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(V?E) 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 V?E is higher in HYPV and ERBR than in N and FLAT patterns.