Introduction: Dysfunctional breathing (DB) can be defined as a change in breathing pattern associated with respiratory and/or systemic symptoms, after ruling out underlying respiratory or cardiac disease. Recent evidence suggests that DB contributes to dyspnea in post-COVID-19 syndrome (PCS), as demonstrated by ventilation analysis during cardiopulmonary exercise testing (CPET). Nevertheless, the lack of a standardized classification for the different subtypes of DB poses challenges for accurate diagnosis and effective management. We hypothesized that analyzing the evolution of breathing parameters during CPET may help classify DB into three patterns. Methods: We analyzed 79 CPETs performed between July 2020 and May 2022 on patients with persistent respiratory symptoms at least three months after COVID-19 infection. We classified patients into three different categories based on abnormal breathing patterns: hyperventilation (HYPV), erratic breathing (ERBR), and flattening (FLAT). Results: Age, BMI, gender and peak O2 uptake (V̇O2) were similar between patterns. Compared to normal pattern (N), we found higher V̇E – V̇CO2 slope in HYPV and FLAT, and a lower VT/ V̇E slope in FLAT and ERBR. The FLAT pattern was also characterized by a higher breathing frequency at peak exercise compared to the other patterns. ERBR and FLAT were associated with higher symptom scores (Nijmegen Questionnaire and Dyspnea-12) compared to N. Conclusion: Analyzing the evolution of ventilatory parameters during incremental exercise enables the classification of dysfunctional breathing into three distinct breathing patterns: hyperventilation, erratic breathing, and flattening.
Description of three dysfunctional breathing patterns in post-COVID dyspnea
Taboni, Anna;
2026-01-01
Abstract
Introduction: Dysfunctional breathing (DB) can be defined as a change in breathing pattern associated with respiratory and/or systemic symptoms, after ruling out underlying respiratory or cardiac disease. Recent evidence suggests that DB contributes to dyspnea in post-COVID-19 syndrome (PCS), as demonstrated by ventilation analysis during cardiopulmonary exercise testing (CPET). Nevertheless, the lack of a standardized classification for the different subtypes of DB poses challenges for accurate diagnosis and effective management. We hypothesized that analyzing the evolution of breathing parameters during CPET may help classify DB into three patterns. Methods: We analyzed 79 CPETs performed between July 2020 and May 2022 on patients with persistent respiratory symptoms at least three months after COVID-19 infection. We classified patients into three different categories based on abnormal breathing patterns: hyperventilation (HYPV), erratic breathing (ERBR), and flattening (FLAT). Results: Age, BMI, gender and peak O2 uptake (V̇O2) were similar between patterns. Compared to normal pattern (N), we found higher V̇E – V̇CO2 slope in HYPV and FLAT, and a lower VT/ V̇E slope in FLAT and ERBR. The FLAT pattern was also characterized by a higher breathing frequency at peak exercise compared to the other patterns. ERBR and FLAT were associated with higher symptom scores (Nijmegen Questionnaire and Dyspnea-12) compared to N. Conclusion: Analyzing the evolution of ventilatory parameters during incremental exercise enables the classification of dysfunctional breathing into three distinct breathing patterns: hyperventilation, erratic breathing, and flattening.| File | Dimensione | Formato | |
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