The optimum series of investigations to diagnose asthma

Abstract

Background: Asthma is frequently misdiagnosed attributed to lack of objective testing. The National Institute for Health and Care Excellence recommend diagnostic algorithms in attempt to improve diagnosis (NG80). Algorithms have not been validated. An evidenced based optimal approach to asthma diagnosis in steroid naïve symptomatic patients has yet to be established. The novel test Airways Oscillometry (AO) lacks evidence for its use in asthma diagnosis in steroid naïve symptomatic adults. The SARS-CoV-2 pandemic emphasises knowledge gaps in diagnosing asthma when aerosol generating procedures (AGPs) are not available. This thesis aims to address these gaps in knowledge. Methods: Symptomatic untreated patients were referred into 'Rapid Access Diagnostics in Asthma'€™ research clinic with clinician suspected asthma. Clinical consultation, all tests from the NG80 (FEV1/FVC ratio, BDR, PEFv, FeNO, BCTmeth), and other tests (blood eosinophils, skin prick testing, and airways oscillometry) were measured pre- and post- trial of treatment with inhaled corticosteroids. Expert panel confirmed or refuted asthma diagnosis. Results: NG80 algorithms confidently rule-in asthma but underdiagnose patients in a third of asthmatic adults and one in seven asthmatic children. Our recommended algorithm in adults (any one test positive of: wheeze auscultated, FEV1/FVC 20%, Eosinophils >0.4x109/L, BCTmeth PD20 ≤0.2), and children (any two tests positive of: wheeze auscultated, FEV1/FVC 20%, Eosinophils >0.4x109/L, FeNO ≥35ppb, BCTmeth PD20 ≤0.2), outperformed the current NG80. AO BDR (X5ex%change) was the only measure to discriminate asthma from non-asthma in symptomatic adults (p 0.014). Our non-AGP algorithm (any one positive of; auscultated wheeze, Eosinophils >0.4x109/L, PEFv(alternative) >20%) provided sensitivity 55%, specificity 100%, PPV 100%, NPV 60%, reducing the need for spirometry-based tests by one-third. Conclusions: National asthma guidance (NG80) rules-in asthma but underdiagnosed asthma risking misdiagnosis or treatment delay. Our alternative diagnostic algorithms (with and without AGPs) performed better to ‘rule-in’ asthma but require further validation. The novel test AO BDR was able to discriminate asthma from symptomatic “not asthmaâ€� in steroid naïve patients showing a potential role in asthma diagnosis.

Date of Award	1 Aug 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Stephen Fowler (Supervisor), Clare Murray (Supervisor) & Angela Simpson (Supervisor)