{"title":"Description of three dysfunctional breathing patterns in post-COVID dyspnea","authors":"Ivan Guerreiro , Aurélien Bringard , Pascal Weber , Viva Leverington , Aileen Kharat , Léon Genecand , Anna Taboni , Frédéric Lador","doi":"10.1016/j.resp.2026.104543","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><div>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.</div></div><div><h3>Methods</h3><div>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).</div></div><div><h3>Results</h3><div>Age, BMI, gender and peak O<sub>2</sub> uptake (V̇O<sub>2</sub>) were similar between patterns. Compared to normal pattern (N), we found higher V̇<sub>E</sub> – V̇CO<sub>2</sub> slope in HYPV and FLAT, and a lower VT/ V̇<sub>E</sub> 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.</div></div><div><h3>Conclusion</h3><div>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.</div></div>","PeriodicalId":20961,"journal":{"name":"Respiratory Physiology & Neurobiology","volume":"341 ","pages":"Article 104543"},"PeriodicalIF":1.9000,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Respiratory Physiology & Neurobiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569904826000029","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/1/8 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"PHYSIOLOGY","Score":null,"Total":0}
引用次数: 0
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.
简介:呼吸功能障碍(DB)可定义为排除潜在的呼吸或心脏疾病后,与呼吸和/或全身症状相关的呼吸模式改变。最近的证据表明,心肺运动试验(CPET)期间的通气分析表明,DB会导致covid -19后综合征(PCS)的呼吸困难。然而,缺乏对不同亚型DB的标准化分类给准确诊断和有效管理带来了挑战。我们假设分析CPET期间呼吸参数的演变可能有助于将DB分为三种模式。方法:我们分析了2020年7月至2022年5月期间对COVID-19感染后至少三个月出现持续呼吸道症状的患者进行的79例cpet。我们根据异常呼吸模式将患者分为三种不同的类型:换气过度(HYPV)、呼吸不稳定(ERBR)和压平(FLAT)。结果:年龄、身体质量指数、性别、最大摄氧量(V (O2))相似。与正常模式(N)相比,我们发现HYPV和FLAT的V / E - V / CO2斜率较高,而FLAT和ERBR的VT/ V / E斜率较低。与其他模式相比,FLAT模式的另一个特点是在高峰运动时呼吸频率更高。与n相比,ERBR和FLAT与更高的症状评分(奈梅根问卷和呼吸困难-12)相关。结论:分析渐进式运动期间通气参数的演变可以将呼吸功能障碍分为三种不同的呼吸模式:换气过度、呼吸不稳定和压平。
期刊介绍:
Respiratory Physiology & Neurobiology (RESPNB) publishes original articles and invited reviews concerning physiology and pathophysiology of respiration in its broadest sense.
Although a special focus is on topics in neurobiology, high quality papers in respiratory molecular and cellular biology are also welcome, as are high-quality papers in traditional areas, such as:
-Mechanics of breathing-
Gas exchange and acid-base balance-
Respiration at rest and exercise-
Respiration in unusual conditions, like high or low pressure or changes of temperature, low ambient oxygen-
Embryonic and adult respiration-
Comparative respiratory physiology.
Papers on clinical aspects, original methods, as well as theoretical papers are also considered as long as they foster the understanding of respiratory physiology and pathophysiology.