Description of breathing pattern disorder using sample entropy index in post-COVID19 dyspnoea

Ivan Guerreiro; Aurélien Bringard; Pascal Weber; Viva Leverington; Anna Taboni; Frédéric Lador

doi:10.1183/13993003.congress-2023.PA4632

Abstract

Introduction: Breathing pattern disorder (BPD) has been described in post-COVID19. Precise description between the different patterns has still to be defined. Ventilatory variability quantified by sample entropy index (SampEN) has been proposed to detect BPD during cardiopulmonary exercise test (CPET).

Aim: To evaluate breathing patterns in post-COVID19 dyspnoea using SampEN.

Method: We retrospectively analysed CPET data realized between July 2020 and May 2022 in patients with post-COVID19 dyspnoea. Ventilatory patterns were distributed as “normal”(N), “hyperventilation”(HYPV), “erratic breathing”(ERBR) or “flattening”(FLAT) pattern based on the current literature(Figure 1). Higher values of SampEN signifying greater unpredictability and lower values a greater regularity in ventilation.

Results: 79 consecutive patients were recruited. Compared to N, SampEN(Table 1) was significantly higher for tidal volume(Vt) in HYPV (p = 0.0038) and for the ventilation(V̇E) in HYPV (p<0.0001) and ERBR (p=0.0224).

Conclusion: SampEN could be a useful tool to better characterize BPD in post-COVID19. SampEN for Vt and V̇E is higher in HYPV and ERBR than in N and FLAT patterns.

Footnotes

Cite this article as: European Respiratory Journal 2023; 62: Suppl. 67, PA4632.

This abstract was presented at the 2023 ERS International Congress, in session “Inflammatory endotyping: the macrophage across disease areas”.

This is an ERS International Congress abstract. No full-text version is available. Further material to accompany this abstract may be available at www.ers-education.org (ERS member access only).