RT Journal Article
SR Electronic
T1 Variation Among Spirometry Interpretation Algorithms
JF Respiratory Care
FD American Association for Respiratory Care
SP 1585
OP 1590
DO 10.4187/respcare.07294
VO 65
IS 10
A1 Katrina A D’Urzo
A1 Florence Mok
A1 Anthony D D’Urzo
YR 2020
UL http://rc.rcjournal.com/content/65/10/1585.abstract
AB Several algorithms exist to facilitate spirometric interpretation in clinical practice, yet there is a lack of consensus on how spirometric criteria for asthma, COPD, and restrictive disorders should be incorporated into spirometry interpretation algorithms suitable for use in day-to-day primary care management. The purpose of this review was to identify and describe the variability that exists among spirometry interpretation algorithms and how this might be relevant to the interpretation of spirometric data of common conditions encountered in primary care. MEDLINE, Embase, and mainstream search engines were used to identify all English-language spirometry interpretation algorithm–related material between January 1990 and December 2018. Eight variations in spirometry interpretation algorithms were identified via specific a priori assumptions that each spirometry interpretation algorithm should contain content consistent with national and international guidelines related to spirometry interpretation. Of the 26 spirometry interpretation algorithms identified, 5 were deemed impractical for day-to-day use in primary care (19%), 23 lacked a logic string leading to the postbronchodilator FEV1/FVC (88%), 4 relied on postbronchodilator change in FEV1 to distinguish between asthma and COPD (15%), 24 lacked a prompt for bronchodilator challenge when FEV1/FVC was considered to be at a normal level (92%), 12 did not indicate whether the data represented a prebronchodilator or postbronchodilator scenario (46%), 7 did not include a logic string that considers mixed obstructive/restrictive defect (27%), 23 did not contain a prompt to refer for methacholine challenge testing when spirometry appeared normal (88%), and 2 spirometry interpretation algorithms did not include a logic string leading to restrictive disorder (8%). Our review suggests that there is considerable variability among spirometry interpretation algorithms available as diagnostic aids and that there is a need for standardization of spirometry interpretation algorithms in primary care.