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Background: Technologists must assure the accuracy and precision of pulmonary function equipment prior to testing patients. This study aimed to identify the sources of failure and unacceptable submission rates for spirometry volume linearity and syringe diffusing capacity of the lung for carbon monoxide (D LCO ) check quality control (QC). In addition, we explored whether the time between training and first QC submission affected overall percentage of unacceptable submissions. Methods: Participants in a cross-sectional global study submitted QC for evaluation from October 2014 to May 2018 from 114 laboratories. Descriptive statistics summarized the percentage of unacceptable submissions and sources of failure for volume linearity and syringe D LCO check maneuvers. Spearman’s rho described the correlation between site-specific unacceptable submission rates, and both days between training and the first unacceptable submission and the days between training and first submission. Results: The unacceptable submission rate from 5,083 volume linearity assessments was 10% compared with a 6.2% rate from 4,992 syringe D LCO check maneuvers. Aggregate volume linearity rates of procedural errors (5.8%) and equipment errors (6.2%) were similar, whereas there were more syringe D LCO check equipment errors (5.9%) than procedural errors (0.78%). The time between training and submitting a QC test was not related to overall unacceptable submission rates for volume linearity and syringe D LCO check, r sp = 0.11, P = .27 and r sp = 0.19, P = .052, respectively. Higher unacceptable rates occurred when the first QC failure occurred close to the completion of training for volume linearity and syringe D LCO check, r sp = −0.41, P < .001 and r sp = −0.38, P < .001, respectively. Conclusions: A single QC training session does not adequately prepare technologists to conduct QC. Technologists need clear and consistent guidelines for conducting QC procedures and regular follow-up from experts to properly interpret QC findings, resolve equipment problems, and assure their testing systems are in-control.
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Becker et al. (2025) studied this question.
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