Cornelis J, Denis T, Beckers P, Vrints C, Vissers D, Goossens M
Int J Cardiol. 2017 Aug 1;240:291-296. doi: 10.1016/j.ijcard.2016.12.159. Epub
2016 Dec 29.
BACKGROUND: Cardiopulmonary exercise testing (CPET) gained importance in the
prognostic assessment of especially patients with heart failure (HF). A
meaningful prognostic parameter for early mortality in HF is exercise oscillatory
ventilation (EOV). This abnormal respiratory pattern is recognized by hypo- and
hyperventilation during CPET. Up until now, assessment of EOV is mainly done upon
visual agreement or manual calculation. The purpose of this research was to
automate the interpretation of EOV so this prognostic parameter could be readily
investigated during CPET.
METHODS AND RESULTS: Preliminary, four definitions describing the original
characteristics of EOV, were selected and integrated in the “Ventilatory
Oscillations during Exercise-tool” (VOdEX-tool), a graphical user interface that
allows automate calculation of EOV. A Discrete Meyer Level 2 wavelet
transformation appeared to be the optimal filter to apply on the collected
breath-by-breath minute ventilation CPET data. Divers aspects of the definitions
i.e. cycle length, amplitude, regularity and total duration of EOV were combined
and calculated. The oscillations meeting the criteria were visualised. Filter
methods and cut-off criteria were made adjustable for clinical application and
research. The VOdEX-tool was connected to a database.
CONCLUSIONS: The VOdEX-tool provides the possibility to calculate EOV
automatically and to present the clinician an overview of the presence of EOV at
a glance. The computerized analysis of EOV can be made readily available in
clinical practice by integrating the tool in the manufactures existing CPET
software. The VOdEX-tool enhances assessment of EOV and therefore contributes to
the estimation of prognosis in especially patients with HF.