Description of three dysfunctional breathing patterns in post-COVID dyspnea

Area of Science:

• Pulmonary Medicine
• Cardiorespiratory Physiology

Background:

• Dysfunctional breathing (DB) presents with respiratory and systemic symptoms, often contributing to dyspnea in post-COVID-19 syndrome (PCS).
• Current diagnostic challenges stem from the lack of standardized classification for DB subtypes.
• Cardiopulmonary exercise testing (CPET) shows potential for analyzing breathing patterns in PCS patients.

Purpose of the Study:

• To investigate the utility of CPET in classifying DB into distinct patterns.
• To identify specific ventilatory parameter changes associated with different DB subtypes.

Main Methods:

• Analysis of 79 CPETs from patients with persistent respiratory symptoms post-COVID-19.
• Classification of patients into three DB patterns: hyperventilation (HYPV), erratic breathing (ERBR), and flattening (FLAT), based on abnormal breathing patterns during CPET.

Main Results:

• No significant differences in age, BMI, gender, or peak oxygen uptake (V̇O2) between patterns.
• HYPV and FLAT showed a higher V̇E-V̇CO2 slope compared to normal (N).
• FLAT and ERBR exhibited a lower VT/V̇E slope; FLAT also had higher peak breathing frequency. ERBR and FLAT were linked to elevated symptom scores.

Conclusions:

• Ventilatory parameter evolution during incremental exercise effectively classifies DB into HYPV, ERBR, and FLAT patterns.
• This classification approach offers a standardized method for diagnosing and managing DB in PCS.
• CPET-derived breathing pattern analysis is a valuable tool for understanding and addressing DB.