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Compute spirometry reference values for given demographics

Source: R/spirometry.R
pft_spirometry.Rd

pft_spirometry() computes ATS-compliant upper and lower normal limits for common spirometry measures including FEV1, FVC, FEV1/FVC, FEF2575, and FEF75.

Usage

pft_spirometry(
  data,
  year = 2022,
  sex = sex,
  age = age,
  height = height,
  race = race
)

Arguments

data

A data frame containing columns for sex ("M","F"), race ("AfrAm","NEAsia","SEAsia","Other/mixed", "Caucasian"), age (in years, in the range 3-95 for FEV1 / FVC / FEV1/FVC and 3-90 for FEF25-75 / FEF75 per the GLI spline tables), and height (in centimeters). Rows with NA in sex, age, or height (or, for GLI 2012, in race) are returned with NA reference values. Race is ignored when year = 2022 (GLI Global equations are race-neutral).

If data also contains any of fev1_measured, fvc_measured, fev1fvc_measured, fef2575_measured, fef75_measured, the corresponding measured value is used to compute a z-score and percent-predicted for that measure (see Value).

year

The year of GLI published equations. Valid options are 2012 (multi-ethnic, requires a race column) and 2022 (race-neutral "GLI Global"; the race column, if present, is ignored). Defaults to 2022, the current ERS/ATS recommendation.

sex, age, height, race

Column references. By default pft_spirometry() reads from sex, age, height, and (for GLI 2012) race. If your data frame names them differently, override via a bare name (sex = Sex), a string (sex = "Sex"), or an rlang injection (sex = !!my_var). The user's original column names are preserved in the output.

Value

The original data frame with extra columns appended for each measure. Every output column carries the GLI year as a suffix so a single result frame can hold multiple equation outputs side-by-side (fev1_pred_2012, fev1_pred_2022, ...).

  • <measure>_pred_<year>: predicted (median) value.

  • <measure>_lln_<year>: lower limit of normal (5th percentile).

  • <measure>_uln_<year>: upper limit of normal (95th percentile). If a <measure>_measured column was supplied in data, two additional columns are emitted:

  • <measure>_zscore_<year>: LMS z-score ((measured/M)^L - 1) / (L*S).

  • <measure>_pctpred_<year>: percent predicted (measured / pred) * 100.

References

Quanjer PH, Stanojevic S, Cole TJ, et al. Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations. Eur Respir J. 2012;40(6):1324-1343. doi:10.1183/09031936.00080312 .

Bowerman C, Bhakta NR, Brazzale D, et al. A race-neutral approach to the interpretation of lung function measurements. Am J Respir Crit Care Med. 2023;207(6):768-774. doi:10.1164/rccm.202205-0963OC .

See also

pft_volumes() and pft_diffusion() for the analogous reference-value functions for lung volumes and diffusion capacity. pft_classify() consumes the LLN columns produced here to assign ATS interpretive patterns. pft_interpret() is the one-call wrapper that combines spirometry, volumes, diffusion, and all downstream interpretation primitives.

Examples

data <- data.frame(sex=c("M","F"),
                   age=c(30.1,5.1),
                   height=c(178,50),
                   race=c("SEAsia","NEAsia"))
pft_spirometry(data)
#> # A tibble: 2 × 13
#>   sex     age height race   fev1_pred_2022 fev1_lln_2022 fev1_uln_2022
#>   <chr> <dbl>  <dbl> <chr>           <dbl>         <dbl>         <dbl>
#> 1 M      30.1    178 SEAsia          4.24          3.29          5.13 
#> 2 F       5.1     50 NEAsia          0.158         0.122         0.192
#> # ℹ 6 more variables: fvc_pred_2022 <dbl>, fvc_lln_2022 <dbl>,
#> #   fvc_uln_2022 <dbl>, fev1fvc_pred_2022 <dbl>, fev1fvc_lln_2022 <dbl>,
#> #   fev1fvc_uln_2022 <dbl>