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Vaping use has skyrocketed especially among young adults, however there is no consensus on how vaping impacts the lungs. We aimed to determine whether there were changes in lung function acutely after a standard vaping session or if there were differences in lung function metrics between a healthy never‐vaping cohort (N = 6; 27.3 ± 3.0 years) and a young asymptomatic vaping cohort (N = 14; 26.4 ± 8.0 years) indicating chronic changes. Pulmonary function measurements and impulse oscillometry were obtained on all participants. Oxygen‐enhanced and Arterial Spin Labelling MRI were used to measure specific ventilation and perfusion, respectively, before and after vaping, and in the control cohort at baseline. MRI metrics did not show any significant differences in specific ventilation or perfusion after vaping. Heart rate increased post‐vaping (68.1 ± 10.5 to 71.3 ± 8.7, p = 0.020); however, this and other metrics did not show a nicotine dose‐dependent effect. There was a significant negative correlation between BMI and change in mean perfusion post‐vaping (p = 0.003); those with normal/low BMI showing an increase in perfusion and vice versa for high BMI. This may be due to subjects lying supine during vaping inhalation. Pulmonary function metrics indicative of airways resistance showed significant differences between the vaping and control cohorts indicating early airway changes.
Vaping use has skyrocketed especially among young adults, however there is no consensus on how vaping impacts the lungs. We aimed to determine whether there were changes in lung function acutely after a standard vaping session or if there were differences in lung function metrics between a healthy never‐vaping cohort (N = 6; 27.3 ± 3.0 years) and a young asymptomatic vaping cohort (N = 14; 26.4 ± 8.0 years) indicating chronic changes. Pulmonary function measurements and impulse oscillometry were obtained on all participants. Oxygen‐enhanced and Arterial Spin Labelling MRI were used to measure specific ventilation and perfusion, respectively, before and after vaping, and in the control cohort at baseline. MRI metrics did not show any significant differences in specific ventilation or perfusion after vaping. Heart rate increased post‐vaping (68.1 ± 10.5 to 71.3 ± 8.7, p = 0.020); however, this and other metrics did not show a nicotine dose‐dependent effect. There was a significant negative correlation between BMI and change in mean perfusion post‐vaping (p = 0.003); those with normal/low BMI showing an increase in perfusion and vice versa for high BMI. This may be due to subjects lying supine during vaping inhalation. Pulmonary function metrics indicative of airways resistance showed significant differences between the vaping and control cohorts indicating early airway changes.
IntroductionSmall airways dysfunction contributes to asthma pathophysiology and clinical outcomes including exacerbations and asthma control. Respiratory oscillometry is a simple, non-invasive and effort independent lung function test that provides vital information about small airway function. However, interpretation and clinical utility of respiratory oscillometry has been in part limited by lack of agreed parameters and the respective cutoffs. The aim of this study was to determine the prevalence of small airways dysfunction based on published impulse oscillometry (IOS) definition in patients with asthma referred to a tertiary asthma clinic and the extent to which it correlates with asthma clinical outcomes.MethodsWe retrospectively reviewed the medical records of all patients with asthma managed in the severe asthma clinic between January 2019 and December 2022 who underwent routine lung function tests with oscillometry and spirometry. Small airways dysfunction was determined from various published IOS parameter cutoffs, and the data were analysed to determine correlations between IOS parameters and asthma outcomes.ResultsAmongst the 148 patients, the prevalence of small airways dysfunction ranged from 53% to 78% depending on the defining oscillometry parameter. All oscillometry parameters correlated with the severity of airflow obstruction (FEV1% predicted, p < 0.001). Several oscillometry parameters correlated with asthma symptom burden, the strongest correlation was seen for frequency dependent resistance (R5–R20) with scores of Asthma Control Questionnaire (ACQ6) (Spearman's rank coefficient 0.213, p = 0.028) and Asthma Control Test (ACT) (Spearman's rank coefficient −0.248, p = 0.012). R5–R20 was predictive of poor asthma control defined by ACQ6 >1.5 (OR 2.97, p = 0.022) or ACT <20 (OR 2.44, p = 0.055). Small airways dysfunction defined by R5–R20 and area under the reactance curve (AX) also significantly increases asthma exacerbation risk (OR 2.60, p = 0.02 and OR 2.31, p = 0.03 respectively).ConclusionRespiratory oscillometry is a sensitive measure of small airways dysfunction that should complement spirometry in the routine assessment of asthma. Small airways dysfunction is highly prevalent in patients with asthma referred to a tertiary asthma clinic. R5–R20 was the metric most predictive in identifying patients at risk of asthma exacerbations and poor asthma control.
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