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Phenotyping Exertional Breathlessness Using Cardiopulmonary Cycle Exercise Testing in People With Chronic Airflow
Magnus Ekström1, Pei Zhi Li2, Hayley Lewthwaite3
1Department of Clinical Sciences Lund, Respiratory Medicine, Allergology and Palliative Medicine, Faculty of Medicine, Lund University, Lund, Sweden.
Background:
Exertional breathlessness is a cardinal symptom of people with chronic airflow limitation (CAL) and can be evaluated using cardiopulmonary exercise testing (CPET).
Research Question:
Does abnormally high exertional breathlessness in relationship to the rate of oxygen uptake (V'O2) and minute ventilation (V'E) indicate different underlying pathophysiologic mechanisms and clinical characteristics in people with CAL?
Study Design And Methods:
Analysis of people aged ≥ 40 years with CAL (FEV1 to FVC ratio after bronchodilation less than lower limit of normal) undergoing symptom-limited incremental cycle CPET in the Canadian Cohort Obstructive Lung Disease study. Using published normative references, breathlessness phenotypes at peak exercise were categorized as abnormal (Borg 0-10 scale intensity rating more than upper limit of normal) by V'O2 alone, abnormal by both V'O2 and V'E, or normal by both V'O2 and V'E. Exercise physiologic responses and clinical characteristics were compared between groups.
Results:
We included 325 people (44% female) with CAL (mean [SD]) FEV1, 75.4 [17.5] % predicted). Compared with the normal by both V'O2 and V'E group (n = 237 [73%]), the abnormal by V'O2 only group (n = 29 [9%]) showed lower pulmonary diffusing capacity and greater exercise ventilatory inefficiency, whereas the abnormal by both V'O2 and V'E group (n = 50 [15%]) showed even worse lung function, dynamic critical inspiratory constraints, and exertional breathlessness along with greater symptom burden in daily life, lower physical activity, and worse health status.
Interpretation:
Our results show that exertional breathlessness phenotyped in relationship to V'O2 and V'E using normative reference equations enables multivariable analyses of underlying symptom mechanisms and associated clinical characteristics.
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