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Bronchodilator response per the ERS/ATS 2022 criterion

Source: R/interpretation.R
pft_bdr.Rd

Classifies bronchodilator response (BDR) by the percent change in the measured value relative to the patient's predicted value, as recommended by Stanojevic et al. ERJ 2022. Significant BDR is defined as a post-bronchodilator increase of more than 10% of the predicted value in either FEV1 or FVC. This replaces the 2005 standard, which used a >=12% AND >=200 mL change from baseline.

Usage

pft_bdr(pre, post, predicted, threshold = BDR_THRESHOLD_PCT_PRED)

Arguments

pre

Numeric vector of baseline measurements obtained before bronchodilator administration.

post

Numeric vector of the corresponding measurements obtained after bronchodilator administration, in the same units and of the same length as pre.

predicted

Numeric vector of predicted (median) values for the same measure and units, typically the <measure>_pred_<year> column from a previous call to pft_spirometry().

threshold

Percent-of-predicted change considered significant. Defaults to 10 (the Stanojevic 2022 criterion).

Value

A data frame with one row per input observation and columns:

  • pct_pred_change: (post - pre) / predicted * 100.

  • is_significant: logical, TRUE when pct_pred_change > threshold. NA is propagated wherever any of pre, post, predicted is NA.

Pre- and post-bronchodilator values

pre is the baseline measurement obtained before bronchodilator administration; post is the corresponding measurement obtained after bronchodilator administration under the laboratory's testing protocol. Each pre/post pair must refer to the same physiologic measure in the same units and belong to the same paired assessment. The caller identifies which values are pre and post; pft does not infer test phase from timestamps, values, medication records, or curve shape, and it interprets the supplied labels literally.

Column naming

This function's pct_pred_change column is percent-of-predicted change (the 2022 criterion). The predecessor pft_bdr_2005() emits a similarly-named but different column, pct_change, which is percent-of-baseline change ((post - pre) / pre * 100, the 2005 criterion). The two functions deliberately use distinct column names so a result frame can carry both without ambiguity.

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 . See the "Bronchodilator responsiveness testing" section.

See also

pft_spirometry() to obtain the predicted FEV1 / FVC values used as the denominator. pft_interpret() runs BDR automatically when <measure>_pre and <measure>_post columns are present.

Examples

pft_bdr(pre = 2.5, post = 3.0, predicted = 4.0)
#> # A tibble: 1 × 2
#>   pct_pred_change is_significant
#>             <dbl> <lgl>         
#> 1            12.5 TRUE          
# -> 12.5% of predicted change, is_significant = TRUE