Compute carbon monoxide diffusion capacity or transfer factor reference values for given demographics

pft_diffusion() computes ATS-compliant upper and lower normal limits for carbon monoxide measured diffusion capacity and European equivalents including DLCO (or TLCO), KCO, and VA.

Usage

pft_diffusion(data, SI.units = FALSE, sex = sex, age = age, height = height)

Arguments

data

A data frame containing columns for sex ("M","F"), age (in years, in the range 5-90 per the GLI 2017 spline tables) and height (in centimeters). If data also contains a <measure>_measured column for any of the active measures (tlco, kco_si, va under SI units; dlco, kco_tr, va under traditional), the measured value is used to compute z-score and percent-predicted (see Value).

SI.units

Logical, default FALSE. Selects the unit system for both the reference outputs and any measured inputs (see "Units" below). FALSE (traditional): DLCO in mL/min/mmHg, KCO (kco_tr) in mL/min/mmHg/L, VA in L. TRUE (SI): TLCO in mmol/min/kPa, KCO (kco_si) in mmol/min/kPa/L, VA in L.

sex, age, height

Column references. By default pft_diffusion() reads from sex, age, and height. 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:

• <measure>_pred: predicted (median) value.

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

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

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

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

Units

The caller selects the unit system with SI.units; pft does not infer the unit system from column names or numeric magnitude, and it does not convert measured values between unit systems. Measured diffusion columns must already be in the selected system:

SI.units	Measured columns read	Units
FALSE (default)	dlco_measured, kco_tr_measured, va_measured	mL/min/mmHg, mL/min/mmHg/L, L
TRUE	tlco_measured, kco_si_measured, va_measured	mmol/min/kPa, mmol/min/kPa/L, L

Measured columns belonging to the other unit system are left untouched and do not produce z-scores (for example, a dlco_measured column is ignored when SI.units = TRUE). Supplying values in the wrong units under the right column name (for example, SI values in dlco_measured) cannot be detected and will produce incorrect z-scores and percent-predicted values.

Applicability (source population)

The GLI 2017 source publication describes its TLCO/DLCO reference equations as being for Caucasians: about 85% of the collated data were from Caucasian participants, and the non-Caucasian data were insufficient to derive separate equations (Stanojevic et al. 2017). The race-neutral GLI Global 2022 spirometry equations available in pft_spirometry() do not make these diffusion equations race-neutral or multi-ethnic. Users should consider whether the source reference population is appropriate for the population under study before interpreting outputs. Ages outside the 5-90 year spline range return NA reference values.

References

Stanojevic S, Graham BL, Cooper BG, et al. Official ERS technical standards: Global Lung Function Initiative reference values for the carbon monoxide transfer factor for Caucasians. Eur Respir J. 2017;50(3):1700010. doi:10.1183/13993003.00010-2017 . (Author correction: doi:10.1183/13993003.50010-2017 , applied here.)

See also

pft_spirometry() and pft_volumes() for the analogous reference-value functions. pft_severity() grades DLCO impairment severity from the z-score column produced here. pft_interpret() composes all three reference functions in one call.

Examples

data <- data.frame(sex=c("M","F"),
                   age=c(30,5.1),
                   height=c(178,50))
pft_diffusion(data)
#> # A tibble: 2 × 12
#>   sex     age height dlco_pred dlco_lln dlco_uln kco_tr_pred kco_tr_lln
#>   <chr> <dbl>  <dbl>     <dbl>    <dbl>    <dbl>       <dbl>      <dbl>
#> 1 M      30      178     33.0     26.1     41.0         4.99       3.99
#> 2 F       5.1     50      2.64     1.83     3.69       11.0        7.45
#> # ℹ 4 more variables: kco_tr_uln <dbl>, va_pred <dbl>, va_lln <dbl>,
#> #   va_uln <dbl>