Abstract
ERS/ATS DLCO standards recommend acceptability ranges for weekly DLCO simulation testing performed with a 3-L syringe. On some devices, the ERS/ATS limits may exceed or not fit a 3-sd range, in which case, simulation ranges based on 3 sd may be appropriate. https://bit.ly/3Z0YoZL
To the Editor:
Diffusing capacity of the lungs for carbon monoxide (DLCO) is an important pulmonary function test for the diagnosis and management of obstructive, restrictive and pulmonary vascular disease. The 2017 European Respiratory Society (ERS)/American Thoracic Society (ATS) standards for single-breath carbon monoxide uptake in the lungs recommend that a weekly DLCO simulation test be performed with a calibrated 3-L syringe [1]. This type of simulation provides quality control values for both DLCO and alveolar volume (VA). According to ERS/ATS standards, an acceptable simulated DLCO is <0.5 mL·min−1·mmHg−1 and an acceptable simulated VA is 3±0.3 L, under ambient temperature, pressure, dry (ATPD) conditions [1]. The ERS/ATS DLCO standards document states that the simulated VA should be reported under BTPS (body temperature, pressure, saturated) conditions; however, in this type of simulation, volumes should be reported under ATPD conditions.
We previously reported a case from a single system where the simulated VA was 8–11 standard deviations above the measured mean due to a leak in a gas sampling collection bag, yet all of these values were within the ERS/ATS limits of acceptability [1, 2]. We suggested that DLCO and VA simulation limits based on actual performance rather than fixed arbitrary values may provide better quality control of DLCO devices. The purpose of this study was to analyse DLCO and VA simulation data from multiple devices and laboratories, and compare the performance of these devices against the ERS/ATS recommended simulation limits.
We analysed DLCO and VA simulation data collected from three different types of DLCO systems: Medisoft BodyBox (three devices) and SpiroAir (one device) (Sorinnes, Belgium) (ComPAS software; Morgan Scientific, Haverhill, MA, USA), and Platinum Elite (nine devices) (MGC Diagnostics Corporation, St Paul, MN, USA). The Medisoft devices are classical systems that use plastic bags for the collection of discrete gas samples (referred to as “expiratory bag” in this letter), whereas the MGC devices were equipped with either a rapid gas analyser (RGA) (six devices) or gas chromatograph (GC) (three devices). Data were collected from four clinical laboratories (St Louis University, St Louis, MO, USA; University of Vermont, Burlington, VT, USA; Elliot Health System, Manchester, NH, USA; and St Joseph Hospital, Nashua, NH, USA). Data were collected between 2017 and 2021.
DLCO and VA simulations were performed with a 3-L calibration syringe with a current accuracy certification according to each laboratory's protocol. The Medisoft/Morgan Scientific devices perform the DLCO simulation with a full syringe of test gas in patient testing mode while the MGC devices perform the DLCO simulation with 1 L air mixed with 2 L test gas in a simulation test mode. Consecutive measurements performed on different days were retrospectively collected from each device. DLCO or VA simulation values identified as statistical outliers that would likely prompt corrective action were excluded. Data from each type of device were compared to the 2017 ERS/ATS limits [1] and then to each other. Following individual comparisons, the data from all devices were pooled and compared to the 2017 ERS/ATS limits [1]. The use of 3-sd limits (common in laboratory medicine) [3] were considered in comparison to the fixed limits as recommended by the ERS/ATS standards.
Commercially available software was used to perform statistical analysis (Prism, version 4.0; GraphPad Software, San Diego, CA, USA). Grubb's test was applied to identify statistical outliers. Mean and standard deviation were calculated for each type of device, differences between device types was assessed with the Kruskal–Wallis (one-way ANOVA) test and Dunn's multiple comparison post-test if necessary. A p-value <0.05 was considered significant.
A total of four DLCO measurements (two expiratory bags and two GCs) and five VA measurements (one expiratory bag, two RGAs and two GCs) were removed from analysis after being identified as outliers. Following outlier removal, 1157 DLCO (expiratory bag, n=286; RGA, n=707; GC, n=164) and 1158 VA (expiratory bag, n=287; RGA, n=706; GC, n=165) simulation tests were analysed. The mean DLCO and VA values from different devices and when pooled collectively were within the ERS/ATS simulation limits (figure 1). The left panels of the figure shows the pooled DLCO and VA simulation data in comparison to the ERS/ATS limits. There were some differences between devices. If a 3-sd range is used, the high end of the DLCO range marginally exceeds the ERS/ATS limit (<0.5 mL·min−1·mmHg−1) for the expiratory bag (0.58 mL·min−1·mmHg−1), RGA (0.81 mL·min−1·mmHg−1) and for the pooled data (0.75 mL·min−1·mmHg−1).
The left panels shows pooled diffusing capacity of the lung for carbon monoxide (DLCO) and alveolar volume (VA) simulation data from multiple devices and laboratories compared to European Respiratory Society (ERS)/American Thoracic Society (ATS) acceptability ranges. The right panels show box-and-whisker plots of DLCO and VA simulation data from different devices assessed with the Kruskal–Wallis (one-way ANOVA) test and Dunn's multiple comparison post-test. The red lines in the right panels represent the measured 3 standard deviation range. The solid lines in the lower panels represent the VA simulation target and the dashed lines in all panels represent the ERS/ATS acceptability ranges. ATPD: gas conditions at atmospheric temperature, pressure, dry; Exp bag: expiratory bag; RGA: rapid gas analyser; GC: gas chromatograph.
The measured 3-sd VA range for the RGA, GC and pooled data matched the ERS/ATS-recommended variance of ±0.3 L, and were 10.4%, 10.3% and 10.3% of the mean, respectively. However, the 3-sd VA range for the RGA, GC and pooled data were offset below the ERS/ATS fixed range (3±0.3 L) because the mean VA for these devices were <3 L: 2.89, 2.92 and 2.91 L, respectively.
The measured 3-sd range for the expiratory bag devices (±0.15 L, 5% of the mean 2.98 L) was tighter than the ERS/ATS range. Using the ERS/ATS VA range for these devices would create acceptability boundaries of −5.6 and +6.4 sd from the measured mean. Using a ±3-sd range may be more appropriate than the fixed ERS/ATS VA range for devices with less variance.
Comparison of DLCO and VA simulation data between device types revealed statistically significant differences between all device types (figure 1, right panels). While it is unclear if these differences are clinically important, they may be important with regards to establishing acceptable ranges for VA simulation.
Our data support the limits of acceptability for DLCO simulation (<0.5 mL·min−1·mmHg−1) as recommended by the ERS/ATS DLCO standards. However, a potential limitation of this recommendation is that there is no consideration of limits on negative DLCO values which may indicate gas analyser malfunction. Indeed, all four DLCO outliers that were removed from this study were negative values (expiratory bag: −0.32, −0.32; GC: −0.34, −0.30) but satisfy the ERS/ATS single-sided limit of <0.5 mL·min−1·mmHg−1. While a VA range of ±0.3 L perfectly fit the 3-sd range for the RGA, GC and pooled data, the mean VA were <3 L, resulting in an offset of the 3-sd range from the ERS/ATS range. However, the 3-sd VA range from the expiratory bag devices were significantly tighter than the ERS/ATS recommended ranges.
It is possible that a methodological difference might be responsible for the varying results between devices. For example, the expiratory bag devices performed the DLCO simulation with a full syringe of test gas in patient testing mode while the RGA and GC devices used in this study performed the DLCO simulation with 1 L air mixed with 2 L test gas in a simulation test mode. Factors that might cause the simulated VA to be <3 L include the volume of dead space correction applied to either the syringe or the DLCO system, as well as the mechanism supplying the inspired gas (e.g. reservoir bag or demand valve). Manufacturers must perform these simulations on their equipment and provide guidance for their customers to achieve ERS/ATS-compliant simulation data.
Performing a DLCO simulation test weekly, or whenever a problem is suspected, provides a quick means for troubleshooting a complex system. Any simulation data outside of the acceptability limits should prompt users to take the system out of service until the problem can be resolved. This requires that the acceptability limits accurately represent the performance of the DLCO system under normal operating conditions. Subtle DLCO system malfunctions may escape detection by calibration procedures so failure to perform weekly DLCO simulation and biological control testing risks reporting inaccurate patient data. Because DLCO thresholds are used in many clinical scenarios, inaccurate data may have serious consequences for patients [4, 5].
Our data, collected from 13 devices and four clinical laboratories under real-world conditions, indicate that the ERS/ATS acceptability limits for DLCO simulation are appropriate. However, a limit on negative values should be added. For many of the devices we examined, the absolute VA ranges fit the ERS/ATS recommendation but were offset below 3±0.3 L because the mean VA was offset below 3 L. Unfortunately, our study was limited to a few devices; additional research on other DLCO systems and the cause of the mean VA offset is needed. Manufacturers must ensure that their systems produce simulation data that fit the ERS/ATS targets. A VA range ±3 sd may be more appropriate for devices with a measured range tighter than ±0.3 L. Based on the data presented, we suggest that future ERS/ATS DLCO technical standards recommend a DLCO target that accounts for negative values and a VA target of 3±0.3 L or ±3 sd, whichever is smaller.
Acknowledgements
The authors would like to thank Kevin Hodgdon (Department of Respiratory Care, University of Vermont Medical Center, Burlington, VT, USA), Vanessa Gall (Pulmonary Function Laboratory, St Louis University Hospital, St Louis, MO, USA) and Teresa Goodwin (Pulmonary Function Laboratory, St Joseph Hospital, Nashua, NH, USA) for assisting with data collection.
Footnotes
Provenance: Submitted article, peer reviewed.
Conflict of interest: J.M. Haynes has received consulting fees from Morgan Scientific, Inc., outside the submitted work; honoraria from the American Association for Respiratory Care, Respiratory Care Society of Washington State, Pennsylvania Society for Respiratory Care and Ohio Respiratory Care Society, outside the submitted work; and support for attending meetings and/or travel from the American Association for Respiratory Care and National Board for Respiratory Care, outside the submitted work; and is a Trustee for the National Board for Respiratory Care, outside the submitted work.
Conflict of interest: G.L. Ruppel has received consulting fees from the National Board for Respiratory Care, outside the submitted work; and speaker fees or honoraria from MGC Diagnostics, outside the submitted work.
Conflict of interest: D.A. Kaminsky has received royalties from UptoDate, Inc., outside the submitted work; and speaker honoraria from MGC Diagnostics, Inc., outside the submitted work.
- Received November 17, 2022.
- Accepted December 17, 2022.
- Copyright ©The authors 2023
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