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Screen for Preserved Ratio Impaired Spirometry (PRISm)

Source: R/interpretation.R
pft_prism.Rd

PRISm is the spirometry-only manifestation of the "non-specific" pattern when TLC is not available: a low FEV1, a low FVC, and a preserved (normal) FEV1/FVC ratio. The 2022 ERS/ATS interpretation standard (Stanojevic et al.) classifies it in Table 5 with row "Non-specific pattern" (FEV1 reduced, FVC reduced, FEV1/FVC normal).

Typically called via pft_interpret() as part of the one-call workflow; exported for callers who want to apply the screen to pre-computed columns directly.

This function adds a prism logical column to the data frame. PRISm is a spirometry-only screen and does not require a TLC measurement.

Usage

pft_prism(
  data,
  year = 2022,
  fev1 = fev1,
  fev1_lln = NULL,
  fvc = fvc,
  fvc_lln = NULL,
  fev1fvc = fev1fvc,
  fev1fvc_lln = NULL
)

Arguments

data

A data frame containing the six input columns named below.

year

GLI year suffix used when looking up the LLN columns (fev1_lln, fvc_lln, fev1fvc_lln). Defaults to 2022. Set to match the year argument used in the upstream pft_spirometry() / pft_interpret() call.

fev1, fev1_lln, fvc, fvc_lln, fev1fvc, fev1fvc_lln

Column references for the six required columns. Defaults are the canonical names (fev1, fev1_lln_<year>, ...); override with a bare name, a string, or !!var (see "Column-name overrides" below).

Value

The original data frame with a prism logical column appended. NA propagates from any of the six input columns.

Column-name overrides

Each column-reference argument accepts three forms:

  • a bare column name – fev1 = my_fev1

  • a string – fev1 = "my_fev1"

  • an injected value – fev1 = !!my_var where my_var <- "my_fev1"

Defaults are the canonical pft column names, so callers whose data already follows the convention pass no extra arguments.

References

Stanojevic S, Kaminsky DA, Miller MR, et al. ERS/ATS technical standard on interpretive strategies for routine lung function tests. Eur Respir J. 2022;60(1):2101499. doi:10.1183/13993003.01499-2021 . PRISm appears in Table 5 as the spirometry-only form of the non-specific pattern.

See also

pft_classify() for the full ATS pattern classification when TLC is available; pft_interpret() runs both PRISm and full classification automatically when the relevant columns are present.

Examples

d <- data.frame(fev1    = 2.0, fev1_lln_2022    = 2.5,
                fvc     = 2.6, fvc_lln_2022     = 3.0,
                fev1fvc = 0.80, fev1fvc_lln_2022 = 0.70)
pft_prism(d)
#> # A tibble: 1 × 7
#>    fev1 fev1_lln_2022   fvc fvc_lln_2022 fev1fvc fev1fvc_lln_2022 prism
#>   <dbl>         <dbl> <dbl>        <dbl>   <dbl>            <dbl> <lgl>
#> 1     2           2.5   2.6            3     0.8              0.7 TRUE 

# Column-name override: data using non-canonical names.
d2 <- data.frame(my_fev1 = 2.0, my_fev1_lln = 2.5,
                 fvc = 2.6, fvc_lln_2022 = 3.0,
                 fev1fvc = 0.80, fev1fvc_lln_2022 = 0.70)
pft_prism(d2, fev1 = my_fev1, fev1_lln = my_fev1_lln)
#> # A tibble: 1 × 7
#>   my_fev1 my_fev1_lln   fvc fvc_lln_2022 fev1fvc fev1fvc_lln_2022 prism
#>     <dbl>       <dbl> <dbl>        <dbl>   <dbl>            <dbl> <lgl>
#> 1       2         2.5   2.6            3     0.8              0.7 TRUE