Asthma diagnosis: into the fourth dimension. Issue 6 (27th January 2021)

• Record Type: Journal Article
• Authors: Wang, Ran; Murray, Clare S; Fowler, Stephen J; Simpson, Angela; Durrington, Hannah Jane
• Is Part Of: Thorax. Volume 76:Issue 6(2021)
• Page Start: 624
• Page End: 631
• Publication Date: 2021-01-27
• Subjects: asthma -- asthma guidelines; Chest -- Diseases -- Periodicals; Thorax; Chest -- Diseases; Periodicals; Periodicals; 617.54
• DOI: 10.1136/thoraxjnl-2020-216421
• Languages: English
• ISSNs: 0040-6376

Abstract

Abstract : Asthma is the most common chronic respiratory disease in the UK; however, the misdiagnosis rate is substantial. The lack of consistency in national guidelines and the paucity of data on the performance of diagnostic algorithms compound the challenges in asthma diagnosis. Asthma is a highly rhythmic disease, characterised by diurnal variability in clinical symptoms and pathogenesis. Asthma also varies day to day, seasonally and from year to year. As much as it is a hallmark for asthma, this variability also poses significant challenges to asthma diagnosis. Almost all established asthma diagnostic tools demonstrate diurnal variation, yet few are performed with standardised timing of measurements. The dichotomous interpretation of diagnostic outcomes using fixed cut-off values may further limit the accuracy of the tests, particularly when diurnal variability straddles cut-off values within a day, and careful interpretation beyond the 'positive' and 'negative' outcome is needed. The day-to-day and more long-term variations are less predictable and it is unclear whether performing asthma diagnostic tests during asymptomatic periods may influence diagnostic sensitivities. With the evolution of asthma diagnostic tools, home monitoring and digital apps, novel strategies are needed to bridge these gaps in knowledge, and circadian variability should be considered during the standardisation process. This review summarises the biological mechanisms of circadian rhythms in asthma and highlights novel data on the significance of time (the fourth dimension) in asthma diagnosis.