CORRESPONDING AUTHOR
Professor Paul D Robinson
The Children’s Hospital at Westmead
The Sydney Children’s Hospital Network
Respiratory Medicine Department
Cnr Hawkesbury Road and Hainsworth Street
Locked Bag 4001, Westmead 2145, NSW Australia
t: (02) 9845 3395/97 | f: (02) 9845 3396 | e:
dr.pdrobinson@gmail.com
To the Editor,
The recent identification of a sensor crosstalk (XT) error in the
Exhalyser D MBW device1 led to the release of new
software (3.3.1). Understanding impacts of transition between
MBWN2 software updates, and how to best handle
historical data, is critical2. Should users simply
migrate legacy data, by uploading into the new software version to
enable XT correction (XTC), or perform a more time-consuming reload of
raw data A‐files to apply all advances between that and
historical software versions (3.1.6): XTC, O2 drift
correction and novel gas signal flow synchronisation methodology
(dynamic delay correction, DDC)? What are the differences and which
approach most accurately reflects MBWN2 Lung Clearance
Index (LCI) values collected within 3.3.1?
This issue has been investigated to varying degrees across three studies
published in 2022. Two studies have drawn differing conclusions
comparing agreement between migration and reloading. Oestreich et
al3 (n=44, healthy and Cystic Fibrosis, CF) reported a
mean (95% CI) LCI difference of −0.16 (−0.27 to −0.04) turnovers (TO)
or −1.3%, with an observed magnitude-dependent bias, which they felt
supported a recommendation to reload data (and not migrate). Jensen et
al.4, in a reply to that letter, “respectfully
disagreed”. In their independent analysis of a separate, similarly
sized cohort, in which they attempted to isolate the impact of XTC on
3.1.6 data, mean (95% CI) difference between migration and reload was
−0.10 (−0.26, 0.06), or -1%, was not statistically significant, without
a magnitude-dependent bias when correctly expressed as relative
difference.
In the next study to be published, by Short et al, this discussion was
extended by introducing direct comparison to 3.3.1 collected
data. Subjects (n=19, healthy and CF) performed ≥2 technically
acceptable trials on both 3.1.6 and 3.3.1 in a fixed order (mandated by
study protocol). They confirmed the non-significant difference between
migrated and reloaded data reported by Jensen, but also showed a large
difference between collected 3.3.1 data and 3.1.6-collected data
‘corrected’ via either migration or reloading into 3.3.1: mean absolute
difference 0.5-0.8, relative difference 7.2-8.5%. The authors felt
these differences raised concerns about ‘corrected’ 3.1.6 data being
used by the current GLI normative values project to derive reference
equations applicable for 3.3.1, and proposed that, ideally, only data
collected in 3.3.1 should be included. This conclusion would have
significant implications on the available data to derive these
equations.
Here we present results from an independent Australian dataset that the
3 CORCs have scrutinised and agree offers methodological improvements to
help maximise the utility of legacy data. In this study, performed under
local ethics approval (2021/ETH11854), recruited participants performed
≥2 technically acceptable trials in both 3.1.6 and 3.3.1, in a
randomised order, on a single Exhalyser D device at a single visit.
3.1.6 data were both migrated and reloaded in 3.3.1 to generate
‘corrected’ LCI values to compare to data collected directly on version
3.3.1. Aspects of processing within 3.3.1 were identical for reloaded
and 3.3.1 collected data, as done by Short et al, but with the addition
of consistent O2 and CO2 sensor offset
values. The latter was not performed in the study by Short et al where
instead, software and equipment specific offsets were used to produce
effective synchronisation (assessed visually) during the washout phase.