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Converting F ENO by different flows to standard flow F ENO
Author(s) -
LassmannKlee Paul G.,
Lehtimäki Lauri,
Lindholm Tuula,
Malmberg Leo Pekka,
Sovijärvi Anssi R.A.,
Piirilä Päivi Liisa
Publication year - 2019
Publication title -
clinical physiology and functional imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.608
H-Index - 67
eISSN - 1475-097X
pISSN - 1475-0961
DOI - 10.1111/cpf.12574
Subject(s) - medicine , exhaled nitric oxide , copd , asthma , exhalation , population , cardiology , anesthesia , spirometry , environmental health
In clinical practice, assessment of expiratory nitric oxide ( F ENO ) may reveal eosinophilic airway inflammation in asthmatic and other pulmonary diseases. Currently, measuring of F ENO is standardized to exhaled flow level of 50 ml s −1 , since the expiratory flow rate affects the F ENO results. To enable the comparison of F ENO measured with different expiratory flows, we firstly aimed to establish a conversion model to estimate F ENO at the standard flow level, and secondly, validate it in five external populations. F ENO measurements were obtained from 30 volunteers (mixed adult population) at the following multiple expiratory flow rates: 50, 30, 100 and 300 ml s −1 , after different mouthwash settings, and a conversion model was developed. We tested the conversion model in five populations: healthy adults, healthy children, and patients with COPD , asthma and alveolitis. F ENO conversions in the mixed adult population, in healthy adults and in children, showed the lowest deviation between estimatedF ^ ENO from 100 ml s −1 and measured F ENO at 50 mL s −1 : −0·28 ppb, −0·44 ppb and 0·27 ppb, respectively. In patients with COPD , asthma and alveolitis, the deviation was −1·16 ppb, −1·68 ppb and 1·47 ppb, respectively. We proposed a valid model to convert F ENO in healthy or mixed populations, as well as in subjects with obstructive pulmonary diseases and found it suitable for converting F ENO measured with different expiratory flows to the standard flow in large epidemiological data, but not on individual level. In conclusion, a model to convert F ENO from different flows to the standard flow was established and validated.