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Creating Severity Records From Diameter

Source: R/derive_diam_to_sev_records.R
derive_diam_to_sev_records.Rd

To derive the severity records from the diameter records.

Usage

derive_diam_to_sev_records(
  dataset,
  filter_add = NULL,
  diam_code = "DIAMETER",
  faobj_values = c("REDNESS", "SWELLING"),
  testcd_sev = "SEV",
  test_sev = "Severity/Intensity",
  none = 0,
  mild = 2,
  mod = 5,
  sev = 10
)

Arguments

dataset

Input data set

The variables USUBJID,FAOBJ,AVAL, AVALC, FATESTCD and FATEST are expected for Input data set.

filter_add

filter for the dataset.

diam_code

Diameter record filter

Permitted Value: A character vector or scalar.

Helps to filter the diameter records to derive the severity records by passing the FATESTCD value for diameter which is corresponding to the specified events in faobj_values.

faobj_values

Event filter

Permitted Value: A character vector or Scalar.

Helps to filter the events (Redness and Swelling) which has diameter records to derive severity records by passing the events from FAOBJ.

testcd_sev

To assign FATESTCD value for severity

Permitted Value: A character scalar

Assign the value for FATESTCD variable to indicate the severity records. Ignore the argument if you want to set the default value (SEV).

test_sev

FATEST Value for severity

Permitted Value: A Character scalar

Assign the value for FATEST variable to indicate the severity records. Ignore the argument if you want to set the default value.

none

Pass the lower limit for grade "NONE"

Permitted Value: A numeric vector

The none and the following arguments (mild, mode and sev) will be used for assigning the diameter limit to derive the AVALC (severity grade).

Assign the lower limit to derive the Severity Grade (AVALC).
For Example: User passing 0 to none and 2 to mild, 0 will act as lower limit and 2 will act as upper limit.

Note: Use the limit reference to pass the values to these arguments
Since the condition was coded like this,
NONE : none < AVAL <= mild
MILD : mild < AVAL <= mod
MODERATE : mod < AVAL <= sev
SEVERE : sev < AVAL
User should pass the values as numeric scalar. Refer the default values.

mild

Pass the lower limit for grade "MILD"

Permitted Value: A numeric vector

mod

Pass the lower limit for grade "MODERATE"

Permitted Value: A numeric vector

sev

Pass the lower limit for grade "SEVERE"

Permitted Value: A numeric vector

Value

The Input data with the new severity records for Redness and swelling which is specified in faobj_values and AVAL, AVALC will be derived and FATESTCD, FATEST will be changed as per the values.

Note

Basically, This function will derive and create the severity records from the diameter record for the particular events specified in the faobj_values that user wants. If you want to derive the Severity from diameter, even though you have the severity in SDTM data. This function will re-derive the severity and remove the derived SDTM severity records.

See also

Other der_rec: derive_fever_records()

Author

Arjun Rubalingam

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(admiral)
library(tibble)

input <- tribble(
  ~USUBJID, ~FAOBJ, ~AVAL, ~AVALC, ~ATPTREF, ~FATEST, ~FATESTCD,
  "XYZ1001", "REDNESS", 7.5, "7.5", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "REDNESS", 3.5, "3.5", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "REDNESS", 2, "2", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "REDNESS", 1.8, "1.8", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "REDNESS", 1.4, "1.4", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1002", "REDNESS", 11.1, "11.1", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "REDNESS", 7.4, "7.4", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "REDNESS", 6, "6", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "REDNESS", 2.1, "2.1", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "REDNESS", 1.1, "1.1", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1001", "SWELLING", 5.5, "5.5", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "SWELLING", 2.5, "2.5", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "SWELLING", 2, "2", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "SWELLING", 1.8, "1.8", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1001", "SWELLING", 1.4, "1.4", "VACCINATION 1", "Diameter", "DIAMETER",
  "XYZ1002", "SWELLING", 10.1, "10.1", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "SWELLING", 7.1, "7.1", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "SWELLING", 5, "5", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "SWELLING", 1.8, "1.8", "VACCINATION 2", "Diameter", "DIAMETER",
  "XYZ1002", "SWELLING", 1.4, "1.4", "VACCINATION 2", "Diameter", "DIAMETER"
)

derive_diam_to_sev_records(
  dataset = input,
  faobj_values = c("REDNESS", "SWELLING"),
  diam_code = "DIAMETER",
  testcd_sev = "SEV",
  test_sev = "Severity"
)
#> # A tibble: 40 × 8
#>    USUBJID FAOBJ    AVAL AVALC    ATPTREF       FATEST   FATESTCD FASEQ
#>    <chr>   <chr>   <dbl> <chr>    <chr>         <chr>    <chr>    <int>
#>  1 XYZ1001 REDNESS     2 MODERATE VACCINATION 1 Severity SEV         NA
#>  2 XYZ1001 REDNESS     1 MILD     VACCINATION 1 Severity SEV         NA
#>  3 XYZ1001 REDNESS     0 NONE     VACCINATION 1 Severity SEV         NA
#>  4 XYZ1001 REDNESS     0 NONE     VACCINATION 1 Severity SEV         NA
#>  5 XYZ1001 REDNESS     0 NONE     VACCINATION 1 Severity SEV         NA
#>  6 XYZ1002 REDNESS     3 SEVERE   VACCINATION 2 Severity SEV         NA
#>  7 XYZ1002 REDNESS     2 MODERATE VACCINATION 2 Severity SEV         NA
#>  8 XYZ1002 REDNESS     2 MODERATE VACCINATION 2 Severity SEV         NA
#>  9 XYZ1002 REDNESS     1 MILD     VACCINATION 2 Severity SEV         NA
#> 10 XYZ1002 REDNESS     0 NONE     VACCINATION 2 Severity SEV         NA
#> # ℹ 30 more rows