resp <-
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "RESPRT",
    tgt_var = "VSTESTCD",
    tgt_val = "RESP",
    ct_spec = study_ct,
    ct_clst = "C66741"
  ) %>%
  dplyr::filter(!is.na(.data$VSTESTCD)) %>%
  # Map VSTEST using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "RESPRT",
    tgt_var = "VSTEST",
    tgt_val = "Respiratory Rate",
    ct_spec = study_ct,
    ct_clst = "C67153",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRES using assign_no_ct algorithm
  assign_no_ct(
    raw_dat = vs_raw,
    raw_var = "RESPRT",
    tgt_var = "VSORRES",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRESU using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "RESPRT",
    tgt_var = "VSORRESU",
    tgt_val = "breaths/min",
    ct_spec = study_ct,
    ct_clst = "C66770",
    id_vars = oak_id_vars()
  )

# Map topic variable TEMP from raw variable TEMP and its qualifiers.
vs_temp <-
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "TEMP",
    tgt_var = "VSTESTCD",
    tgt_val = "TEMP",
    ct_spec = study_ct,
    ct_clst = "C66741"
  ) %>%
  dplyr::filter(!is.na(.data$VSTESTCD)) %>%
  # Map VSTEST using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "TEMP",
    tgt_var = "VSTEST",
    tgt_val = "Temperature",
    ct_spec = study_ct,
    ct_clst = "C67153",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRES using assign_no_ct algorithm
  assign_no_ct(
    raw_dat = vs_raw,
    raw_var = "TEMP",
    tgt_var = "VSORRES",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRESU using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "TEMP",
    tgt_var = "VSORRESU",
    tgt_val = "C",
    ct_spec = study_ct,
    ct_clst = "C66770",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSLOC from TEMPLOC using assign_ct
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "TEMPLOC",
    tgt_var = "VSLOC",
    ct_spec = study_ct,
    ct_clst = "C74456",
    id_vars = oak_id_vars()
  )

# Map topic variable OXYSAT from raw variable OXY_SAT and its qualifiers.
vs_oxysat <-
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "OXY_SAT",
    tgt_var = "VSTESTCD",
    tgt_val = "OXYSAT",
    ct_spec = study_ct,
    ct_clst = "C66741"
  ) %>%
  dplyr::filter(!is.na(.data$VSTESTCD)) %>%
  # Map VSTEST using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "OXY_SAT",
    tgt_var = "VSTEST",
    tgt_val = "Oxygen Saturation",
    ct_spec = study_ct,
    ct_clst = "C67153",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRES using assign_no_ct algorithm
  assign_no_ct(
    raw_dat = vs_raw,
    raw_var = "OXY_SAT",
    tgt_var = "VSORRES",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSORRESU using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "OXY_SAT",
    tgt_var = "VSORRESU",
    tgt_val = "%",
    ct_spec = study_ct,
    ct_clst = "C66770",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSLAT using assign_ct from raw variable LAT
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "LAT",
    tgt_var = "VSLAT",
    ct_spec = study_ct,
    ct_clst = "C99073",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSLOC using assign_ct from raw variable LOC
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "LOC",
    tgt_var = "VSLOC",
    ct_spec = study_ct,
    ct_clst = "C74456",
    id_vars = oak_id_vars()
  )

# Map topic variable VSALL from raw variable ASMNTDN with the logic if ASMNTDN  == 1 then VSTESTCD = VSALL
vs_vsall <-
  hardcode_ct(
    raw_dat = condition_add(vs_raw, ASMNTDN == 1L),
    raw_var = "ASMNTDN",
    tgt_var = "VSTESTCD",
    tgt_val = "VSALL",
    ct_spec = study_ct,
    ct_clst = "C66741"
  ) %>%
  dplyr::filter(!is.na(.data$VSTESTCD)) %>%
  # Map VSTEST using hardcode_ct algorithm
  hardcode_ct(
    raw_dat = vs_raw,
    raw_var = "ASMNTDN",
    tgt_var = "VSTEST",
    tgt_val = "Vital Signs",
    ct_spec = study_ct,
    ct_clst = "C67153",
    id_vars = oak_id_vars()
  )

## ----eval=TRUE----------------------------------------------------------------
# Combine all the topic variables into a single data frame and map qualifiers
# applicable to all topic variables
vs <- dplyr::bind_rows(
  vs_vsall, vs_sysbp, vs_diabp, vs_pulse, vs_resp,
  vs_temp, vs_oxysat
) %>%
  # Map qualifiers common to all topic variables
  # Map VSDTC using assign_ct algorithm
  assign_datetime(
    raw_dat = vs_raw,
    raw_var = c("VTLD", "VTLTM"),
    tgt_var = "VSDTC",
    raw_fmt = c(list(c("d-m-y", "dd-mmm-yyyy")), "H:M")
  ) %>%
  # Map VSTPT from TMPTC using assign_ct
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "TMPTC",
    tgt_var = "VSTPT",
    ct_spec = study_ct,
    ct_clst = "TPT",
    id_vars = oak_id_vars()
  ) %>%
  # Map VSTPTNUM from TMPTC using assign_ct
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "TMPTC",
    tgt_var = "VSTPTNUM",
    ct_spec = study_ct,
    ct_clst = "TPTNUM",
    id_vars = oak_id_vars()
  ) %>%
  # Map VISIT from INSTANCE using assign_ct
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "INSTANCE",
    tgt_var = "VISIT",
    ct_spec = study_ct,
    ct_clst = "VISIT",
    id_vars = oak_id_vars()
  ) %>%
  # Map VISITNUM from INSTANCE using assign_ct
  assign_ct(
    raw_dat = vs_raw,
    raw_var = "INSTANCE",
    tgt_var = "VISITNUM",
    ct_spec = study_ct,
    ct_clst = "VISITNUM",
    id_vars = oak_id_vars()
  )

## ----eval=TRUE, echo=FALSE----------------------------------------------------
sdtm.oak:::dataset_oak_vignette(
  vs,
  display_vars = exprs(
    oak_id, raw_source, patient_number, VSTESTCD, VSTEST, VSORRES, VSORRESU, VSPOS,
    VSLAT, VSDTC, VSTPT, VSTPTNUM, VISIT, VISITNUM
  )
)

## ----eval=TRUE----------------------------------------------------------------
vs <- vs %>%
  dplyr::mutate(
    STUDYID = "test_study",
    DOMAIN = "VS",
    VSCAT = "VITAL SIGNS",
    USUBJID = paste0("test_study", "-", .data$patient_number)
  ) %>%
  # derive_seq(tgt_var = "VSSEQ",
  #            rec_vars= c("USUBJID", "VSTRT")) %>%
  derive_study_day(
    sdtm_in = .,
    dm_domain = dm,
    tgdt = "VSDTC",
    refdt = "RFXSTDTC",
    study_day_var = "VSDY"
  ) %>%
  dplyr::select("STUDYID", "DOMAIN", "USUBJID", everything())

## ----eval=TRUE, echo=FALSE----------------------------------------------------
sdtm.oak:::dataset_oak_vignette(
  vs,
  display_vars = exprs(
    STUDYID, DOMAIN, USUBJID, VSTESTCD, VSTEST, VSORRES, VSORRESU, VSPOS,
    VSLAT, VSTPT, VSTPTNUM, VISIT, VISITNUM, VSDTC, VSDY
  )
)

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sdtm.oak documentation built on April 3, 2025, 9:37 p.m.