Manual revision of automated lung function grading results in an increase of accepted data and a relevant change in FEV ₁ and FVC

Background: In population studies, automated portable devices are used to measure lung function on location. A build-in automated quality algorithm selects technically correct lung function data for analysis. Aim: To evaluate the performance of intergraded quality control in lung function testing equipment. Methods: Lung function measurements in 6137 children (age 6 -13) were collected from the HITEA, FRESH and the PIAMA study. All measurements were performed with a portable device, which uses an algorithm based on between-manoeuvre acceptability criteria from the ATS/ERS in an adapted grading system (NDD EasyOne). Data with A, B and C grades are acceptable for data analysis while data with grades D or F are rejected. All tests were manually checked by a certified respiratory function technologist using the same grading system to evaluate decisions made by the algorithm. Furthermore, data from the PIAMA study (n=1530) was used to determine the absolute effect of manual revision on mean FEV 1 and FVC. Results: Manual revision resulted in 2411 adjustments (39%): 374 (16%) to a lower and 1346 (56%) to a higher quality grade. Of all original measurements 21% was rejected by automated quality control. From these, 685 measurements (53%) could be saved for analysis after manual revision. In addition, 110 accepted manoeuvres were rejected (2%) Manuel revision resulted in an absolute change in FEV 1 and FVC of respectively 189 and 240 ml. Conclusion: Manual revision saves a large number of measurements and changes lung function values. Adaptation of the algorithm may improve the performance of automated grading of lung function measurements.