The impact of physiological variability on asthma diagnosis and management

Student thesis: Phd

Abstract

One in 11 people in the UK are diagnosed with asthma but about a third who are treated for asthma do not have asthma at all, and many with asthma never receive a diagnosis and correct treatment. Managing patients with asthma and preventing asthma attacks is also challenging. The NHS spends £1.1 billion per year on asthma care. The symptoms of asthma are caused by airway narrowing and inflammation that comes and goes. Asthma symptoms often change during the day and typically worsen during night-time. Asthma symptoms can also change from day-to-day and upon exposure to triggers such as exercise or cold air. I studied how changes in asthma test results can affect how we diagnose and treat asthma. I found that within the same day the routine tests that we use to assess asthma can change depending on when the tests are performed. These changes may affect how we diagnose and treat individuals with asthma. I have also found that the changes in airway narrowing and inflammation from day to day can be a useful tool to tell doctors if patients' asthma is controlled. The levels of fractional exhaled nitric oxide (FeNO, a simple breath test to measure inflammation in the lungs) also change over the years when children grow, particularly during puberty. These changes should be taken into account when test results are interpreted. I have also found that giving asthma steroid inhalers in the mid-afternoon could better improve lung function and inflammation compared to in the morning, or twice a day (this is the usual way the doctors prescribe it). My work shows that the timing in performing asthma tests and giving treatment is important in asthma. The changes in asthma over time should also be considered by doctors when test results are interpreted.ƒ
Date of Award1 Aug 2024
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorStephen Fowler (Supervisor), Clare Murray (Supervisor), Angela Simpson (Supervisor) & Hannah Durrington (Supervisor)

Keywords

  • Variability
  • FeNO
  • Chronotherapy
  • Asthma
  • Diagnosis
  • Circadian

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